first presentation of diabetes mellitus

Type 1 Diabetes Mellitus Clinical Presentation

Author: Romesh Khardori, MD, PhD, FACP; Chief Editor: George T Griffing, MD more...
Sections Type 1 Diabetes Mellitus
Practice Essentials
Pathophysiology
Epidemiology
Patient Education
Physical Examination
Complications
Laboratory Studies
Tests to Differentiate Type 1 from Type 2 Diabetes
Approach Considerations
Self-Monitoring of Glucose Levels
Continuous Glucose Monitoring
Insulin Therapy
Management of Hypoglycemia
Management of Hyperglycemia
Management of Complications
Glycemic Control During Serious Medical Illness and Surgery
Glycemic Control During Pregnancy
Consultations
Medication Summary
Antidiabetics, Insulins
Antidiabetics, Amylinomimetics
Hypoglycemia Antidotes
Monoclonal Antibodies
Allogeneic Islet Cells
Questions & Answers

The most common symptoms of type 1 diabetes mellitus (DM) are polyuria, polydipsia, and polyphagia, along with lassitude, nausea, and blurred vision, all of which result from the hyperglycemia itself.

Polyuria is caused by osmotic diuresis secondary to hyperglycemia. Severe nocturnal enuresis secondary to polyuria can be an indication of onset of diabetes in young children. Thirst is a response to the hyperosmolar state and dehydration.

Fatigue and weakness may be caused by muscle wasting from the catabolic state of insulin deficiency, hypovolemia, and hypokalemia. Muscle cramps are caused by electrolyte imbalance. Blurred vision results from the effect of the hyperosmolar state on the lens and vitreous humor. Glucose and its metabolites cause osmotic swelling of the lens, altering its normal focal length.

Symptoms at the time of the first clinical presentation can usually be traced back several days to several weeks. However, beta-cell destruction may have started months, or even years, before the onset of clinical symptoms.

The onset of symptomatic disease may be sudden. It is not unusual for patients with type 1 DM to present with diabetic ketoacidosis (DKA), which may occur de novo or secondary to the stress of illness or surgery. An explosive onset of symptoms in a young lean patient with ketoacidosis always has been considered diagnostic of type 1 DM.

Over time, patients with new-onset type 1 DM will lose weight, despite normal or increased appetite, because of depletion of water and a catabolic state with reduced glycogen, proteins, and triglycerides. Weight loss may not occur if treatment is initiated promptly after the onset of the disease.

Gastrointestinal (GI) symptoms of type 1 DM are as follows:

Nausea, abdominal discomfort or pain, and change in bowel movements may accompany acute DKA

Acute fatty liver may lead to distention of the hepatic capsule, causing right upper quadrant pain

Persistent abdominal pain may indicate another serious abdominal cause of DKA (eg, pancreatitis

Chronic GI symptoms in the later stage of DM are caused by visceral autonomic neuropathy

Neuropathy affects up to 50% of patients with type 1 DM, but symptomatic neuropathy is typically a late development, developing after many years of chronic prolonged hyperglycemia. Peripheral neuropathy presents as numbness and tingling in both hands and feet, in a glove-and-stocking pattern; it is bilateral, symmetric, and ascending.

History in patients with established diabetes

It is important to inquire about the type and duration of the patient’s diabetes and about the care the patient is receiving for diabetes. Determination of the type of diabetes is based on history, therapy, and clinical judgment. The chronic complications of diabetes are related to the length of time the patient has had the disease.

Ask about the type of insulin being used, delivery system (pump vs injections), dose, and frequency. Also ask about oral antidiabetic agents, if any. Of course, a full review of all medications and over-the-counter supplements being taken is crucial in the assessment of patients with type 1 DM.

Patients using a pump or a multiple-injection regimen have a basal insulin (taken through the pump or with the injection of a long-acting insulin analogue) and a premeal rapid-acting insulin, the dose of which may be determined as a function of the carbohydrate count plus the correction (to adjust for how high the premeal glucose level is). In these patients, ask about the following:

Basal rates (eg, units per hour by pump, generally 0.4-1.5 U/h, potentially varying on the basis of time of day); the total daily dose as basal insulin is a helpful value to know

Carbohydrate ratio (ie, units of insulin per grams of carbohydrate, generally 1 unit of rapid-acting insulin per 10-15 g carbohydrate)

Correction dose (ie, how far the blood glucose level is expected to decrease per unit of rapid-acting insulin, often 1 U of insulin per 50-mg/dL decrease, though individuals with insulin resistance may need 1 U per 25-mg/dL decrease)

Some patients may be taking premeal pramlintide (an amylin analogue)

A focused diabetes history should also include the following questions:

Is the patient’s diabetes generally well controlled, with near-normal blood glucose levels? (Patients with poorly controlled blood glucose levels heal more slowly and are at increased risk for infection and other complications)

Does the patient have severe hypoglycemic reactions? (If the patient has episodes of severe hypoglycemia and therefore is at risk for losing consciousness, this possibility must be addressed, especially if the patient drives)

Does the patient have diabetic nephropathy that might alter the use of medications or intravenous (IV) radiographic contrast material?

Does the patient have macrovascular disease, such as coronary artery disease (CAD), which should be considered in the emergency department (ED)?

Does the patient self-monitor his or her blood glucose levels? (Note the frequency and range of values at each time of day; an increasing number of patients monitor with continuous sensors)

When was the patient’s hemoglobin A 1c (HbA 1c ) value (an indicator of long-term glucose control) last measured? What was it?

In assessing glycemic exposure of a patient with established type 1 DM, review of self-monitored blood glucose levels is necessary. Ideally, this done by uploading time- and date-stamped levels from the patient’s meter to assure full understanding of the frequency of testing and the actual levels.

Questions regarding hypoglycemia and hyperglycemia

Hypoglycemia and hyperglycemia should be considered. Ask the following questions as needed:

Has the patient experienced recent polyuria, polydipsia, nocturia, or weight loss?

Has the patient had episodes of unexplained hypoglycemia? If so, when, how often, and how does the patient treat these episodes?

Does the patient have hypoglycemia unawareness (ie, does the patient lack the adrenergic warning signs of hypoglycemia)? (Hypoglycemia unawareness indicates an increased risk of subsequent episodes of hypoglycemia)

Questions regarding microvascular complications

Microvascular complications, such as retinopathy and nephropathy, should be considered as well. Ask the following questions as appropriate:

When was the patient’s last dilated eye examination? What were the results?

Does the patient have known kidney disease?

What were the dates and results of the last measurements of urine protein and serum creatinine levels?

Questions regarding macrovascular complications

Macrovascular complications should be explored. Questions should include the following:

Does the patient have hypertension? What medications are taken?

Does the patient have symptoms of claudication or a history of vascular bypass?

Has the patient had a stroke or transient ischemic attack?

What are the patient’s most recent lipid levels?

Is the patient taking lipid-lowering medication?

Questions regarding neuropathy

Potential neuropathy should be taken into account. Ask whether the patient has a history of neuropathy or symptoms of peripheral neuropathy or whether autonomic neuropathy is present (including erectile dysfunction if the patient is a man).

Diabetes-focused examination

A diabetes-focused physical examination includes assessment of vital signs, funduscopic examination, limited vascular and neurologic examinations, and foot examination. Other organ systems should be assessed as indicated by the patient’s clinical situation. A comprehensive examination is not necessary at every visit.

Assessment of vital signs

Patients with established diabetes and autonomic neuropathy may have orthostatic hypotension. Orthostatic vital signs may be useful in assessing volume status and in suggesting the presence of an autonomic neuropathy. Measurement of the pulse is important, in that relative tachycardia is a typical finding in autonomic neuropathy, often preceding the development of orthostatic hypotension. If the respiratory rate and pattern suggest Kussmaul respiration, DKA must be considered immediately, and appropriate tests must be ordered.

Funduscopic examination

The funduscopic examination should include a careful view of the retina. Both the optic disc and the macula should be visualized. If hemorrhages or exudates are seen, the patient should be referred to an ophthalmologist as soon as possible. Examiners who are not ophthalmologists tend to underestimate the severity of retinopathy, which cannot be evaluated accurately unless the patients’ pupils are dilated.

Foot examination

The dorsalis pedis and posterior tibialis pulses should be palpated and their presence or absence noted. This is particularly important in patients who have foot infections: poor lower-extremity blood flow can delay healing and increase the risk of amputation.

Documenting lower-extremity sensory neuropathy is useful in patients who present with foot ulcers because decreased sensation limits the patient’s ability to protect the feet and ankles. If peripheral neuropathy is found, the patient should be made aware that foot care (including daily foot examination) is very important for the prevention of foot ulcers and lower-extremity amputation. (See Diabetic Foot and Diabetic Foot Infections .)

Infections cause considerable morbidity and mortality in patients with diabetes. Infection may precipitate metabolic derangements, and conversely, the metabolic derangements of diabetes may facilitate infection. (See Infections in Patients with Diabetes Mellitus .)

Patients with long-standing diabetes tend to have microvascular and macrovascular disease with resultant poor tissue perfusion and increased risk of infection. The ability of the skin to act as a barrier to infection may be compromised when the diminished sensation of diabetic neuropathy results in unnoticed injury.

Diabetes increases susceptibility to various types of infections. The most common sites are the skin and urinary tract. Dermatologic infections that occur with increased frequency in patients with diabetes include staphylococcal follicular skin infections, superficial fungal infections, cellulitis, erysipelas, and oral or genital candidal infections. Both lower urinary tract infections and acute pyelonephritis are seen with greater frequency.

A few infections, such as malignant otitis externa, rhinocerebral mucormycosis, and emphysematous pyelonephritis, occur almost exclusively in patients with diabetes, though they are fairly rare even in this population. Infections such as staphylococcal sepsis occur more frequently and are more often fatal in patients with diabetes than in others. Infections such as pneumococcal pneumonia affect patients with diabetes and other patients with the same frequency and severity. [ 84 ]

A study reported that out of 178 adult patients hospitalized with coronavirus disease 2019 (COVID-19), at least one underlying condition was found in 89.3%, the most common being hypertension (49.7%), obesity (48.3%), chronic lung disease (34.6%), diabetes mellitus (28.3%), and cardiovascular disease (27.8%). [ 85 ]

According to a report by Stokes et al, out of 287,320 US cases of COVID-19 in which the patient’s underlying health status was known, diabetes was the second most common underlying condition (30%), after cardiovascular disease (32%), which in this study included hypertension. [ 86 , 87 ]

The aforementioned study by Barrera et al found the overall prevalence of diabetes in patients with COVID-19 to be 12%, with the prevalence being 18% in severe COVID-19. [ 63 , 64 ]

In patients with type 1 DM who were diagnosed with COVID-19, a study by Ebekozien et al found that high blood glucose (48.5%), elevated temperature (45.5%), dry cough (39.4%), excess fatigue (33.3%), vomiting (33.3%), shortness of breath (30.3), nausea (30.2%), and body aches/headaches (21.2%) were the most prevalent presenting symptoms reported. Moreover, diabetic ketoacidosis was the most prevalent adverse outcome (45.5%) among these patients. [ 88 , 89 ]

The Centers for Disease Control and Prevention (CDC) includes type 2 DM in the list of conditions that increase the likelihood of severe illness in persons with COVID-19, and type 1 DM in the list of conditions that may increase this likelihood. [ 90 ]

Ophthalmologic complications

Diabetes can affect the lens, vitreous, and retina, causing visual symptoms that may prompt the patient to seek emergency care. Visual blurring may develop acutely as the lens changes shape with marked changes in blood glucose concentrations.

This effect, which is caused by osmotic fluxes of water into and out of the lens, usually occurs as hyperglycemia increases, but it also may be seen when high glucose levels are lowered rapidly. In either case, recovery to baseline visual acuity can take up to a month, and some patients are almost completely unable to read small print or do close work during this period.

Patients with diabetes tend to develop senile cataracts at a younger age than persons without diabetes. Rarely, patients with type 1 DM that is very poorly controlled (eg, those with frequent episodes of DKA) can acutely develop a “snowflake” (or “metabolic”) cataract. Named for their snowflake or flocculent appearance, these cataracts can progress rapidly and create total opacification of the lens within a few days.

Whether diabetes increases the risk of glaucoma remains controversial; epidemiologic studies have yielded conflicting results. [ 91 ] Glaucoma in diabetes relates to the neovascularization of the iris (ie, rubeosis iridis diabetica).

Diabetic retinopathy is the principal ophthalmologic complication of DM. (See Diabetic Retinopathy .) Diabetic retinopathy is the leading cause of blindness in the United States in people younger than 60 years and affects the eyes in the following different ways:

Background retinopathy involves retinal small vessel abnormality leading to hard exudates, hemorrhages, and microaneurysms; it does not affect acuity

Proliferative retinopathy involves extensive proliferation of new retinal small blood vessels; a sudden loss of vision can occur because of vitreous hemorrhage from proliferating new vessels or retinal detachment

Maculopathy involves edema and hard exudate or retinal ischemia; it causes a marked reduction of acuity

Whether patients develop diabetic retinopathy depends on the duration of their diabetes and on the level of glycemic control. [ 92 , 93 , 94 ] The following are the 5 stages in the progression of diabetic retinopathy:

Dilation of the retinal venules and formation of retinal capillary microaneurysms

Increased vascular permeability

Vascular occlusion and retinal ischemia

Proliferation of new blood vessels on the surface of the retina

Hemorrhage and contraction of the fibrovascular proliferation and the vitreous

The first 2 stages of diabetic retinopathy are jointly referred to as background or nonproliferative retinopathy. Initially, the retinal venules dilate, then microaneurysms (tiny red dots on the retina that cause no visual impairment) appear. The microaneurysms or retinal capillaries become more permeable, and hard exudates appear, reflecting leakage of plasma.

Rupture of intraretinal capillaries results in hemorrhage. If a superficial capillary ruptures, a flame-shaped hemorrhage appears. Hard exudates are often found in partial or complete rings (circinate pattern), which usually include multiple microaneurysms. These rings usually mark an area of edematous retina.

The patient may not notice a change in visual acuity unless the center of the macula is involved. Macular edema can cause visual loss; therefore, all patients with suspected macular edema must be referred to an ophthalmologist for evaluation and possible laser therapy. Laser therapy is effective in decreasing macular edema and preserving vision but is less effective in restoring lost vision. (See Macular Edema in Diabetes .)

Preproliferative (stage 3) and proliferative diabetic retinopathy (stages 4 and 5) are the next phases in the progression of the disease. Cotton-wool spots can be seen in preproliferative retinopathy. These represent retinal microinfarcts from capillary occlusion and appear as off-white to gray patches with poorly defined margins.

Proliferative retinopathy is characterized by neovascularization, or the development of networks of fragile new vessels that often are seen on the optic disc or along the main vascular arcades. The vessels undergo cycles of proliferation and regression. During proliferation, fibrous adhesions develop between the vessels and the vitreous. Subsequent contraction of the adhesions can result in traction on the retina and retinal detachment. Contraction also tears the new vessels, which hemorrhage into the vitreous.

Diabetic nephropathy

About 20–30% of patients with type 1 DM develop evidence of nephropathy, [ 95 ] and all patients with diabetes should be considered to have the potential for renal impairment unless proven otherwise. Chronically elevated blood pressure contributes to the decline in renal function. The use of contrast media can precipitate acute renal failure in patients with underlying diabetic nephropathy. Although most recover from contrast medium–induced renal failure within 10 days, some have irreversible renal failure. (See Diabetic Nephropathy .)

Diabetic neuropathy

In the peripheral nerves, diabetes causes peripheral neuropathy. (See Diabetic Lumbosacral Plexopathy and Diabetic Neuropathy .) The 4 types of diabetic neuropathy are as follows:

Peripheral distal symmetrical polyneuropathy, predominantly sensory

Autonomic neuropathy

Proximal painful motor neuropathy

Cranial mononeuropathy (ie, cranial nerve III, IV, or VI)

Of these 4 types, distal symmetric sensorimotor polyneuropathy (in a glove-and-stocking distribution) is the most common. [ 96 ] Besides causing pain in its early stages, this type of neuropathy eventually results in the loss of peripheral sensation. The combination of decreased sensation and peripheral arterial insufficiency often leads to foot ulceration and eventual amputation.

Acute-onset mononeuropathies in diabetes include acute cranial mononeuropathies, mononeuropathy multiplex, focal lesions of the brachial or lumbosacral plexus, and radiculopathies. Of the cranial neuropathies, the third cranial nerve (oculomotor) is most commonly affected, followed by the sixth nerve (abducens) and the fourth nerve (trochlear).

Patients can present with diplopia and eye pain. In diabetic third-nerve palsy, the pupil is usually spared, whereas in third-nerve palsy due to intracranial aneurysm or tumor, the pupil is affected in 80-90% of cases.

It is important to consider nondiabetic causes of cranial nerve palsies, including intracranial tumors, aneurysms, and brainstem stroke. [ 97 ] Therefore, evaluation should include nonenhanced and contrast-enhanced compute4d tomography (CT) or, preferably, magnetic resonance imaging (MRI). Neurologic consultation is recommended. Acute cranial-nerve mononeuropathies usually resolve in 2-9 months. Acute thrombosis or ischemia of the blood vessels supplying the structure involved is thought to cause these neuropathies.

Macrovascular complications

People with diabetes experience accelerated atherosclerosis, affecting the small arteries of the heart, brain, lower extremity, and kidney. Coronary atherosclerosis often occurs at a younger age and is more severe and extensive than in those without diabetes, increasing the risk of ischemic heart disease. Atherosclerosis of the internal carotid and vertebrobasilar arteries and their branches predisposes to cerebral ischemia.

Severe atherosclerosis of the iliofemoral and smaller arteries of the lower legs predisposes to gangrene. Ischemia of a single toe or ischemic areas on the heel are characteristic of diabetic peripheral vascular disease; these result from the involvement of much smaller and more peripheral arteries.

Atherosclerosis of the main renal arteries and their intrarenal branches causes chronic nephron ischemia, which is a significant component of multiple renal lesions in diabetes. However, not all people with type 1 DM are at risk for nephropathy, because there are some polymorphisms in the various factors involved in its pathogenesis, which can modulate the course of this disease from one person to the other.

Risk factors for macrovascular disease

Macrovascular disease is the leading cause of death in patients with diabetes, causing 65-75% of deaths in this group, compared with approximately 35% of deaths in people without diabetes. Diabetes by itself increases the risk of myocardial infarction (MI) 2-fold in men and 4-fold in women, and many patients have other risk factors for MI as well.

The HbA1c value per se, rather than self-reported diabetes status or other established risk factors, robustly predicts MI odds. Each 1% increment in HbA1c independently predicts 19% higher odds for MI. [ 98 ] The risk of stroke in people with diabetes is double that of nondiabetic people, and the risk of peripheral vascular disease is 4 times that of people without diabetes.

Patients with diabetes may have an increased incidence of silent ischemia. [ 99 ] Diastolic dysfunction is common in patients with diabetes and should be considered in patients who have symptoms of congestive heart failure and a normal ejection fraction.

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Herold KC, Bundy BN, Long SA, and the, Type 1 Diabetes TrialNet Study Group. An Anti-CD3 Antibody, Teplizumab, in Relatives at Risk for Type 1 Diabetes. N Engl J Med . 2019 Aug 15. 381 (7):603-13. [QxMD MEDLINE Link] . [Full Text] .

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[Guideline] Donaghue KC, Marcovecchio ML, Wadwa RP, et al. ISPAD Clinical Practice Consensus Guidelines 2018: microvascular and macrovascular complications in children and adolescents. Pediatr Diabetes . 2018 Oct. 19 Suppl 27:262-74. [QxMD MEDLINE Link] . [Full Text] .

[Guideline] DiMeglio LA, Acerini CL, Codner E, et al. ISPAD Clinical Practice Consensus Guidelines 2018: glycemic control targets and glucose monitoring for children, adolescents, and young adults with diabetes. Pediatr Diabetes . 2018 Oct. 19 Suppl 27:105-14. [QxMD MEDLINE Link] . [Full Text] .

[Guideline] LeRoith D, Biessels GJ, Braithwaite SS, et al. Treatment of Diabetes in Older Adults: An Endocrine Society* Clinical Practice Guideline. J Clin Endocrinol Metab . 2019 May 1. 104 (5):1520-74. [QxMD MEDLINE Link] . [Full Text] .

[Guideline] Tucker ME. New Endocrine Society Guidelines Address Diabetes in Older Adults. Medscape Medical News . 2019 Mar 23. [Full Text] .

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US Food and Drug Administration. FDA authorizes first interoperable, automated insulin dosing controller designed to allow more choices for patients looking to customize their individual diabetes management device system. Available at https://www.fda.gov/news-events/press-announcements/fda-authorizes-first-interoperable-automated-insulin-dosing-controller-designed-allow-more-choices?fbclid=IwAR3TSBssEd4n6b9hR5oe9Bzwmz3su1yQny8bcQeHVi0WFSsvURBh3nPjR-Y . December 13, 2019; Accessed: December 1, 2020.

[Guideline] American Diabetes Association. Standards of medical care in diabetes-2015 abridged for primary care providers. Clin Diabetes . 2015 Apr. 33 (2):97-111. [QxMD MEDLINE Link] . [Full Text] .

Brooks M. FDA Clears Blood Test to Help Diagnose Type 1 Diabetes. Medscape Medical News . Aug 21 2014. [Full Text] .

Hsiao-Chuan L, et al. Enterovirus infection is associated with an increased risk of childhood type 1 diabetes in Taiwan: A nationwide population-based cohort study. Diabetologia . 2014. [Full Text] .

Leegaard A, Riis A, Kornum JB, et al. Diabetes, Glycemic Control, and Risk of Tuberculosis: A population-based case-control study. Diabetes Care . 2011 Dec. 34(12):2530-5. [QxMD MEDLINE Link] . [Full Text] .

Ludwig J, Sanbonmatsu L, Gennetian L, et al. Neighborhoods, obesity, and diabetes--a randomized social experiment. N Engl J Med . 2011 Oct 20. 365(16):1509-19. [QxMD MEDLINE Link] .

[Guideline] Peters A, Laffel L. Diabetes Care for Emerging Adults: Recommendations for Transition From Pediatric to Adult Diabetes Care Systems: A position statement of the American Diabetes Association, with representation by the American College of Osteopathic Family Physicians, the American Academy of Pediatrics, the American Association of Clinical Endocrinologists, the American Osteopathic Association, the Centers for Disease Control and Prevention, Children with Diabetes, The Endocrine Society, the International Socie... Diabetes Care . 2011 Nov. 34(11):2477-85. [QxMD MEDLINE Link] . [Full Text] .

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Contributor Information and Disclosures

Romesh Khardori, MD, PhD, FACP (Retired) Professor, Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, Eastern Virginia Medical School Romesh Khardori, MD, PhD, FACP is a member of the following medical societies: American Association of Clinical Endocrinology , American College of Physicians , American Diabetes Association , Endocrine Society Disclosure: Nothing to disclose.

George T Griffing, MD Professor Emeritus of Medicine, St Louis University School of Medicine George T Griffing, MD is a member of the following medical societies: American Association for Physician Leadership , American Association for the Advancement of Science , American College of Medical Practice Executives , American College of Physicians , American Diabetes Association , American Federation for Medical Research , American Heart Association , Central Society for Clinical and Translational Research , Endocrine Society , International Society for Clinical Densitometry , Southern Society for Clinical Investigation Disclosure: Nothing to disclose.

Howard A Bessen, MD Professor of Medicine, Department of Emergency Medicine, University of California, Los Angeles, David Geffen School of Medicine; Program Director, Harbor-UCLA Medical Center

Howard A Bessen, MD is a member of the following medical societies: American College of Emergency Physicians

Disclosure: Nothing to disclose.

Barry E Brenner, MD, PhD, FACEP Professor of Emergency Medicine, Professor of Internal Medicine, Program Director, Emergency Medicine, Case Medical Center, University Hospitals, Case Western Reserve University School of Medicine

Barry E Brenner, MD, PhD, FACEP is a member of the following medical societies: Alpha Omega Alpha , American Academy of Emergency Medicine , American College of Chest Physicians , American College of Emergency Physicians , American College of Physicians , American Heart Association , American Thoracic Society , Arkansas Medical Society , New York Academy of Medicine , New York Academy ofSciences ,and Society for Academic Emergency Medicine

Aneela Naureen Hussain, MD, FAAFM Assistant Professor, Department of Family Medicine, State University of New York Downstate Medical Center; Consulting Staff, Department of Family Medicine, University Hospital of Brooklyn

Aneela Naureen Hussain, MD, FAAFM is a member of the following medical societies: American Academy of Family Physicians , American Medical Association , American Medical Women's Association , Medical Society of the State of New York , and Society of Teachers of Family Medicine

Anne L Peters, MD, CDE Director of Clinical Diabetes Programs, Professor, Department of Medicine, University of Southern California, Keck School of Medicine, Los Angeles, California, Los Angeles County/University of Southern California Medical Center

Anne L Peters, MD, CDE is a member of the following medical societies: American College of Physicians and American Diabetes Association

Disclosure: Amylin Honoraria Speaking and teaching; AstraZeneca Consulting fee Consulting; Lilly Consulting fee Consulting; Takeda Consulting fee Consulting; Bristol Myers Squibb Honoraria Speaking and teaching; NovoNordisk Consulting fee Consulting; Medtronic Minimed Consulting fee Consulting; Dexcom Honoraria Speaking and teaching; Roche Honoraria Speaking and teaching

Don S Schalch, MD Professor Emeritus, Department of Internal Medicine, Division of Endocrinology, University of Wisconsin Hospitals and Clinics

Don S Schalch, MD is a member of the following medical societies: American Diabetes Association , American Federation for Medical Research , Central Society for Clinical Research , and Endocrine Society

Erik D Schraga, MD Staff Physician, Department of Emergency Medicine, Mills-Peninsula Emergency Medical Associates

Francisco Talavera, PharmD, PhD Adjunct Assistant Professor, University of Nebraska Medical Center College of Pharmacy; Editor-in-Chief, Medscape Drug Reference

Disclosure: Medscape Salary Employment

Miriam T Vincent, MD, PhD Professor and Chair, Department of Family Practice, State University of New York Downstate Medical Center

Miriam T Vincent, MD, PhD is a member of the following medical societies: Alpha Omega Alpha , American Academy of Family Physicians , American Association for the Advancement of Science , Medical Society of the State of New York , North American Primary Care Research Group , Sigma Xi , and Society of Teachers of Family Medicine

Disclosure: Joslin Diabetes Group, Harvard Honoraria Speaking and teaching

Scott R Votey, MD Director of Emergency Medicine Residency, Ronald Reagan UCLA Medical Center; Professor of Medicine/Emergency Medicine, University of California, Los Angeles, David Geffen School of Medicine

Scott R Votey, MD is a member of the following medical societies: Society for Academic Emergency Medicine

Frederick H Ziel, MD Associate Professor of Medicine, University of California, Los Angeles, David Geffen School of Medicine; Physician-In-Charge, Endocrinology/Diabetes Center, Director of Medical Education, Kaiser Permanente Woodland Hills; Chair of Endocrinology, Co-Chair of Diabetes Complete Care Program, Southern California Permanente Medical Group

Frederick H Ziel, MD is a member of the following medical societies: American Association of Clinical Endocrinologists , American College of Endocrinology , American College of Physicians , American College of Physicians-American Society of Internal Medicine , American Diabetes Association , American Federation for Medical Research , American Medical Association , American Society for Bone and Mineral Research , California Medical Association , Endocrine Society , andInternational Society for Clinical Densitometry

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Type 1 Diabetes Mellitus
Pediatric Type 1 Diabetes Mellitus
Type 2 Diabetes Mellitus
Pediatric Type 2 Diabetes Mellitus
Fast Five Quiz: How Much Do You Know About Diabetic Neuropathy?
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Perioperative Management of the Diabetic Patient
Diabetes Mellitus Type 1 News & Perspectives
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'No Excuses': Training for the Olympics with Type 1 Diabetes
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General presentation

Diabetes mellitus (DM) is an important endocrine disorder that presents commonly in children and adolescents. There are two types of diabetes mellitus: type 1 and type 2. Type 1 DM is one of the most common chronic diseases in children and is characterized by insulin deficiency as a result of autoimmune destruction of pancreatic beta islet cells; whereas type 2 DM is the presence of high blood glucose with insulin resistance and relative insulin deficiency. Diabetes mellitus is a chronic condition that requires long-term follow-up and adequate patient (and parent) education to maintain good glycemic control to prevent long-term complications.

Epidemiology

Approximately 2/3 of all new diabetes diagnoses in patients less than 19 years of age in the United States are type 1 DM. Over 300,000 Canadians have type 1 DM, with a 3-5% increase each year; especially in children aged 5-9. Typically, the age of onset has a bimodal distribution, with the first peak in children 4-6 years old, and the second peak in children 10-14 years old (early puberty). Unlike other autoimmune diseases, the overall incidence appears to be equal in both genders. There is a higher risk of developing this condition in children with close relatives who have type 1 DM.

The incidence of type 2 DM has increased 10 fold in the last decade. There is an estimated 3600/100,000 cases of type 2 DM in Canadian adolescents and 1100/100,000 cases in Canadian children. This value may be as high as 1% in Canadian aboriginal youths and children. There is a strong association between increasing rates of obesity in the pediatric population and the development of type 2 DM.

Basic Physiology

In type 1 DM, there is autoimmune-mediated destruction of insulin-producing pancreatic beta cells that results in insulin deficiency. It is a progressive condition that occurs in genetically susceptible individuals. The autoimmune destruction can be triggered by various environmental agents. Some proposed environmental factors include pregnancy-related and perinatal influences, viruses, cow’s milk and cereals. There is a long latency period (where the patient is asymptomatic and euglycemic) between the onset of beta cell destruction and clinical presentation of diabetes mellitus. A large number of functional beta cells must be lost before clinical symptoms like hyperglycemia occurs.

Genetic polymorphisms in six genes have been shown to be associated with type 1 DM. Major Histocompatibility Complex genes and elsewhere in the genome all contribute to the risk, but only the HLA alleles seem to have a large effect.

The natural history has four stages:

Preclinical autoimmune destruction of pancreatic beta cells
Onset of clinical symptoms
Transient remission
Established diabetes with acute and chronic complications

Type 2 DM is a complex, multifactorial disease characterized by both relative insulin deficiency and insulin resistance with various environmental and behavioural risk factors. Increased hepatic glucose production, insulin resistance and progressive loss of glucose-stimulated insulin release all contribute to the development of hyperglycemia. In Type 2 DM, pancreatic beta cells retain the ability to produce insulin, but levels are not adequate to counteract the developing insulin resistance. The current theory is that insulin resistance develops first, followed and complicated by gradual destruction of beta cells. Insulin resistance worsens with obesity and physical inactivity; and improves with weight loss and increased physical exercise.

Puberty also plays a role in the development of type 2 DM in adolescents. During this period, insulin sensitivity is approximately 30% lower than that of preadolescents or adults, which results in hyperinsulinemia as a compensatory mechanism. In adolescents with both genetic predisposition and negative environmental contributors, this period of relative insulin resistance may result in a decompensated state (inadequate insulin secretion and glucose intolerance). The resulting hyperglycemic state may cause worsening abnormalities of insulin secretion and action, starting a vicious cycle that progress beyond the adolescent years.

Clinical Presentation

Childhood type 1 DM can present in the following ways:

Classic new onset:

Hyperglycemia without acidosis

Symptoms include:

Can present as nocturia, bedwetting, daytime incontinence in a previously continent child
Polydipsia – due to increased serum osmolality and hypovolemia
Impaired glucose utilization in skeletal muscle and increased fat and muscle breakdown

Diabetic ketoacidosis

Similar symptoms but are usually more severe

Clinical: polydipsia, polyuria, dehydration, hypotension, ketosis, etc.
Metabolic: hyperglycemia, glycosuria, metabolic acidosis, ketonemia, etc.

Reported frequency varies between 15-67%

Young children (<6) from low socioeconomic backgrounds are more likely to present with diabetic ketoacidosis

Silent Presentation

Diagnosis before onset of clinical symptoms

Typically occurs in children with a family member with type 1 DM (close monitoring)

Childhood type 2 DM can present in the following ways:

Hyperglycemia, ketonuria, acidosis
Frequency varies between 5-25%

Hyperosmolar hyperglycemic state

Marked hyperglycemia (>33.3 mmol/L) and severe dehydration but no ketonuria
Less common in adolescents

Symptomatic

Due to hyperglycemia and include: polyuria, polydipsia, and nocturia
Recent weight loss is less frequent
Adolescent girls: vaginal discharge due to candida infection may be initial presentation

Asymptomatic

Identified based on screening (for type 2 DM or urinalysis as part of a regular physical exam)

Questions to ask

Historical Investigation

Presenting condition:

Have you been very thirsty? Do you drink a lot?
Have you been urinating more than usual?
Has the child had any bedwetting episodes?
Has there been any recent weight loss?
Have you been feeling tired lately?
Have you noticed an increased appetite lately?
Has the child had more frequent minor skin infections?

Predisposing factors:

Have you had any viral infections recently?
What kinds of exercise do you participate in on a regular basis? How frequent do you exercise? How long do you exercise each time?
How many hours a day do you spend watching TV, using the computer, and play video games?
What do you normally eat? What is the portion size? How many meals do you have per day? Do you normally eat out or home cooked meals? Do you eat as a family? Do you eat at the table or in front of the tv?

Family history:

Are there any family members with insulin-dependent diabetes mellitus?
Are there any family members with autoimmune conditions?
Does your mother or father have diabetes?
Are there any other family members with diabetes? (grandparents, aunts, uncles, brothers, sisters, etc.)

Physical Examination

Do a complete physical exam with particular attention to the following:

Assess hydration status
Assess circulation: HR, BP, capillary refill
Temperature: coexisting infection
Use growth chart to check for weight loss
Neck examination: look for thyroid abnormalities
Respiratory: respiratory rate (hyperventilation – DKA), auscultation (respiratory infection), ketones on breath (DKA)
Measure body weight and height, calculate BMI
Measure lying and standing BP
Inspect skin for acanthosisnigricans
Examine feet to look for decreased sensation and circulation (pulses)
Measure visual acuity

Differential diagnosis

DM types 1 and 2
Diabetes insipidus
Urinary tract infection
Malabsorption (e.g. Celiac disease)
Secondary diabetes
Maturity-onset diabetes of the young

Procedures for investigation

Diagnostic Criteria

Fasting plasma glucose >7 mmol/L (no caloric intake for at least 8 hours)
Symptoms of hyperglycemia, random venous plasma glucose >11.1 mmol/L
Abnormal oral glucose tolerance test – plasma glucose >11.1 mmol/L measured 2 hours after a glucose load of 1.75 g/kg (max 75g)
Glycated hemoglobin (A1C) ≥ 6.5%

Other Investigations

Urinalysis for glucosuria and ketonuria
Urinalysis for microalbuminemia
Alemzadeh R, Wyatt DT. Section 6 – Diabetes mellitus in children. In: Kliegman: Nelson Textbook of Pediatrics. 18 th ed. Saunders, Pennsylvania. 2007
Eisenbarth GS, McCulloch DK. Pathogenesis of type 1 diabetes mellitus. In: UpToDate, Basow, DS (Ed), UpToDate, Waltham, MA, 2011
Laffel L, Svoren B. Epidemiology, presentation, and diagnosis of type 2 diabetes mellitus in children and adolescents. In: UpToDate, Basow, DS (Ed), UpToDate, Waltham, MA, 2011
Levinson P, Nelson BA, Scherger JE. Diabetes mellitus type 1 in children. [Online]. 2007. Availabe from: FirstConsult, MDConsult. [cited 2011 Jan 15]
Levitsky LL, Misra M. Epidemiology, presentation, and diagnosis of type 1 diabetes mellitus in children and adolescents. In: UpToDate, Basow, DS (Ed), UpToDate, Waltham, MA, 2011
McCulloch DK, Robertson RP. Pathogenesis of type 2 diabetes mellitus. In: UpToDate, Basow, DS (Ed), UpToDate, Waltham, MA, 2011
Panagiotopoulos C. Type 2 diabetes in children and adolescents. BCMJ. 2004;46(9): 461-466
Scherger JE, McIntire SDC, Escobar O, Heinzman DM. Diabetes mellitus type 2 in children. [Online]. 2007. Availabe from: FirstConsult, MDConsult. [cited 2011 Jan 15]

Acknowledgements

Written by: Ying Yao

Edited by: Dianna Louie

Last updated on November 10, 2011 @5:01 pm

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Basics of cardiac pharmacology
Approach to cardiac history taking
Congestive heart failure in children
Approach to Pediatric Hypertension
Approach to Cyanotic Congenital Heart Disease in the Newborn
Approach to Syncope: Is it Cardiac or Not?
Approach to Pediatric Tachycardia
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Basic Physiology and Approach to Heart Sounds
Approach to Pediatric ECGs
Care of a Child with Turner Syndrome
Approach to the Underweight Child
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Approach to Vomiting
Suspected Foreign Body Ingestion
Approach to a Mediastinal Mass
Toxic Ingestion
Nutritional Deficiencies
Pharmacology of Common Agents Used in Gastrointestinal Conditions
Approach to Pediatric Abdominal Pain
Pediatric Gastrointestinal History Taking
Approach to diarrhea
Approach to a picky eater
Constipation
Hepatomegaly
Splenomegaly
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Failure to Thrive
Approach to Skin Lesions
Common Paediatric Skin Conditions & Birthmarks
Approach to the child with mental health concerns
Child with a sore ear (Otalgia)
To vaccinate or not to vaccinate
Approach to a the Child with a Fever and Rash
Approach to a Routine Adolescent Interview
Sore Throat in Children – Clinical Considerations and Evaluation
Approach to Strabismus
Approach to Adolescent Substance Use
Approach to the Child Who is Dry
Conjunctivitis: Approach to the Child with a Red Eye
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Pediatric Neck Mass
Fetal Alcohol Spectrum Disorder
To Circumcise or Not to Circumcise
Approach to inborn errors of metabolism
Infants of Diabetic Mothers
Fever in the Newborn Period
Neonatal Thrombocytopenia
Consequences of Prematurity
Respiratory Distress in the Newborn
Approach to Neonatal Cyanosis
Approach to the Child with IUGR/SGA
Neonatal Jaundice
Breastfeeding Problems
Diaper Rash: Clinical Considerations and Evaluation
The Pediatric Neurological History
Evaluation of Pediatric Development (Normal)
Closed Head Injury in Pediatrics
Approach to the Ataxic Child
Approach to the Child with a Seizure
Basics to the Approach of Developmental Delay
Lumbar Puncture in Pediatrics
The Basics of Cerebral Palsy
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Febrile Seizures
Approach to the Comatose Child
Basics of Spina Bifida
Principles of Pharmacotherapy in Neurology
Easy Bleeding
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Tumor Lysis Syndrome
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Pediatric Neutropenia
Blood Transfusion Reactions
Approach to Sickle Cell Disease
Iron-deficiency and Health Consequences in Children
Easy Clotting
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Approach to Pediatric Leukemias and Lymphomas
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Approach to Non-Accidental Injuries
Common Pediatric Bone Diseases-Approach to Pathological Fractures
Infant with an Abnormal Hip Exam
Knock Kneed Children
Elbow Injuries
Approach to the Child with a Limp
Pediatric Fractures
Clearing the C - Spine
Approach to a Child With a Cough
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Introduction
Systemic Exam
Kidneys and Bladder
Male Infants
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General exam
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General Inspection
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Patient Care & Health Information
Diseases & Conditions
Type 1 diabetes

What is type 1 diabetes? A Mayo Clinic expert explains

Learn more about type 1 diabetes from endocrinologist Yogish Kudva, M.B.B.S.

I'm Dr. Yogish C. Kudva an endocrinologist at Mayo Clinic. In this video, we'll cover the basics of type 1 diabetes. What is it? Who gets it? The symptoms, diagnosis, and treatment. Whether you're looking for answers for yourself or someone you love. We are here to give you the best information available. Type 1 diabetes is a chronic condition that affects the insulin making cells of the pancreas. It's estimated that about 1.25 million Americans live with it. People with type 1 diabetes don't make enough insulin. An important hormone produced by the pancreas. Insulin allows your cells to store sugar or glucose and fat and produce energy. Unfortunately, there is no known cure. But treatment can prevent complications and also improve everyday life for patients with type 1 diabetes. Lots of people with type 1 diabetes live a full life. And the more we learn and develop treatment for the disorder, the better the outcome.

We don't know what exactly causes type 1 diabetes. We believe that it is an auto-immune disorder where the body mistakenly destroys insulin producing cells in the pancreas. Typically, the pancreas secretes insulin into the bloodstream. The insulin circulates, letting sugar enter your cells. This sugar or glucose, is the main source of energy for cells in the brain, muscle cells, and other tissues. However, once most insulin producing cells are destroyed, the pancreas can't produce enough insulin, meaning the glucose can't enter the cells, resulting in an excess of blood sugar floating in the bloodstream. This can cause life-threatening complications. And this condition is called diabetic ketoacidosis. Although we don't know what causes it, we do know certain factors can contribute to the onset of type 1 diabetes. Family history. Anyone with a parent or sibling with type 1 diabetes has a slightly increased risk of developing it. Genetics. The presence of certain genes can also indicate an increased risk. Geography. Type 1 diabetes becomes more common as you travel away from the equator. Age, although it can occur at any age there are two noticeable peaks. The first occurs in children between four and seven years of age and the second is between 10 and 14 years old.

Signs and symptoms of type 1 diabetes can appear rather suddenly, especially in children. They may include increased thirst, frequent urination, bed wetting in children who previously didn't wet the bed. Extreme hunger, unintended weight loss, fatigue and weakness, blurred vision, irritability, and other mood changes. If you or your child are experiencing any of these symptoms, you should talk to your doctor.

The best way to determine if you have type 1 diabetes is a blood test. There are different methods such as an A1C test, a random blood sugar test, or a fasting blood sugar test. They are all effective and your doctor can help determine what's appropriate for you. If you are diagnosed with diabetes, your doctor may order additional tests to check for antibodies that are common in type 1 diabetes in the test called C-peptide, which measures the amount of insulin produced when checked simultaneously with a fasting glucose. These tests can help distinguish between type 1 and type 2 diabetes when a diagnosis is uncertain.

If you have been diagnosed with type 1 diabetes, you may be wondering what treatment looks like. It could mean taking insulin, counting carbohydrates, fat protein, and monitoring your glucose frequently, eating healthy foods, and exercising regularly to maintain a healthy weight. Generally, those with type 1 diabetes will need lifelong insulin therapy. There are many different types of insulin and more are being developed that are more efficient. And what you may take may change. Again, your doctor will help you navigate what's right for you. A significant advance in treatment from the last several years has been the development and availability of continuous glucose monitoring and insulin pumps that automatically adjust insulin working with the continuous glucose monitor. This type of treatment is the best treatment at this time for type 1 diabetes. This is an exciting time for patients and for physicians that are keen to develop, prescribe such therapies. Surgery is another option. A successful pancreas transplant can erase the need for additional insulin. However, transplants aren't always available, not successful and the procedure can pose serious risks. Sometimes it may outweigh the dangers of diabetes itself. So transplants are often reserved for those with very difficult to manage conditions. A successful transplant can bring life transforming results. However, surgery is always a serious endeavor and requires ample research and concentration from you, your family, and your medical team.

The fact that we don't know what causes type 1 diabetes can be alarming. The fact that we don't have a cure for it even more so. But with the right doctor, medical team and treatment, type 1 diabetes can be managed. So those who live with it can get on living. If you would like to learn even more about type 1 diabetes, watch our other related videos or visit mayoclinic.org. We wish you well.

Type 1 diabetes, once known as juvenile diabetes or insulin-dependent diabetes, is a chronic condition. In this condition, the pancreas makes little or no insulin. Insulin is a hormone the body uses to allow sugar (glucose) to enter cells to produce energy.

Different factors, such as genetics and some viruses, may cause type 1 diabetes. Although type 1 diabetes usually appears during childhood or adolescence, it can develop in adults.

Even after a lot of research, type 1 diabetes has no cure. Treatment is directed toward managing the amount of sugar in the blood using insulin, diet and lifestyle to prevent complications.

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Type 1 diabetes symptoms can appear suddenly and may include:

Feeling more thirsty than usual
Urinating a lot
Bed-wetting in children who have never wet the bed during the night
Feeling very hungry
Losing weight without trying
Feeling irritable or having other mood changes
Feeling tired and weak
Having blurry vision

When to see a doctor

Talk to your health care provider if you notice any of the above symptoms in you or your child.

The exact cause of type 1 diabetes is unknown. Usually, the body's own immune system — which normally fights harmful bacteria and viruses — destroys the insulin-producing (islet) cells in the pancreas. Other possible causes include:

Exposure to viruses and other environmental factors

The role of insulin

Once a large number of islet cells are destroyed, the body will produce little or no insulin. Insulin is a hormone that comes from a gland behind and below the stomach (pancreas).

The pancreas puts insulin into the bloodstream.
Insulin travels through the body, allowing sugar to enter the cells.
Insulin lowers the amount of sugar in the bloodstream.
As the blood sugar level drops, the pancreas puts less insulin into the bloodstream.

The role of glucose

Glucose — a sugar — is a main source of energy for the cells that make up muscles and other tissues.

Glucose comes from two major sources: food and the liver.
Sugar is absorbed into the bloodstream, where it enters cells with the help of insulin.
The liver stores glucose in the form of glycogen.
When glucose levels are low, such as when you haven't eaten in a while, the liver breaks down the stored glycogen into glucose. This keeps glucose levels within a typical range.

In type 1 diabetes, there's no insulin to let glucose into the cells. Because of this, sugar builds up in the bloodstream. This can cause life-threatening complications.

Risk factors

Some factors that can raise your risk for type 1 diabetes include:

Family history. Anyone with a parent or sibling with type 1 diabetes has a slightly higher risk of developing the condition.
Genetics. Having certain genes increases the risk of developing type 1 diabetes.
Geography. The number of people who have type 1 diabetes tends to be higher as you travel away from the equator.
Age. Type 1 diabetes can appear at any age, but it appears at two noticeable peaks. The first peak occurs in children between 4 and 7 years old. The second is in children between 10 and 14 years old.

Complications

Over time, type 1 diabetes complications can affect major organs in the body. These organs include the heart, blood vessels, nerves, eyes and kidneys. Having a normal blood sugar level can lower the risk of many complications.

Diabetes complications can lead to disabilities or even threaten your life.

Heart and blood vessel disease. Diabetes increases the risk of some problems with the heart and blood vessels. These include coronary artery disease with chest pain (angina), heart attack, stroke, narrowing of the arteries (atherosclerosis) and high blood pressure.

Nerve damage (neuropathy). Too much sugar in the blood can injure the walls of the tiny blood vessels (capillaries) that feed the nerves. This is especially true in the legs. This can cause tingling, numbness, burning or pain. This usually begins at the tips of the toes or fingers and spreads upward. Poorly controlled blood sugar could cause you to lose all sense of feeling in the affected limbs over time.

Damage to the nerves that affect the digestive system can cause problems with nausea, vomiting, diarrhea or constipation. For men, erectile dysfunction may be an issue.

Kidney damage (nephropathy). The kidneys have millions of tiny blood vessels that keep waste from entering the blood. Diabetes can damage this system. Severe damage can lead to kidney failure or end-stage kidney disease that can't be reversed. End-stage kidney disease needs to be treated with mechanical filtering of the kidneys (dialysis) or a kidney transplant.
Eye damage. Diabetes can damage the blood vessels in the retina (part of the eye that senses light) (diabetic retinopathy). This could cause blindness. Diabetes also increases the risk of other serious vision conditions, such as cataracts and glaucoma.
Foot damage. Nerve damage in the feet or poor blood flow to the feet increases the risk of some foot complications. Left untreated, cuts and blisters can become serious infections. These infections may need to be treated with toe, foot or leg removal (amputation).
Skin and mouth conditions. Diabetes may leave you more prone to infections of the skin and mouth. These include bacterial and fungal infections. Gum disease and dry mouth also are more likely.
Pregnancy complications. High blood sugar levels can be dangerous for both the parent and the baby. The risk of miscarriage, stillbirth and birth defects increases when diabetes isn't well-controlled. For the parent, diabetes increases the risk of diabetic ketoacidosis, diabetic eye problems (retinopathy), pregnancy-induced high blood pressure and preeclampsia.

There's no known way to prevent type 1 diabetes. But researchers are working on preventing the disease or further damage of the islet cells in people who are newly diagnosed.

Ask your provider if you might be eligible for one of these clinical trials. It is important to carefully weigh the risks and benefits of any treatment available in a trial.

Summary of revisions: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-Srev.
Papadakis MA, et al., eds. Diabetes mellitus. In: Current Medical Diagnosis & Treatment 2022. 61st ed. McGraw Hill; 2022. https://accessmedicine.mhmedical.com. Accessed May 4, 2022.
What is diabetes? National Institute of Diabetes and Digestive and Kidney Diseases. https://www.niddk.nih.gov/health-information/diabetes/overview/what-is-diabetes. Accessed May 4, 2022.
Levitsky LL, et al. Epidemiology, presentation, and diagnosis of type 1 diabetes mellitus in children and adolescents. https://www.uptodate.com/contents/search. Accessed May 4, 2022.
Diabetes mellitus (DM). Merck Manual Professional Version. https://www.merckmanuals.com/professional/endocrine-and-metabolic-disorders/diabetes-mellitus-and-disorders-of-carbohydrate-metabolism/diabetes-mellitus-dm. Accessed May 4, 2022.
AskMayoExpert. Type 1 diabetes mellitus. Mayo Clinic; 2021.
Robertson RP. Pancreas and islet transplantation in diabetes mellitus. https://www.uptodate.com/contents/search. Accessed May 4, 2022.
Levitsky LL, et al. Management of type 1 diabetes mellitus in children during illness, procedures, school, or travel. https://www.uptodate.com/contents/search. Accessed May 4, 2022.
Hyperglycemia (high blood glucose). American Diabetes Association. https://www.diabetes.org/healthy-living/medication-treatments/blood-glucose-testing-and-control/hyperglycemia. Accessed May 4, 2022.
Diabetes and DKA (ketoacidosis). American Diabetes Association. https://www.diabetes.org/diabetes/dka-ketoacidosis-ketones. Accessed May 4, 2022.
Insulin resistance & prediabetes. National Institute of Diabetes and Digestive and Kidney Diseases. https://www.niddk.nih.gov/health-information/diabetes/overview/what-is-diabetes/prediabetes-insulin-resistance. Accessed May 4, 2022.
Blood sugar and insulin at work. American Diabetes Association. https://www.diabetes.org/tools-support/diabetes-prevention/high-blood-sugar. Accessed May 4, 2022.
Inzucchi SE, et al. Glycemic control and vascular complications in type 1 diabetes. https://www.uptodate.com/contents/search. Accessed May 4, 2022.
Diabetes and oral health. American Diabetes Association. https://www.diabetes.org/diabetes/keeping-your-mouth-healthy. Accessed May 4, 2022.
Drug treatment of diabetes mellitus. Merck Manual Professional Version. https://www.merckmanuals.com/professional/endocrine-and-metabolic-disorders/diabetes-mellitus-and-disorders-of-carbohydrate-metabolism/drug-treatment-of-diabetes-mellitus. Accessed May 4, 2022.
Weinstock DK, et al. Management of blood glucose in adults with type 1 diabetes mellitus. https://www.uptodate.com/contents/search. Accessed May 7, 2022.
FDA proves first automated insulin delivery device for type 1 diabetes. U.S. Food and Drug Administration. https://www.fda.gov/news-events/press-announcements/fda-approves-first-automated-insulin-delivery-device-type-1-diabetes. Accessed May 4, 2022.
Boughton CK, et al. Advances in artificial pancreas systems. Science Translational Medicine. 2019; doi:10.1126/scitranslmed.aaw4949.
Hypoglycemia (low blood sugar). American Diabetes Association. https://www.diabetes.org/healthy-living/medication-treatments/blood-glucose-testing-and-control/hypoglycemia. Accessed May 4, 2022.
Diabetes in the workplace and the ADA. U.S. Equal Opportunity Employment Commission. https://www.eeoc.gov/laws/guidance/diabetes-workplace-and-ada. Accessed May 4, 2022.
Cardiovascular disease and risk management: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S010.
Diabetes technology. Standards of Medical Care in Diabetes — 2022. 2022; doi:10.2337/dc22-S007.
FDA authorizes a second artificial pancreas system. JDRF. https://www.jdrf.org/blog/2019/12/13/jdrf-reports-fda-authorizes-second-artificial-pancreas-system/. Accessed May 4, 2022.
Classification and diagnosis of diabetes: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S002.
Retinopathy, neuropathy, and foot care: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S012.
Glycemic targets: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S012.
Pharmacologic approaches to glycemic treatment: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S009.
Facilitating behavior change and well-being to improve health outcomes: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S005.
Centers for Disease Control and Prevention. Use of hepatitis B vaccination for adults with diabetes mellitus: Recommendations of the Advisory Committee on Immunization Practices (ACIP). Morbidity and Mortality Weekly Report. 2011;60:1709.
Management of diabetes in pregnancy: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S015.
Older adults: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S013.
FDA approves first-of-its-kind automated insulin delivery and monitoring system for use in young pediatric patients. U.S. Food and Drug Administration. https://www.fda.gov/news-events/press-announcements/fda-approves-first-its-kind-automated-insulin-delivery-and-monitoring-system-use-young-pediatric#:~:text=Today, the U.S. Food and,by individuals aged 2 to. Accessed May 8, 2022.
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Pathophysiology and Clinical Presentation

Pathophysiology:

Type 1 Diabetes Mellitus is a syndrome characterized by hyperglycemia and insulin deficiency resulting from the loss of beta cells in pancreatic islets (Mapes & Faulds, 2014). Nonimmune (type 1B diabetes), occurs secondary to other diseases and is much less common than autoimmune (type 1A). The destruction of beta cells in Type 1A diabetes results from the interaction of both genetic and environmental factors. Although the genetic susceptibility is not well understood, type 1 diabetes is most strongly associated with major histocompatibility complex (MHC), specifically histocompatibility leukocyte antigen (HLA) class II alleles (HLA-DQ and HLA-DR) (McCance & Heuther, 2014). Type 1 diabetes is less hereditary than type 2 but 7-13% of patients also have a first degree relative with type 1 diabetes (Mapes & Faulds, 2014). Environmental factors include viral infections (especially enteroviruses), exposure to infectious microorganisms (such as Helicobacter pylori ), exposure to cow’s milk proteins and a lack of vitamin D (McCance & Heuther, 2014).

The destruction of insulin-producing beta cells in the pancreas starts with the formation of autoantigens. These autoantigens are ingested by antigen-presenting cells which activate T helper 1 (Th1) and T helper 2 (Th2) lmphocytes. Activated Th1 lymphocytes secrete interluekin-2 (IL-2) and interferon. IL-2 activates autoantigen-specific T cytotoxic lymphocytes which destroy islet cells through the secretion of toxic perforins and granzymes. Interferon activates macrophages and stimulates the release of inflammatory cytokines (including IL-1 and tumor necrosis factor [TNF]) which further destroy beta cells (McCance & Heuther, 2014). Activated Th2 lymphocytes produce IL-4 which stimulates B lymphocytes to proliferate and produce islet cell autoantibodies (ICAs) and anti-glutamic acid decarboxylase (antiGAD65) antibodies. AntiGAD65 is an enzyme that helps control the release of insulin from beta cells and can be used to determine the cause of diabetes (McCance & Heuther, 2014). Insulin autoantibodies [IAAs]) and zinc transporter 8 (Znt8) protein are also associated with type 1 diabetes mellitus. Despite it’s complicated pathophysiology, it is important to understand the destruction of beta cells in type 1 diabetes because it leads to a lack of insulin and amylin. Without insulin or amylin the body cannot promote glucose disappearance or limit glucose appearance from the bloodstream, respectively, resulting in hyperglycemia (Mapes & Faulds, 2014).

Clinical Presentation:

Type 1 diabetes does not present clinically until 80-90% of the beta cells have been destroyed (McCance & Heuther, 2014). Because insulin stimulates glucose uptake into tissues, stores glycose as glycogen, inhibits glucagon secretion and inhibits glucose production from the liver, the destruction of insulin-producing beta cells causes hyperglycemia (Mapes & Faulds, 2014). Type 1 diabetics may present with abrupt onset of diabetic ketoacidosis, polyuria, polyphagia, polydipsia, or rapid weight loss with marked hyperglycemia (Mapes & Faulds, 2014). To diagnose diabetes, patients must have an A1C level greater than 6.5% percent on two separate tests; the presence of ketones in the urine and/or autoantibodies in the blood can distinguish type 1 from type 2 diabetes (Mayo Clinic, 2014).

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In this section

Diabetes mellitus

This guideline has been adapted for statewide use with the support of the Victorian Paediatric Clinical Network

Diabetic Ketoacidosis (DKA)

Diabetes insipidus

Diabetic Mellitus and Endoscopy

Diabetes Mellitus and Surgery

Diabetes phone calls (Management of Diabetes phone calls)

Background

All patients presenting with a blood glucose level (BGL) ≥11.1 mmol/L should have blood ketones tested on a capillary sample using a bedside Optium TM meter.

If this test is positive (>0.6 mmol/L), assess for acidosis to determine further management, see Diabetic Ketoacidosis (DKA) . Urinalysis can be used for initial assessment if blood ketone testing is not available
If ketones are negative, or the pH is normal in the presence of ketones, patients can be managed with subcutaneous (subcut) insulin

New presentation diabetes, mildly ill

<3% dehydration, no acidosis and not vomiting

Investigations for all children newly diagnosed with diabetes

Check blood ketones (bedside test) on all patients presenting with BGL ≥11.1 mmol/L.

If ketones positive (>0.6), assess for acidosis with a venous blood gas; if pH <7.30, proceed as per Diabetic Ketoacidosis (DKA) .
Ketones may be present without acidosis; if this is the case, continue to monitor ketones with each BGL to ensure they are clearing with insulin therapy (monitor until 2 consecutive levels are <0.6 and again if any BGL is >15.0 mmol/L).
GAD antibodies, insulin antibodies, coeliac screen, thyroid function tests

Additional tests to consider

For children / adolescents who are overweight or have clinical evidence of acanthosis nigricans:

C-peptide and insulin levels (may help to distinguish Type 2 diabetes, although T1DM still more likely in this scenario)
lipid profile

The decision about the individual insulin regimen will be made by the paediatric diabetes team in discussion with the family and child. The regimens outlined below are a guide only and individual clinicians may recommend an alternative approach.

Initial Treatment

0.25 units/kg of quick-acting insulin subcut stat.

If within 2 hr prior to a meal defer and give meal-time dose only.
Halve dose if ≤4 yr old. Dose may be lower if not ketotic.

Ongoing Treatment

Standard insulin regimens in newly diagnosed patients may comprise either of the two regimens below:

1. Twice daily injections of a mixture of short and intermediate-acting insulins:

Usually commence with total daily dose (TDD) of 1 unit/kg/day but this may need modification (eg less in younger child aged <5 years).

This is given as 2/3 of TDD in morning, 1/3 of TDD at night. 2/3 of each dose as intermediate-acting insulin, 1/3 as short-acting insulin.

Note: In children who will be starting twice daily injections but who present after 2200 hrs, it may be too late to start with a mixture of intermediate and short acting insulins. In this instance, give 0.25 U/kg short-acting insulin, which may need to be repeated after 4-6 hours, with a snack (depending on BGL, ketones and interval to breakfast).

2. Multiple daily injections (MDI) of insulin using a long-acting insulin analogue at night and pre-meal injections of rapid-acting insulin analogue

Also start with TDD of ~1.0 U/kg/day.

Give 0.4U/kg as basal insulin (long-acting insulin analogue eg insulin glargine) at ~2000- 2100 hrs.
Give the remainder as rapid-acting insulin in 3 equal doses before meals (ie ~0.2 U/kg before each main meal).
If children who will start MDI regimens present during the day, slightly higher pre-meal doses may be necessary (eg 0.25 U/kg) until basal insulin is given that evening.

In general, multiple daily injection regimens offer greater lifestyle flexibility (around mealtimes, sport etc); however the child must be old enough to learn how to administer insulin using a pen device without parental supervision (eg at school). This is usually possible with children aged >10 years. Twice daily mixed injections are usually commenced in children <10 years.

When to admit/consult local paediatric team:

All new presentations of diabetes. In many places these children need to be admitted for commencement of insulin and diabetic education.

When to consider transfer to tertiary centre:

Children requiring care above the level of comfort of the local hospital.

For emergency advice and paediatric or neonatal ICU transfers, call the Paediatric Infant Perinatal Emergency Retrieval (PIPER) Service: 1300 137 650.

Diabetes Ambulatory Care Service (DACS) allows for many newly diagnosed children with diabetes to not require hospitalization. Please see relevant paediatric diabetes protocol on MMC intranet policies and procedures site.

AnGel cream can be used for initial doses of insulin in a newly diagnosed child

Children who are well at diagnosis (not acidotic, well hydrated and tolerating oral intake) may be eligible to have their diabetes education and initial stabilisation as an ambulatory care patient. Additional eligibility criteria include age >3 years, English speaking family, living within the HITH catchment area, contactable by telephone and absence of any familial / psychosocial impediment to safe care in the community. Prior to linking into this program, children need to have met with the diabetes team (medical team, social worker and diabetes educator) to be assessed for suitability and also to have an initial education session around blood glucose testing and management of hypoglycemia. Hospital in the Home nurses also need to be available to attend the family home to support injections. These requirements generally mean that children who present after lunchtime will not be discharged to HITH until the following day. Direct access to ambulatory care on day of diagnosis is also not possible for children whose initial presentation is on Friday, Saturday or Sunday.

Hyperglycaemic, ketotic mildly ill patients with established diabetes

Patients with established T1DM who present with hyperglycaemia and ketosis but normal pH , will need additional subcut insulin to clear their ketones.

(i) Patients on intermittent daily injections of insulin (bd or MDI)

Give 10% of the patient's total daily insulin dose as a sub-cut injection of rapid-acting insulin (this is in addition to usual insulin regimen). Monitor BGL and ketones 1-2 hourly. This dose of rapid-acting insulin can be repeated after 2-4 hours if blood ketones are not <1.0 mmol/L.

(ii) Patients on insulin pump therapy

Need to assume line failure / blockage has interrupted insulin delivery. Give 20% of the patient's total daily insulin dose as a s.c. injection of rapid-acting insulin (higher dose relative to above patient group is because there is no longer acting insulin 'on board' in pump patients). Once subcut insulin has been given, ask the patient or family to resite the pump cannula and commence delivery at usual settings. Monitor BGL and ketones 1-2 hourly. For patients on pump therapy, ketones should clear to <0.6 mmol/L.

Notify local paediatric team or paediatric endocrinologist if there are any management issues that you want to discuss. If discharged home, the family should be advised to check BGLs and ketones regularly and to follow up with their diabetes nurse educator the following day.

Consider transfer when:

Information Specific to RCH

Diabetic educators and the endocrinology team are available for help with management.

Classification

Diagnostic tests for diabetes, type 1 diabetes, prediabetes and type 2 diabetes, cystic fibrosis–related diabetes, posttransplantation diabetes mellitus, monogenic diabetes syndromes, pancreatic diabetes or diabetes in the context of disease of the exocrine pancreas, gestational diabetes mellitus, 2. classification and diagnosis of diabetes: standards of medical care in diabetes—2021.

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American Diabetes Association; 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes—2021 . Diabetes Care 1 January 2021; 44 (Supplement_1): S15–S33. https://doi.org/10.2337/dc21-S002

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The American Diabetes Association (ADA) “Standards of Medical Care in Diabetes” includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee ( https://doi.org/10.2337/dc21-SPPC ), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction ( https://doi.org/10.2337/dc21-SINT ). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC .

Diabetes can be classified into the following general categories:

Type 1 diabetes (due to autoimmune β-cell destruction, usually leading to absolute insulin deficiency, including latent autoimmune diabetes of adulthood)

Type 2 diabetes (due to a progressive loss of adequate β-cell insulin secretion frequently on the background of insulin resistance)

Specific types of diabetes due to other causes, e.g., monogenic diabetes syndromes (such as neonatal diabetes and maturity-onset diabetes of the young), diseases of the exocrine pancreas (such as cystic fibrosis and pancreatitis), and drug- or chemical-induced diabetes (such as with glucocorticoid use, in the treatment of HIV/AIDS, or after organ transplantation)

Gestational diabetes mellitus (diabetes diagnosed in the second or third trimester of pregnancy that was not clearly overt diabetes prior to gestation)

This section reviews most common forms of diabetes but is not comprehensive. For additional information, see the American Diabetes Association (ADA) position statement “Diagnosis and Classification of Diabetes Mellitus” ( 1 ).

Type 1 diabetes and type 2 diabetes are heterogeneous diseases in which clinical presentation and disease progression may vary considerably. Classification is important for determining therapy, but some individuals cannot be clearly classified as having type 1 or type 2 diabetes at the time of diagnosis. The traditional paradigms of type 2 diabetes occurring only in adults and type 1 diabetes only in children are no longer accurate, as both diseases occur in both age-groups. Children with type 1 diabetes typically present with the hallmark symptoms of polyuria/polydipsia, and approximately one-third present with diabetic ketoacidosis (DKA) ( 2 ). The onset of type 1 diabetes may be more variable in adults; they may not present with the classic symptoms seen in children and may experience temporary remission from the need for insulin ( 3 – 5 ). Occasionally, patients with type 2 diabetes may present with DKA ( 6 ), particularly ethnic and racial minorities ( 7 ). It is important for the provider to realize that classification of diabetes type is not always straightforward at presentation and that misdiagnosis is common (e.g., adults with type 1 diabetes misdiagnosed as having type 2 diabetes; individuals with maturity-onset diabetes of the young [MODY] misdiagnosed as having type 1 diabetes, etc.). Although difficulties in distinguishing diabetes type may occur in all age-groups at onset, the diagnosis becomes more obvious over time in people with β-cell deficiency.

In both type 1 and type 2 diabetes, various genetic and environmental factors can result in the progressive loss of β-cell mass and/or function that manifests clinically as hyperglycemia. Once hyperglycemia occurs, patients with all forms of diabetes are at risk for developing the same chronic complications, although rates of progression may differ. The identification of individualized therapies for diabetes in the future will require better characterization of the many paths to β-cell demise or dysfunction ( 8 ). Across the globe many groups are working on combining clinical, pathophysiological, and genetic characteristics to more precisely define the subsets of diabetes currently clustered into the type 1 diabetes versus type 2 diabetes nomenclature with the goal of optimizing treatment approaches. Many of these studies show great promise and may soon be incorporated into the diabetes classification system ( 9 ).

Characterization of the underlying pathophysiology is more precisely developed in type 1 diabetes than in type 2 diabetes. It is now clear from studies of first-degree relatives of patients with type 1 diabetes that the persistent presence of two or more islet autoantibodies is a near certain predictor of clinical hyperglycemia and diabetes. The rate of progression is dependent on the age at first detection of autoantibody, number of autoantibodies, autoantibody specificity, and autoantibody titer. Glucose and A1C levels rise well before the clinical onset of diabetes, making diagnosis feasible well before the onset of DKA. Three distinct stages of type 1 diabetes can be identified ( Table 2.1 ) and serve as a framework for future research and regulatory decision-making ( 8 , 10 ). There is debate as to whether slowly progressive autoimmune diabetes with an adult onset should be termed latent autoimmune diabetes in adults (LADA) or type 1 diabetes. The clinical priority is awareness that slow autoimmune β-cell destruction can occur in adults leading to a long duration of marginal insulin secretory capacity. For the purpose of this classification, all forms of diabetes mediated by autoimmune β-cell destruction are included under the rubric of type 1 diabetes. Use of the term LADA is common and acceptable in clinical practice and has the practical impact of heightening awareness of a population of adults likely to develop overt autoimmune β-cell destruction ( 11 ), thus accelerating insulin initiation prior to deterioration of glucose control or development of DKA ( 4 , 12 ).

Staging of type 1 diabetes ( 8 , 10 )

.	Stage 1 .	Stage 2 .	Stage 3 .
Characteristics	• Autoimmunity	• Autoimmunity	• New-onset hyperglycemia
	• Normoglycemia	• Dysglycemia	• Symptomatic
	• Presymptomatic	• Presymptomatic
Diagnostic criteria	• Multiple autoantibodies	• Multiple autoantibodies	• Clinical symptoms
	• No IGT or IFG	• Dysglycemia: IFG and/or IGT	• Diabetes by standard criteria
		• FPG 100 125 mg/dL (5.6 6.9 mmol/L)
		• 2-h PG 140 199 mg/dL (7.8 11.0 mmol/L)
		• A1C 5.7 6.4% (39 47 mmol/mol) or ≥10% increase in A1C

.	Stage 1 .	Stage 2 .	Stage 3 .
Characteristics	• Autoimmunity	• Autoimmunity	• New-onset hyperglycemia
	• Normoglycemia	• Dysglycemia	• Symptomatic
	• Presymptomatic	• Presymptomatic
Diagnostic criteria	• Multiple autoantibodies	• Multiple autoantibodies	• Clinical symptoms
	• No IGT or IFG	• Dysglycemia: IFG and/or IGT	• Diabetes by standard criteria
		• FPG 100 125 mg/dL (5.6 6.9 mmol/L)
		• 2-h PG 140 199 mg/dL (7.8 11.0 mmol/L)
		• A1C 5.7 6.4% (39 47 mmol/mol) or ≥10% increase in A1C

FPG, fasting plasma glucose; IFG, impaired fasting glucose; IGT, impaired glucose tolerance; 2-h PG, 2-h plasma glucose.

The paths to β-cell demise and dysfunction are less well defined in type 2 diabetes, but deficient β-cell insulin secretion, frequently in the setting of insulin resistance, appears to be the common denominator. Type 2 diabetes is associated with insulin secretory defects related to inflammation and metabolic stress among other contributors, including genetic factors. Future classification schemes for diabetes will likely focus on the pathophysiology of the underlying β-cell dysfunction ( 8 , 9 , 13 – 15 ).

Diabetes may be diagnosed based on plasma glucose criteria, either the fasting plasma glucose (FPG) value or the 2-h plasma glucose (2-h PG) value during a 75-g oral glucose tolerance test (OGTT), or A1C criteria ( 16 ) ( Table 2.2 ).

Criteria for the diagnosis of diabetes

FPG ≥126 mg/dL (7.0 mmol/L). Fasting is defined as no caloric intake for at least 8 h.

2-h PG ≥200 mg/dL (11.1 mmol/L) during OGTT. The test should be performed as described by WHO, using a glucose load containing the equivalent of 75 g anhydrous glucose dissolved in water.

A1C ≥6.5% (48 mmol/mol). The test should be performed in a laboratory using a method that is NGSP certified and standardized to the DCCT assay.

In a patient with classic symptoms of hyperglycemia or hyperglycemic crisis, a random plasma glucose ≥200 mg/dL (11.1 mmol/L).

FPG ≥126 mg/dL (7.0 mmol/L). Fasting is defined as no caloric intake for at least 8 h.

2-h PG ≥200 mg/dL (11.1 mmol/L) during OGTT. The test should be performed as described by WHO, using a glucose load containing the equivalent of 75 g anhydrous glucose dissolved in water.

A1C ≥6.5% (48 mmol/mol). The test should be performed in a laboratory using a method that is NGSP certified and standardized to the DCCT assay.

In a patient with classic symptoms of hyperglycemia or hyperglycemic crisis, a random plasma glucose ≥200 mg/dL (11.1 mmol/L).

DCCT, Diabetes Control and Complications Trial; FPG, fasting plasma glucose; OGTT, oral glucose tolerance test; WHO, World Health Organization; 2-h PG, 2-h plasma glucose.

In the absence of unequivocal hyperglycemia, diagnosis requires two abnormal test results from the same sample or in two separate test samples.

Generally, FPG, 2-h PG during 75-g OGTT, and A1C are equally appropriate for diagnostic screening. It should be noted that the tests do not necessarily detect diabetes in the same individuals. The efficacy of interventions for primary prevention of type 2 diabetes ( 17 , 18 ) has mainly been demonstrated among individuals who have impaired glucose tolerance (IGT) with or without elevated fasting glucose, not for individuals with isolated impaired fasting glucose (IFG) or for those with prediabetes defined by A1C criteria.

The same tests may be used to screen for and diagnose diabetes and to detect individuals with prediabetes ( Table 2.2 and Table 2.5 ) ( 19 ). Diabetes may be identified anywhere along the spectrum of clinical scenarios—in seemingly low-risk individuals who happen to have glucose testing, in individuals tested based on diabetes risk assessment, and in symptomatic patients.

Fasting and 2-Hour Plasma Glucose

The FPG and 2-h PG may be used to diagnose diabetes ( Table 2.2 ). The concordance between the FPG and 2-h PG tests is imperfect, as is the concordance between A1C and either glucose-based test. Compared with FPG and A1C cut points, the 2-h PG value diagnoses more people with prediabetes and diabetes ( 20 ). In people in whom there is discordance between A1C values and glucose values, FPG and 2-h PG are more accurate ( 21 ).

Recommendations

2.1 To avoid misdiagnosis or missed diagnosis, the A1C test should be performed using a method that is certified by the NGSP and standardized to the Diabetes Control and Complications Trial (DCCT) assay. B

2.2 Marked discordance between measured A1C and plasma glucose levels should raise the possibility of A1C assay interference and consideration of using an assay without interference or plasma blood glucose criteria to diagnose diabetes. B

2.3 In conditions associated with an altered relationship between A1C and glycemia, such as hemoglobinopathies including sickle cell disease, pregnancy (second and third trimesters and the postpartum period), glucose-6-phosphate dehydrogenase deficiency, HIV, hemodialysis, recent blood loss or transfusion, or erythropoietin therapy, only plasma blood glucose criteria should be used to diagnose diabetes. (See other conditions altering the relationship of a1c and glycemia below for more information.) B

The A1C test should be performed using a method that is certified by the NGSP ( www.ngsp.org ) and standardized or traceable to the Diabetes Control and Complications Trial (DCCT) reference assay. Although point-of-care A1C assays may be NGSP certified and cleared by the U.S. Food and Drug Administration (FDA) for use in monitoring glycemic control in people with diabetes in both Clinical Laboratory Improvement Amendments (CLIA)-regulated and CLIA-waived settings, only those point-of-care A1C assays that are also cleared by the FDA for use in the diagnosis of diabetes should be used for this purpose, and only in the clinical settings for which they are cleared. As discussed in Section 6 “Glycemic Targets” ( https://doi.org/10.2337/dc21-S006 ), point-of-care A1C assays may be more generally applied for assessment of glycemic control in the clinic.

A1C has several advantages compared with FPG and OGTT, including greater convenience (fasting not required), greater preanalytical stability, and less day-to-day perturbations during stress, changes in diet, or illness. However, these advantages may be offset by the lower sensitivity of A1C at the designated cut point, greater cost, limited availability of A1C testing in certain regions of the developing world, and the imperfect correlation between A1C and average glucose in certain individuals. The A1C test, with a diagnostic threshold of ≥6.5% (48 mmol/mol), diagnoses only 30% of the diabetes cases identified collectively using A1C, FPG, or 2-h PG, according to National Health and Nutrition Examination Survey (NHANES) data ( 22 ).

When using A1C to diagnose diabetes, it is important to recognize that A1C is an indirect measure of average blood glucose levels and to take other factors into consideration that may impact hemoglobin glycation independently of glycemia, such as hemodialysis, pregnancy, HIV treatment ( 23 , 24 ), age, race/ethnicity, pregnancy status, genetic background, and anemia/hemoglobinopathies. (See other conditions altering the relationship of a1c and glycemia below for more information.)

The epidemiologic studies that formed the basis for recommending A1C to diagnose diabetes included only adult populations ( 22 ). However, recent ADA clinical guidance concluded that A1C, FPG, or 2-h PG can be used to test for prediabetes or type 2 diabetes in children and adolescents (see screening and testing for prediabetes and type 2 diabetes in children and adolescents below for additional information) ( 25 ).

Race/Ethnicity/Hemoglobinopathies

Hemoglobin variants can interfere with the measurement of A1C, although most assays in use in the U.S. are unaffected by the most common variants. Marked discrepancies between measured A1C and plasma glucose levels should prompt consideration that the A1C assay may not be reliable for that individual. For patients with a hemoglobin variant but normal red blood cell turnover, such as those with the sickle cell trait, an A1C assay without interference from hemoglobin variants should be used. An updated list of A1C assays with interferences is available at www.ngsp.org/interf.asp .

African Americans heterozygous for the common hemoglobin variant HbS may have, for any given level of mean glycemia, lower A1C by about 0.3% compared with those without the trait ( 26 ). Another genetic variant, X-linked glucose-6-phosphate dehydrogenase G202A, carried by 11% of African Americans, was associated with a decrease in A1C of about 0.8% in homozygous men and 0.7% in homozygous women compared with those without the variant ( 27 ).

Even in the absence of hemoglobin variants, A1C levels may vary with race/ethnicity independently of glycemia ( 28 – 30 ). For example, African Americans may have higher A1C levels than non-Hispanic Whites with similar fasting and postglucose load glucose levels ( 31 ). Though conflicting data exists, African Americans may also have higher levels of fructosamine and glycated albumin and lower levels of 1,5-anhydroglucitol, suggesting that their glycemic burden (particularly postprandially) may be higher ( 32 , 33 ). Similarly, A1C levels may be higher for a given mean glucose concentration when measured with continuous glucose monitoring ( 34 ). Despite these and other reported differences, the association of A1C with risk for complications appears to be similar in African Americans and non-Hispanic Whites ( 35 , 36 ).

Other Conditions Altering the Relationship of A1C and Glycemia

In conditions associated with increased red blood cell turnover, such as sickle cell disease, pregnancy (second and third trimesters), glucose-6-phosphate dehydrogenase deficiency ( 37 , 38 ), hemodialysis, recent blood loss or transfusion, or erythropoietin therapy, only plasma blood glucose criteria should be used to diagnose diabetes ( 39 ). A1C is less reliable than blood glucose measurement in other conditions such as the postpartum state ( 40 – 42 ), HIV treated with certain protease inhibitors (PIs) and nucleoside reverse transcriptase inhibitors (NRTIs) ( 23 ), and iron-deficient anemia ( 43 ).

Confirming the Diagnosis

Unless there is a clear clinical diagnosis (e.g., patient in a hyperglycemic crisis or with classic symptoms of hyperglycemia and a random plasma glucose ≥200 mg/dL [11.1 mmol/L]), diagnosis requires two abnormal test results, either from the same sample ( 44 ) or in two separate test samples. If using two separate test samples, it is recommended that the second test, which may either be a repeat of the initial test or a different test, be performed without delay. For example, if the A1C is 7.0% (53 mmol/mol) and a repeat result is 6.8% (51 mmol/mol), the diagnosis of diabetes is confirmed. If two different tests (such as A1C and FPG) are both above the diagnostic threshold when analyzed from the same sample or in two different test samples, this also confirms the diagnosis. On the other hand, if a patient has discordant results from two different tests, then the test result that is above the diagnostic cut point should be repeated, with careful consideration of the possibility of A1C assay interference. The diagnosis is made on the basis of the confirmed test. For example, if a patient meets the diabetes criterion of the A1C (two results ≥6.5% [48 mmol/mol]) but not FPG (<126 mg/dL [7.0 mmol/L]), that person should nevertheless be considered to have diabetes.

Each of the tests has preanalytic and analytic variability, so it is possible that a test yielding an abnormal result (i.e., above the diagnostic threshold), when repeated, will produce a value below the diagnostic cut point. This scenario is likely for FPG and 2-h PG if the glucose samples remain at room temperature and are not centrifuged promptly. Because of the potential for preanalytic variability, it is critical that samples for plasma glucose be spun and separated immediately after they are drawn. If patients have test results near the margins of the diagnostic threshold, the health care professional should discuss signs and symptoms with the patient and repeat the test in 3 – 6 months.

In a patient with classic symptoms, measurement of plasma glucose is sufficient to diagnose diabetes (symptoms of hyperglycemia or hyperglycemic crisis plus a random plasma glucose ≥200 mg/dL [11.1 mmol/L]). In these cases, knowing the plasma glucose level is critical because, in addition to confirming that symptoms are due to diabetes, it will inform management decisions. Some providers may also want to know the A1C to determine the chronicity of the hyperglycemia. The criteria to diagnose diabetes are listed in Table 2.2 .

2.4 Screening for type 1 diabetes risk with a panel of islet autoantibodies is currently recommended in the setting of a research trial or can be offered as an option for first-degree family members of a proband with type 1 diabetes. B

2.5 Persistence of autoantibodies is a risk factor for clinical diabetes and may serve as an indication for intervention in the setting of a clinical trial. B

Immune-Mediated Diabetes

This form, previously called “insulin-dependent diabetes” or “juvenile-onset diabetes,” accounts for 5 – 10% of diabetes and is due to cellular-mediated autoimmune destruction of the pancreatic β-cells. Autoimmune markers include islet cell autoantibodies and autoantibodies to GAD (GAD65), insulin, the tyrosine phosphatases IA-2 and IA-2β, and zinc transporter 8 (ZnT8). Numerous clinical studies are being conducted to test various methods of preventing type 1 diabetes in those with evidence of islet autoimmunity ( www.clinicaltrials.gov and www.trialnet.org/our-research/prevention-studies ) ( 12 , 45 – 49 ). Stage 1 of type 1 diabetes is defined by the presence of two or more of these autoimmune markers. The disease has strong HLA associations, with linkage to the DQA and DQB genes. These HLA-DR/DQ alleles can be either predisposing or protective ( Table 2.1 ). There are important genetic considerations, as most of the mutations that cause diabetes are dominantly inherited. The importance of genetic testing is in the genetic counseling that follows. Some mutations are associated with other conditions, which then may prompt additional screenings.

The rate of β-cell destruction is quite variable, being rapid in some individuals (mainly infants and children) and slow in others (mainly adults) ( 50 ). Children and adolescents may present with DKA as the first manifestation of the disease. Others have modest fasting hyperglycemia that can rapidly change to severe hyperglycemia and/or DKA with infection or other stress. Adults may retain sufficient β-cell function to prevent DKA for many years; such individuals may have remission or decreased insulin needs for months or years and eventually become dependent on insulin for survival and are at risk for DKA ( 3 – 5 , 51 , 52 ). At this latter stage of the disease, there is little or no insulin secretion, as manifested by low or undetectable levels of plasma C-peptide. Immune-mediated diabetes is the most common form of diabetes in childhood and adolescence, but it can occur at any age, even in the 8th and 9th decades of life.

Autoimmune destruction of β-cells has multiple genetic predispositions and is also related to environmental factors that are still poorly defined. Although patients are not typically obese when they present with type 1 diabetes, obesity is increasingly common in the general population, and there is evidence that it may also be a risk factor for type 1 diabetes. As such, obesity should not preclude the diagnosis. People with type 1 diabetes are also prone to other autoimmune disorders such as Hashimoto thyroiditis, Graves disease, celiac disease, Addison disease, vitiligo, autoimmune hepatitis, myasthenia gravis, and pernicious anemia (see Section 4 “Comprehensive Medical Evaluation and Assessment of Comorbidities,” https://doi.org/10.2337/dc21-S004 ).

Idiopathic Type 1 Diabetes

Some forms of type 1 diabetes have no known etiologies. These patients have permanent insulinopenia and are prone to DKA but have no evidence of β-cell autoimmunity. However, only a minority of patients with type 1 diabetes fall into this category. Individuals with autoantibody-negative type 1 diabetes of African or Asian ancestry may suffer from episodic DKA and exhibit varying degrees of insulin deficiency between episodes (possibly ketosis-prone diabetes). This form of diabetes is strongly inherited and is not HLA associated. An absolute requirement for insulin replacement therapy in affected patients may be intermittent. Future research is needed to determine the cause of β-cell destruction in this rare clinical scenario.

Screening for Type 1 Diabetes Risk

The incidence and prevalence of type 1 diabetes is increasing ( 53 ). Patients with type 1 diabetes often present with acute symptoms of diabetes and markedly elevated blood glucose levels, and approximately one-third are diagnosed with life-threatening DKA ( 2 ). Multiple studies indicate that measuring islet autoantibodies in individuals genetically at risk for type 1 diabetes (e.g., relatives of those with type 1 diabetes or individuals from the general population with type 1 diabetes–associated genetic factors) identifies individuals who may develop type 1 diabetes ( 10 ). Such testing, coupled with education about diabetes symptoms and close follow-up, may enable earlier identification of type 1 diabetes onset. A study reported the risk of progression to type 1 diabetes from the time of seroconversion to autoantibody positivity in three pediatric cohorts from Finland, Germany, and the U.S. Of the 585 children who developed more than two autoantibodies, nearly 70% developed type 1 diabetes within 10 years and 84% within 15 years ( 45 ). These findings are highly significant because while the German group was recruited from offspring of parents with type 1 diabetes, the Finnish and American groups were recruited from the general population. Remarkably, the findings in all three groups were the same, suggesting that the same sequence of events led to clinical disease in both “sporadic” and familial cases of type 1 diabetes. Indeed, the risk of type 1 diabetes increases as the number of relevant autoantibodies detected increases ( 48 , 54 , 55 ). In The Environmental Determinants of Diabetes in the Young (TEDDY) study, type 1 diabetes developed in 21% of 363 subjects with at least one autoantibody at 3 years of age ( 56 ).

There is currently a lack of accepted and clinically validated screening programs outside of the research setting; thus, widespread clinical testing of asymptomatic low-risk individuals is not currently recommended due to lack of approved therapeutic interventions. However, one should consider referring relatives of those with type 1 diabetes for islet autoantibody testing for risk assessment in the setting of a clinical research study (see www.trialnet.org ). Individuals who test positive should be counseled about the risk of developing diabetes, diabetes symptoms, and DKA prevention. Numerous clinical studies are being conducted to test various methods of preventing and treating stage 2 type 1 diabetes in those with evidence of autoimmunity with promising results (see www.clinicaltrials.gov and www.trialnet.org ).

2.6 Screening for prediabetes and type 2 diabetes with an informal assessment of risk factors or validated tools should be considered in asymptomatic adults. B

2.7 Testing for prediabetes and/or type 2 diabetes in asymptomatic people should be considered in adults of any age with overweight or obesity (BMI ≥25 kg/m 2 or ≥23 kg/m 2 in Asian Americans) and who have one or more additional risk factors for diabetes ( Table 2.3 ). B

2.8 Testing for prediabetes and/or type 2 diabetes should be considered in women with overweight or obesity planning pregnancy and/or who have one or more additional risk factor for diabetes ( Table 2.3 ). C

2.9 For all people, testing should begin at age 45 years. B

2.10 If tests are normal, repeat testing carried out at a minimum of 3-year intervals is reasonable, sooner with symptoms. C

2.11 To test for prediabetes and type 2 diabetes, fasting plasma glucose, 2-h plasma glucose during 75-g oral glucose tolerance test, and A1C are equally appropriate ( Table 2.2 and Table 2.5 ). B

2.12 In patients with prediabetes and type 2 diabetes, identify and treat other cardiovascular disease risk factors. A

2.13 Risk-based screening for prediabetes and/or type 2 diabetes should be considered after the onset of puberty or after 10 years of age, whichever occurs earlier, in children and adolescents with overweight (BMI ≥85th percentile) or obesity (BMI ≥95th percentile) and who have one or more risk factor for diabetes. (See Table 2.4 for evidence grading of risk factors.) B

2.14 Patients with HIV should be screened for diabetes and prediabetes with a fasting glucose test before starting antiretroviral therapy, at the time of switching antiretroviral therapy, and 3−6 months after starting or switching antiretroviral therapy. If initial screening results are normal, fasting glucose should be checked annually. E

Criteria for testing for diabetes or prediabetes in asymptomatic adults

1. Testing should be considered in adults with overweight or obesity (BMI ≥25 kg/m or ≥23 kg/m in Asian Americans) who have one or more of the following risk factors:

• First-degree relative with diabetes

• High-risk race/ethnicity (e.g., African American, Latino, Native American, Asian American, Pacific Islander)

• History of CVD

• Hypertension (≥140/90 mmHg or on therapy for hypertension)

• HDL cholesterol level <35 mg/dL (0.90 mmol/L) and/or a triglyceride level >250 mg/dL (2.82 mmol/L)

• Women with polycystic ovary syndrome

• Physical inactivity

• Other clinical conditions associated with insulin resistance (e.g., severe obesity, acanthosis nigricans)

2. Patients with prediabetes (A1C ≥5.7% [39 mmol/mol], IGT, or IFG) should be tested yearly.

3. Women who were diagnosed with GDM should have lifelong testing at least every 3 years.

4. For all other patients, testing should begin at age 45 years.

5. If results are normal, testing should be repeated at a minimum of 3-year intervals, with consideration of more frequent testing depending on initial results and risk status.

6. HIV

1. Testing should be considered in adults with overweight or obesity (BMI ≥25 kg/m or ≥23 kg/m in Asian Americans) who have one or more of the following risk factors:

• First-degree relative with diabetes

• High-risk race/ethnicity (e.g., African American, Latino, Native American, Asian American, Pacific Islander)

• History of CVD

• Hypertension (≥140/90 mmHg or on therapy for hypertension)

• HDL cholesterol level <35 mg/dL (0.90 mmol/L) and/or a triglyceride level >250 mg/dL (2.82 mmol/L)

• Women with polycystic ovary syndrome

• Physical inactivity

• Other clinical conditions associated with insulin resistance (e.g., severe obesity, acanthosis nigricans)

2. Patients with prediabetes (A1C ≥5.7% [39 mmol/mol], IGT, or IFG) should be tested yearly.

3. Women who were diagnosed with GDM should have lifelong testing at least every 3 years.

4. For all other patients, testing should begin at age 45 years.

5. If results are normal, testing should be repeated at a minimum of 3-year intervals, with consideration of more frequent testing depending on initial results and risk status.

6. HIV

CVD, cardiovascular disease; GDM, gestational diabetes mellitus; IFG, impaired fasting glucose; IGT, impaired glucose tolerance.

Risk-based screening for type 2 diabetes or prediabetes in asymptomatic children and adolescents in a clinical setting ( 202 )

Testing should be considered in youth who have overweight (≥85th percentile) or obesity (≥95th percentile) and who have one or more additional risk factors based on the strength of their association with diabetes:

• Maternal history of diabetes or GDM during the child's gestation

• Family history of type 2 diabetes in first- or second-degree relative

• Race/ethnicity (Native American, African American, Latino, Asian American, Pacific Islander)

• Signs of insulin resistance or conditions associated with insulin resistance (acanthosis nigricans, hypertension, dyslipidemia, polycystic ovary syndrome, or small-for-gestational-age birth weight)

• Maternal history of diabetes or GDM during the child's gestation

• Family history of type 2 diabetes in first- or second-degree relative

• Race/ethnicity (Native American, African American, Latino, Asian American, Pacific Islander)

GDM, gestational diabetes mellitus.

After the onset of puberty or after 10 years of age, whichever occurs earlier. If tests are normal, repeat testing at a minimum of 3-year intervals (or more frequently if BMI is increasing or risk factor profile deteriorating) is recommended. Reports of type 2 diabetes before age 10 years exist, and this can be considered with numerous risk factors.

Prediabetes

“Prediabetes” is the term used for individuals whose glucose levels do not meet the criteria for diabetes but are too high to be considered normal ( 35 , 36 ). Patients with prediabetes are defined by the presence of IFG and/or IGT and/or A1C 5.7 – 6.4% (39 – 47 mmol/mol) ( Table 2.5 ). Prediabetes should not be viewed as a clinical entity in its own right but rather as an increased risk for diabetes and cardiovascular disease (CVD). Criteria for testing for diabetes or prediabetes in asymptomatic adults is outlined in Table 2.3 . Prediabetes is associated with obesity (especially abdominal or visceral obesity), dyslipidemia with high triglycerides and/or low HDL cholesterol, and hypertension.

Criteria defining prediabetes *

FPG 100 mg/dL (5.6 mmol/L) to 125 mg/dL (6.9 mmol/L) (IFG)

2-h PG during 75-g OGTT 140 mg/dL (7.8 mmol/L) to 199 mg/dL (11.0 mmol/L) (IGT)

A1C 5.7 6.4% (39 47 mmol/mol)

FPG 100 mg/dL (5.6 mmol/L) to 125 mg/dL (6.9 mmol/L) (IFG)

2-h PG during 75-g OGTT 140 mg/dL (7.8 mmol/L) to 199 mg/dL (11.0 mmol/L) (IGT)

A1C 5.7 6.4% (39 47 mmol/mol)

FPG, fasting plasma glucose; IFG, impaired fasting glucose; IGT, impaired glucose tolerance; OGTT, oral glucose tolerance test; 2-h PG, 2-h plasma glucose.

For all three tests, risk is continuous, extending below the lower limit of the range and becoming disproportionately greater at the higher end of the range.

IFG is defined as FPG levels from 100 to 125 mg/dL (from 5.6 to 6.9 mmol/L) ( 57 , 58 ) and IGT as 2-h PG during 75-g OGTT levels from 140 to 199 mg/dL (from 7.8 to 11.0 mmol/L) ( 59 ). It should be noted that the World Health Organization (WHO) and numerous other diabetes organizations define the IFG cutoff at 110 mg/dL (6.1 mmol/L).

As with the glucose measures, several prospective studies that used A1C to predict the progression to diabetes as defined by A1C criteria demonstrated a strong, continuous association between A1C and subsequent diabetes. In a systematic review of 44,203 individuals from 16 cohort studies with a follow-up interval averaging 5.6 years (range 2.8 – 12 years), those with A1C between 5.5% and 6.0% (between 37 and 42 mmol/mol) had a substantially increased risk of diabetes (5-year incidence from 9% to 25%). Those with an A1C range of 6.0–6.5% (42 – 48 mmol/mol) had a 5-year risk of developing diabetes between 25% and 50% and a relative risk 20 times higher compared with A1C of 5.0% (31 mmol/mol) ( 60 ). In a community-based study of African American and non-Hispanic White adults without diabetes, baseline A1C was a stronger predictor of subsequent diabetes and cardiovascular events than fasting glucose ( 61 ). Other analyses suggest that A1C of 5.7% (39 mmol/mol) or higher is associated with a diabetes risk similar to that of the high-risk participants in the Diabetes Prevention Program (DPP) ( 62 ), and A1C at baseline was a strong predictor of the development of glucose-defined diabetes during the DPP and its follow-up ( 63 ). Hence, it is reasonable to consider an A1C range of 5.7 – 6.4% (39 – 47 mmol/mol) as identifying individuals with prediabetes. Similar to those with IFG and/or IGT, individuals with A1C of 5.7 – 6.4% (39 – 47 mmol/mol) should be informed of their increased risk for diabetes and CVD and counseled about effective strategies to lower their risks (see Section 3 “Prevention or Delay of Type 2 Diabetes,” https://doi.org/10.2337/dc21-S003 ). Similar to glucose measurements, the continuum of risk is curvilinear, so as A1C rises, the diabetes risk rises disproportionately ( 60 ). Aggressive interventions and vigilant follow-up should be pursued for those considered at very high risk (e.g., those with A1C >6.0% [42 mmol/mol]).

Table 2.5 summarizes the categories of prediabetes and Table 2.3 the criteria for prediabetes testing. The ADA diabetes risk test is an additional option for assessment to determine the appropriateness of testing for diabetes or prediabetes in asymptomatic adults ( Fig. 2.1 ) ( diabetes.org/socrisktest ). For additional background regarding risk factors and screening for prediabetes, see screening and testing for prediabetes and type 2 diabetes in asymptomatic adults and also screening and testing for prediabetes and type 2 diabetes in children and adolescents below.

ADA risk test ( diabetes.org/socrisktest ).

Type 2 Diabetes

Type 2 diabetes, previously referred to as “noninsulin-dependent diabetes” or “adult-onset diabetes,” accounts for 90 – 95% of all diabetes. This form encompasses individuals who have relative (rather than absolute) insulin deficiency and have peripheral insulin resistance. At least initially, and often throughout their lifetime, these individuals may not need insulin treatment to survive.

There are various causes of type 2 diabetes. Although the specific etiologies are not known, autoimmune destruction of β-cells does not occur, and patients do not have any of the other known causes of diabetes. Most, but not all, patients with type 2 diabetes have overweight or obesity. Excess weight itself causes some degree of insulin resistance. Patients who do not have obesity or overweight by traditional weight criteria may have an increased percentage of body fat distributed predominantly in the abdominal region.

DKA seldom occurs spontaneously in type 2 diabetes; when seen, it usually arises in association with the stress of another illness such as infection, myocardial infarction, or with the use of certain drugs (e.g., corticosteroids, atypical antipsychotics, and sodium–glucose cotransporter 2 inhibitors) ( 64 , 65 ). Type 2 diabetes frequently goes undiagnosed for many years because hyperglycemia develops gradually and, at earlier stages, is often not severe enough for the patient to notice the classic diabetes symptoms caused by hyperglycemia. Nevertheless, even undiagnosed patients are at increased risk of developing macrovascular and microvascular complications.

Patients with type 2 diabetes may have insulin levels that appear normal or elevated, yet the failure to normalize blood glucose reflects a relative defect in glucose-stimulated insulin secretion. Thus, insulin secretion is defective in these patients and insufficient to compensate for insulin resistance. Insulin resistance may improve with weight reduction, exercise, and/or pharmacologic treatment of hyperglycemia but is seldom restored to normal. Recent interventions with intensive diet and exercise or surgical weight loss have led to diabetes remission ( 66 – 72 ) (see Section 8 “Obesity Management for the Treatment of Type 2 Diabetes,” https://doi.org/10.2337/dc21-S008 ).

The risk of developing type 2 diabetes increases with age, obesity, and lack of physical activity. It occurs more frequently in women with prior gestational diabetes mellitus (GDM), with hypertension or dyslipidemia, with polycystic ovary syndrome, and in certain racial/ethnic subgroups (African American, American Indian, Hispanic/Latino, and Asian American). It is often associated with a strong genetic predisposition or family history in first-degree relatives (more so than type 1 diabetes). However, the genetics of type 2 diabetes is poorly understood and under intense investigation in this era of precision medicine ( 13 ). In adults without traditional risk factors for type 2 diabetes and/or younger age, consider islet autoantibody testing (e.g., GAD65 autoantibodies) to exclude the diagnosis of type 1 diabetes.

Screening and Testing for Prediabetes and Type 2 Diabetes in Asymptomatic Adults

Screening for prediabetes and type 2 diabetes risk through an informal assessment of risk factors ( Table 2.3 ) or with an assessment tool, such as the ADA risk test ( Fig. 2.1 ) (online at diabetes.org/socrisktest ), is recommended to guide providers on whether performing a diagnostic test ( Table 2.2 ) is appropriate. Prediabetes and type 2 diabetes meet criteria for conditions in which early detection via screening is appropriate. Both conditions are common and impose significant clinical and public health burdens. There is often a long presymptomatic phase before the diagnosis of type 2 diabetes. Simple tests to detect preclinical disease are readily available. The duration of glycemic burden is a strong predictor of adverse outcomes. There are effective interventions that prevent progression from prediabetes to diabetes (see Section 3 “Prevention or Delay of Type 2 Diabetes,” https://doi.org/10.2337/dc21-S003 ) and reduce the risk of diabetes complications ( 73 ) (see Section 10 “Cardiovascular Disease and Risk Management,” https://doi.org/10.2337/dc21-S010 , and Section 11 “Microvascular Complications and Foot Care,” https://doi.org/10.2337/dc21-S011 ). In the most recent National Institutes of Health (NIH) Diabetes Prevention Program Outcomes Study (DPPOS) report, prevention of progression from prediabetes to diabetes ( 74 ) resulted in lower rates of developing retinopathy and nephropathy ( 75 ). Similar impact on diabetes complications was reported with screening, diagnosis, and comprehensive risk factor management in the U.K. Clinical Practice Research Datalink database ( 73 ). In that report, progression from prediabetes to diabetes augmented risk of complications.

Approximately one-quarter of people with diabetes in the U.S. and nearly half of Asian and Hispanic Americans with diabetes are undiagnosed ( 57 , 58 ). Although screening of asymptomatic individuals to identify those with prediabetes or diabetes might seem reasonable, rigorous clinical trials to prove the effectiveness of such screening have not been conducted and are unlikely to occur. Based on a population estimate, diabetes in women of childbearing age is underdiagnosed ( 76 ). Employing a probabilistic model, Peterson et al. ( 77 ) demonstrated cost and health benefits of preconception screening.

A large European randomized controlled trial compared the impact of screening for diabetes and intensive multifactorial intervention with that of screening and routine care ( 78 ). General practice patients between the ages of 40 and 69 years were screened for diabetes and randomly assigned by practice to intensive treatment of multiple risk factors or routine diabetes care. After 5.3 years of follow-up, CVD risk factors were modestly but significantly improved with intensive treatment compared with routine care, but the incidence of first CVD events or mortality was not significantly different between the groups ( 59 ). The excellent care provided to patients in the routine care group and the lack of an unscreened control arm limited the authors' ability to determine whether screening and early treatment improved outcomes compared with no screening and later treatment after clinical diagnoses. Computer simulation modeling studies suggest that major benefits are likely to accrue from the early diagnosis and treatment of hyperglycemia and cardiovascular risk factors in type 2 diabetes ( 79 ); moreover, screening, beginning at age 30 or 45 years and independent of risk factors, may be cost-effective (<$11,000 per quality-adjusted life year gained—2010 modeling data) ( 80 ). Cost-effectiveness of screening has been reinforced in cohort studies ( 81 , 82 ).

Additional considerations regarding testing for type 2 diabetes and prediabetes in asymptomatic patients include the following.

Age is a major risk factor for diabetes. Testing should begin at no later than age 45 years for all patients. Screening should be considered in adults of any age with overweight or obesity and one or more risk factors for diabetes.

BMI and Ethnicity

In general, BMI ≥25 kg/m 2 is a risk factor for diabetes. However, data suggest that the BMI cut point should be lower for the Asian American population ( 83 , 84 ). The BMI cut points fall consistently between 23 and 24 kg/m 2 (sensitivity of 80%) for nearly all Asian American subgroups (with levels slightly lower for Japanese Americans). This makes a rounded cut point of 23 kg/m 2 practical. An argument can be made to push the BMI cut point to lower than 23 kg/m 2 in favor of increased sensitivity; however, this would lead to an unacceptably low specificity (13.1%). Data from WHO also suggests that a BMI of ≥23 kg/m 2 should be used to define increased risk in Asian Americans ( 85 ). The finding that one-third to one-half of diabetes in Asian Americans is undiagnosed suggests that testing is not occurring at lower BMI thresholds ( 86 , 87 ).

Evidence also suggests that other populations may benefit from lower BMI cut points. For example, in a large multiethnic cohort study, for an equivalent incidence rate of diabetes, a BMI of 30 kg/m 2 in non-Hispanic Whites was equivalent to a BMI of 26 kg/m 2 in African Americans ( 88 ).

Medications

Certain medications, such as glucocorticoids, thiazide diuretics, some HIV medications ( 23 ), and atypical antipsychotics ( 66 ), are known to increase the risk of diabetes and should be considered when deciding whether to screen.

Individuals with HIV are at higher risk for developing prediabetes and diabetes on antiretroviral (ARV) therapies, so a screening protocol is recommended ( 89 ). The A1C test may underestimate glycemia in people with HIV; it is not recommended for diagnosis and may present challenges for monitoring ( 24 ). In those with prediabetes, weight loss through healthy nutrition and physical activity may reduce the progression toward diabetes. Among patients with HIV and diabetes, preventive health care using an approach used in patients without HIV is critical to reduce the risks of microvascular and macrovascular complications. Diabetes risk is increased with certain PIs and NRTIs. New-onset diabetes is estimated to occur in more than 5% of patients infected with HIV on PIs, whereas more than 15% may have prediabetes ( 90 ). PIs are associated with insulin resistance and may also lead to apoptosis of pancreatic β-cells. NRTIs also affect fat distribution (both lipohypertrophy and lipoatrophy), which is associated with insulin resistance. For patients with HIV and ARV-associated hyperglycemia, it may be appropriate to consider discontinuing the problematic ARV agents if safe and effective alternatives are available ( 91 ). Before making ARV substitutions, carefully consider the possible effect on HIV virological control and the potential adverse effects of new ARV agents. In some cases, antihyperglycemic agents may still be necessary.

Testing Interval

The appropriate interval between screening tests is not known ( 92 ). The rationale for the 3-year interval is that with this interval, the number of false-positive tests that require confirmatory testing will be reduced and individuals with false-negative tests will be retested before substantial time elapses and complications develop ( 92 ). In especially high-risk individuals, particularly with weight gain, shorter intervals between screening may be useful.

Community Screening

Ideally, testing should be carried out within a health care setting because of the need for follow-up and treatment. Community screening outside a health care setting is generally not recommended because people with positive tests may not seek, or have access to, appropriate follow-up testing and care. However, in specific situations where an adequate referral system is established beforehand for positive tests, community screening may be considered. Community testing may also be poorly targeted; i.e., it may fail to reach the groups most at risk and inappropriately test those at very low risk or even those who have already been diagnosed ( 93 ).

Screening in Dental Practices

Because periodontal disease is associated with diabetes, the utility of screening in a dental setting and referral to primary care as a means to improve the diagnosis of prediabetes and diabetes has been explored ( 94 – 96 ), with one study estimating that 30% of patients ≥30 years of age seen in general dental practices had dysglycemia ( 96 , 97 ). A similar study in 1,150 dental patients >40 years old in India reported 20.69% and 14.60% meeting criteria for prediabetes and diabetes using random blood glucose. Further research is needed to demonstrate the feasibility, effectiveness, and cost-effectiveness of screening in this setting.

Screening and Testing for Prediabetes and Type 2 Diabetes in Children and Adolescents

In the last decade, the incidence and prevalence of type 2 diabetes in children and adolescents has increased dramatically, especially in racial and ethnic minority populations ( 53 ). See Table 2.4 for recommendations on risk-based screening for type 2 diabetes or prediabetes in asymptomatic children and adolescents in a clinical setting ( 25 ). See Table 2.2 and Table 2.5 for the criteria for the diagnosis of diabetes and prediabetes, respectively, which apply to children, adolescents, and adults. See Section 13 “Children and Adolescents” ( https://doi.org/10.2337/dc21-S013 ) for additional information on type 2 diabetes in children and adolescents.

Some studies question the validity of A1C in the pediatric population, especially among certain ethnicities, and suggest OGTT or FPG as more suitable diagnostic tests ( 98 ). However, many of these studies do not recognize that diabetes diagnostic criteria are based on long-term health outcomes, and validations are not currently available in the pediatric population ( 99 ). The ADA acknowledges the limited data supporting A1C for diagnosing type 2 diabetes in children and adolescents. Although A1C is not recommended for diagnosis of diabetes in children with cystic fibrosis or symptoms suggestive of acute onset of type 1 diabetes and only A1C assays without interference are appropriate for children with hemoglobinopathies, the ADA continues to recommend A1C for diagnosis of type 2 diabetes in this cohort to decrease barriers to screening ( 100 , 101 ).

2.15 Annual screening for cystic fibrosis–related diabetes (CFRD) with an oral glucose tolerance test should begin by age 10 years in all patients with cystic fibrosis not previously diagnosed with CFRD. B

2.16 A1C is not recommended as a screening test for cystic fibrosis–related diabetes. B

2.17 Patients with cystic fibrosis–related diabetes should be treated with insulin to attain individualized glycemic goals. A

2.18 Beginning 5 years after the diagnosis of cystic fibrosis–related diabetes, annual monitoring for complications of diabetes is recommended. E

Cystic fibrosis–related diabetes (CFRD) is the most common comorbidity in people with cystic fibrosis, occurring in about 20% of adolescents and 40 – 50% of adults ( 102 ). Diabetes in this population, compared with individuals with type 1 or type 2 diabetes, is associated with worse nutritional status, more severe inflammatory lung disease, and greater mortality. Insulin insufficiency is the primary defect in CFRD. Genetically determined β-cell function and insulin resistance associated with infection and inflammation may also contribute to the development of CFRD. Milder abnormalities of glucose tolerance are even more common and occur at earlier ages than CFRD. Whether individuals with IGT should be treated with insulin replacement has not currently been determined. Although screening for diabetes before the age of 10 years can identify risk for progression to CFRD in those with abnormal glucose tolerance, no benefit has been established with respect to weight, height, BMI, or lung function. OGTT is the recommended screening test; however, recent publications suggest that an A1C cut point threshold of 5.5% (5.8% in a second study) would detect more than 90% of cases and reduce patient screening burden ( 103 , 104 ). Ongoing studies are underway to validate this approach. Regardless of age, weight loss or failure of expected weight gain is a risk for CFRD and should prompt screening ( 103 , 104 ). The Cystic Fibrosis Foundation Patient Registry ( 105 ) evaluated 3,553 cystic fibrosis patients and diagnosed 445 (13%) with CFRD. Early diagnosis and treatment of CFRD was associated with preservation of lung function. The European Cystic Fibrosis Society Patient Registry reported an increase in CFRD with age (increased 10% per decade), genotype, decreased lung function, and female sex ( 106 , 107 ). Continuous glucose monitoring or HOMA of β-cell function ( 108 ) may be more sensitive than OGTT to detect risk for progression to CFRD; however, evidence linking these results to long-term outcomes is lacking, and these tests are not recommended for screening outside of the research setting ( 109 ).

CFRD mortality has significantly decreased over time, and the gap in mortality between cystic fibrosis patients with and without diabetes has considerably narrowed ( 110 ). There are limited clinical trial data on therapy for CFRD. The largest study compared three regimens: premeal insulin aspart, repaglinide, or oral placebo in cystic fibrosis patients with diabetes or abnormal glucose tolerance. Participants all had weight loss in the year preceding treatment; however, in the insulin-treated group, this pattern was reversed, and patients gained 0.39 (± 0.21) BMI units (P = 0.02). The repaglinide-treated group had initial weight gain, but this was not sustained by 6 months. The placebo group continued to lose weight ( 110 ). Insulin remains the most widely used therapy for CFRD ( 111 ). The primary rationale for the use of insulin in patients with CFRD is to induce an anabolic state while promoting macronutrient retention and weight gain.

Additional resources for the clinical management of CFRD can be found in the position statement “Clinical Care Guidelines for Cystic Fibrosis–Related Diabetes: A Position Statement of the American Diabetes Association and a Clinical Practice Guideline of the Cystic Fibrosis Foundation, Endorsed by the Pediatric Endocrine Society” ( 112 ) and in the International Society for Pediatric and Adolescent Diabetes's 2014 clinical practice consensus guidelines ( 102 ).

2.19 Patients should be screened after organ transplantation for hyperglycemia, with a formal diagnosis of posttransplantation diabetes mellitus being best made once a patient is stable on an immunosuppressive regimen and in the absence of an acute infection. B

2.20 The oral glucose tolerance test is the preferred test to make a diagnosis of posttransplantation diabetes mellitus. B

2.21 Immunosuppressive regimens shown to provide the best outcomes for patient and graft survival should be used, irrespective of posttransplantation diabetes mellitus risk. E

Several terms are used in the literature to describe the presence of diabetes following organ transplantation ( 113 ). “New-onset diabetes after transplantation” (NODAT) is one such designation that describes individuals who develop new-onset diabetes following transplant. NODAT excludes patients with pretransplant diabetes that was undiagnosed as well as posttransplant hyperglycemia that resolves by the time of discharge ( 114 ). Another term, “posttransplantation diabetes mellitus” (PTDM) ( 114 , 115 ), describes the presence of diabetes in the posttransplant setting irrespective of the timing of diabetes onset.

Hyperglycemia is very common during the early posttransplant period, with ∼90% of kidney allograft recipients exhibiting hyperglycemia in the first few weeks following transplant ( 114 – 117 ). In most cases, such stress- or steroid-induced hyperglycemia resolves by the time of discharge ( 117 , 118 ). Although the use of immunosuppressive therapies is a major contributor to the development of PTDM, the risks of transplant rejection outweigh the risks of PTDM and the role of the diabetes care provider is to treat hyperglycemia appropriately regardless of the type of immunosuppression ( 114 ). Risk factors for PTDM include both general diabetes risks (such as age, family history of diabetes, etc.) as well as transplant-specific factors, such as use of immunosuppressant agents ( 119 ). Whereas posttransplantation hyperglycemia is an important risk factor for subsequent PTDM, a formal diagnosis of PTDM is optimally made once the patient is stable on maintenance immunosuppression and in the absence of acute infection ( 117 – 120 ). In a recent study of 152 heart transplant recipients, 38% had PTDM at 1 year. Risk factors for PTDM included elevated BMI, discharge from the hospital on insulin, and glucose values in the 24 h prior to hospital discharge ( 121 ). In an Iranian cohort, 19% had PTDM after heart and lung transplant ( 122 ). The OGTT is considered the gold standard test for the diagnosis of PTDM (1 year posttransplant) ( 114 , 115 , 123 , 124 ). However, screening patients using fasting glucose and/or A1C can identify high-risk patients requiring further assessment and may reduce the number of overall OGTTs required.

Few randomized controlled studies have reported on the short- and long-term use of antihyperglycemic agents in the setting of PTDM ( 119 , 125 , 126 ). Most studies have reported that transplant patients with hyperglycemia and PTDM after transplantation have higher rates of rejection, infection, and rehospitalization ( 117 , 119 , 127 ). Insulin therapy is the agent of choice for the management of hyperglycemia, PTDM, and preexisting diabetes and diabetes in the hospital setting. After discharge, patients with preexisting diabetes could go back on their pretransplant regimen if they were in good control before transplantation. Those with previously poor control or with persistent hyperglycemia should continue insulin with frequent home self-monitoring of blood glucose to determine when insulin dose reductions may be needed and when it may be appropriate to switch to noninsulin agents.

No studies to date have established which noninsulin agents are safest or most efficacious in PTDM. The choice of agent is usually made based on the side effect profile of the medication and possible interactions with the patient's immunosuppression regimen ( 119 ). Drug dose adjustments may be required because of decreases in the glomerular filtration rate, a relatively common complication in transplant patients. A small short-term pilot study reported that metformin was safe to use in renal transplant recipients ( 128 ), but its safety has not been determined in other types of organ transplant. Thiazolidinediones have been used successfully in patients with liver and kidney transplants, but side effects include fluid retention, heart failure, and osteopenia ( 129 , 130 ). Dipeptidyl peptidase 4 inhibitors do not interact with immunosuppressant drugs and have demonstrated safety in small clinical trials ( 131 , 132 ). Well-designed intervention trials examining the efficacy and safety of these and other antihyperglycemic agents in patients with PTDM are needed.

2.22 All children diagnosed with diabetes in the first 6 months of life should have immediate genetic testing for neonatal diabetes. A

2.23 Children and those diagnosed in early adulthood who have diabetes not characteristic of type 1 or type 2 diabetes that occurs in successive generations (suggestive of an autosomal dominant pattern of inheritance) should have genetic testing for maturity-onset diabetes of the young. A

2.24 In both instances, consultation with a center specializing in diabetes genetics is recommended to understand the significance of these mutations and how best to approach further evaluation, treatment, and genetic counseling. E

Monogenic defects that cause β-cell dysfunction, such as neonatal diabetes and MODY, represent a small fraction of patients with diabetes (<5%). Table 2.6 describes the most common causes of monogenic diabetes. For a comprehensive list of causes, see Genetic Diagnosis of Endocrine Disorders ( 133 ).

Most common causes of monogenic diabetes ( 133 )

Gene .	Inheritance .	Clinical features .
	AD	GCK-MODY: stable, nonprogressive elevated fasting blood glucose; typically does not require treatment; microvascular complications are rare; small rise in 2-h PG level on OGTT (<54 mg/dL [3 mmol/L])
	AD	HNF1A-MODY: progressive insulin secretory defect with presentation in adolescence or early adulthood; lowered renal threshold for glucosuria; large rise in 2-h PG level on OGTT (>90 mg/dL [5 mmol/L]); sensitive to sulfonylureas
	AD	HNF4A-MODY: progressive insulin secretory defect with presentation in adolescence or early adulthood; may have large birth weight and transient neonatal hypoglycemia; sensitive to sulfonylureas
	AD	HNF1B-MODY: developmental renal disease (typically cystic); genitourinary abnormalities; atrophy of the pancreas; hyperuricemia; gout
	AD	Permanent or transient: IUGR; possible developmental delay and seizures; responsive to sulfonylureas
	AD	Permanent: IUGR; insulin requiring
	AD	Permanent or transient: IUGR; rarely developmental delay; responsive to sulfonylureas
6q24 ( )	AD for paternal duplications	Transient: IUGR; macroglossia; umbilical hernia; mechanisms include UPD6, paternal duplication or maternal methylation defect; may be treatable with medications other than insulin
	AD	Permanent: pancreatic hypoplasia; cardiac malformations; pancreatic exocrine insufficiency; insulin requiring
	AR	Permanent: Wolcott-Rallison syndrome: epiphyseal dysplasia; pancreatic exocrine insufficiency; insulin requiring
	AD	Permanent diabetes: can be associated with fluctuating liver function ( )
	X-linked	Permanent: immunodysregulation, polyendocrinopathy; enteropathy X-linked (IPEX) syndrome: autoimmune diabetes, autoimmune thyroid disease, exfoliative dermatitis; insulin requiring

Gene .	Inheritance .	Clinical features .
	AD	GCK-MODY: stable, nonprogressive elevated fasting blood glucose; typically does not require treatment; microvascular complications are rare; small rise in 2-h PG level on OGTT (<54 mg/dL [3 mmol/L])
	AD	HNF1A-MODY: progressive insulin secretory defect with presentation in adolescence or early adulthood; lowered renal threshold for glucosuria; large rise in 2-h PG level on OGTT (>90 mg/dL [5 mmol/L]); sensitive to sulfonylureas
	AD	HNF4A-MODY: progressive insulin secretory defect with presentation in adolescence or early adulthood; may have large birth weight and transient neonatal hypoglycemia; sensitive to sulfonylureas
	AD	HNF1B-MODY: developmental renal disease (typically cystic); genitourinary abnormalities; atrophy of the pancreas; hyperuricemia; gout
	AD	Permanent or transient: IUGR; possible developmental delay and seizures; responsive to sulfonylureas
	AD	Permanent: IUGR; insulin requiring
	AD	Permanent or transient: IUGR; rarely developmental delay; responsive to sulfonylureas
6q24 ( )	AD for paternal duplications	Transient: IUGR; macroglossia; umbilical hernia; mechanisms include UPD6, paternal duplication or maternal methylation defect; may be treatable with medications other than insulin
	AD	Permanent: pancreatic hypoplasia; cardiac malformations; pancreatic exocrine insufficiency; insulin requiring
	AR	Permanent: Wolcott-Rallison syndrome: epiphyseal dysplasia; pancreatic exocrine insufficiency; insulin requiring
	AD	Permanent diabetes: can be associated with fluctuating liver function ( )
	X-linked	Permanent: immunodysregulation, polyendocrinopathy; enteropathy X-linked (IPEX) syndrome: autoimmune diabetes, autoimmune thyroid disease, exfoliative dermatitis; insulin requiring

AD, autosomal dominant; AR, autosomal recessive; IUGR, intrauterine growth restriction; OGTT, oral glucose tolerance test; UPD6, uniparental disomy of chromosome 6; 2-h PG, 2-h plasma glucose.

Neonatal Diabetes

Diabetes occurring under 6 months of age is termed “neonatal” or “congenital” diabetes, and about 80 – 85% of cases can be found to have an underlying monogenic cause ( 134 – 137 ). Neonatal diabetes occurs much less often after 6 months of age, whereas autoimmune type 1 diabetes rarely occurs before 6 months of age. Neonatal diabetes can either be transient or permanent. Transient diabetes is most often due to overexpression of genes on chromosome 6q24, is recurrent in about half of cases, and may be treatable with medications other than insulin. Permanent neonatal diabetes is most commonly due to autosomal dominant mutations in the genes encoding the Kir6.2 subunit ( KCNJ11 ) and SUR1 subunit ( ABCC8 ) of the β-cell K ATP channel. A recent report details a de novo mutation in EIF2B1 affecting eIF2 signaling associated with permanent neonatal diabetes and hepatic dysfunction, similar to Wolcott-Rallison syndrome but with few severe comorbidities ( 138 ). Correct diagnosis has critical implications because most patients with K ATP -related neonatal diabetes will exhibit improved glycemic control when treated with high-dose oral sulfonylureas instead of insulin. Insulin gene ( INS ) mutations are the second most common cause of permanent neonatal diabetes, and, while intensive insulin management is currently the preferred treatment strategy, there are important genetic counseling considerations, as most of the mutations that cause diabetes are dominantly inherited.

Maturity-Onset Diabetes of the Young

MODY is frequently characterized by onset of hyperglycemia at an early age (classically before age 25 years, although diagnosis may occur at older ages). MODY is characterized by impaired insulin secretion with minimal or no defects in insulin action (in the absence of coexistent obesity). It is inherited in an autosomal dominant pattern with abnormalities in at least 13 genes on different chromosomes identified to date. The most commonly reported forms are GCK-MODY (MODY2), HNF1A-MODY (MODY3), and HNF4A-MODY (MODY1).

For individuals with MODY, the treatment implications are considerable and warrant genetic testing ( 139 , 140 ). Clinically, patients with GCK-MODY exhibit mild, stable fasting hyperglycemia and do not require antihyperglycemic therapy except sometimes during pregnancy. Patients with HNF1A- or HNF4A-MODY usually respond well to low doses of sulfonylureas, which are considered first-line therapy. Mutations or deletions in HNF1B are associated with renal cysts and uterine malformations (renal cysts and diabetes [RCAD] syndrome). Other extremely rare forms of MODY have been reported to involve other transcription factor genes including PDX1 ( IPF1 ) and NEUROD1 .

Diagnosis of Monogenic Diabetes

A diagnosis of one of the three most common forms of MODY, including GCK-MODY, HNF1A-MODY, and HNF4A-MODY, allows for more cost-effective therapy (no therapy for GCK-MODY; sulfonylureas as first-line therapy for HNF1A-MODY and HNF4A-MODY). Additionally, diagnosis can lead to identification of other affected family members. Genetic screening is increasingly available and cost-effective ( 138 , 140 ).

A diagnosis of MODY should be considered in individuals who have atypical diabetes and multiple family members with diabetes not characteristic of type 1 or type 2 diabetes, although admittedly “atypical diabetes” is becoming increasingly difficult to precisely define in the absence of a definitive set of tests for either type of diabetes ( 135 – 137 , 139 – 145 ). In most cases, the presence of autoantibodies for type 1 diabetes precludes further testing for monogenic diabetes, but the presence of autoantibodies in patients with monogenic diabetes has been reported ( 146 ). Individuals in whom monogenic diabetes is suspected should be referred to a specialist for further evaluation if available, and consultation is available from several centers. Readily available commercial genetic testing following the criteria listed below now enables a cost-effective ( 147 ), often cost-saving, genetic diagnosis that is increasingly supported by health insurance. A biomarker screening pathway such as the combination of urinary C-peptide/creatinine ratio and antibody screening may aid in determining who should get genetic testing for MODY ( 148 ). It is critical to correctly diagnose one of the monogenic forms of diabetes because these patients may be incorrectly diagnosed with type 1 or type 2 diabetes, leading to suboptimal, even potentially harmful, treatment regimens and delays in diagnosing other family members ( 149 ). The correct diagnosis is especially critical for those with GCK-MODY mutations where multiple studies have shown that no complications ensue in the absence of glucose-lowering therapy ( 150 ). Genetic counseling is recommended to ensure that affected individuals understand the patterns of inheritance and the importance of a correct diagnosis.

The diagnosis of monogenic diabetes should be considered in children and adults diagnosed with diabetes in early adulthood with the following findings:

Diabetes diagnosed within the first 6 months of life (with occasional cases presenting later, mostly INS and ABCC8 mutations) ( 134 , 151 )

Diabetes without typical features of type 1 or type 2 diabetes (negative diabetes-associated autoantibodies, nonobese, lacking other metabolic features, especially with strong family history of diabetes)

Stable, mild fasting hyperglycemia (100 – 150 mg/dL [5.5 – 8.5 mmol/L]), stable A1C between 5.6% and 7.6% (between 38 and 60 mmol/mol), especially if nonobese

Pancreatic diabetes includes both structural and functional loss of glucose-normalizing insulin secretion in the context of exocrine pancreatic dysfunction and is commonly misdiagnosed as type 2 diabetes. Hyperglycemia due to general pancreatic dysfunction has been called “type 3c diabetes” and, more recently, diabetes in the context of disease of the exocrine pancreas has been termed pancreoprivic diabetes ( 1 ). The diverse set of etiologies includes pancreatitis (acute and chronic), trauma or pancreatectomy, neoplasia, cystic fibrosis (addressed elsewhere in this chapter), hemochromatosis, fibrocalculous pancreatopathy, rare genetic disorders ( 152 ), and idiopathic forms ( 1 ), which is the preferred terminology. A distinguishing feature is concurrent pancreatic exocrine insufficiency (according to the monoclonal fecal elastase 1 test or direct function tests), pathological pancreatic imaging (endoscopic ultrasound, MRI, computed tomography), and absence of type 1 diabetes–associated autoimmunity ( 153 – 157 ). There is loss of both insulin and glucagon secretion and often higher-than-expected insulin requirements. Risk for microvascular complications is similar to other forms of diabetes. In the context of pancreatectomy, islet autotransplantation can be done to retain insulin secretion ( 158 , 159 ). In some cases, autotransplant can lead to insulin independence. In others, it may decrease insulin requirements ( 160 ).

2.25 Test for undiagnosed prediabetes and diabetes at the first prenatal visit in those with risk factors using standard diagnostic criteria. B

2.26 Test for gestational diabetes mellitus at 24 – 28 weeks of gestation in pregnant women not previously found to have diabetes. A

2.27 Test women with gestational diabetes mellitus for prediabetes or diabetes at 4 – 12 weeks postpartum, using the 75-g oral glucose tolerance test and clinically appropriate nonpregnancy diagnostic criteria. B

2.28 Women with a history of gestational diabetes mellitus should have lifelong screening for the development of diabetes or prediabetes at least every 3 years. B

2.29 Women with a history of gestational diabetes mellitus found to have prediabetes should receive intensive lifestyle interventions and/or metformin to prevent diabetes. A

For many years, GDM was defined as any degree of glucose intolerance that was first recognized during pregnancy ( 60 ), regardless of the degree of hyperglycemia. This definition facilitated a uniform strategy for detection and classification of GDM, but this definition has serious limitations ( 161 ). First, the best available evidence reveals that many, perhaps most, cases of GDM represent preexisting hyperglycemia that is detected by routine screening in pregnancy, as routine screening is not widely performed in nonpregnant women of reproductive age. It is the severity of hyperglycemia that is clinically important with regard to both short- and long-term maternal and fetal risks. Universal preconception and/or first trimester screening is hampered by lack of data and consensus regarding appropriate diagnostic thresholds and outcomes and cost-effectiveness ( 162 , 163 ). A compelling argument for further work in this area is the fact that hyperglycemia that would be diagnostic of diabetes outside of pregnancy and is present at the time of conception is associated with an increased risk of congenital malformations that is not seen with lower glucose levels ( 164 , 165 ).

The ongoing epidemic of obesity and diabetes has led to more type 2 diabetes in women of reproductive age, with an increase in the number of pregnant women with undiagnosed type 2 diabetes in early pregnancy ( 166 – 169 ). Because of the number of pregnant women with undiagnosed type 2 diabetes, it is reasonable to test women with risk factors for type 2 diabetes ( 170 ) ( Table 2.3 ) at their initial prenatal visit, using standard diagnostic criteria ( Table 2.2 ). Women found to have diabetes by the standard diagnostic criteria used outside of pregnancy should be classified as having diabetes complicating pregnancy (most often type 2 diabetes, rarely type 1 diabetes or monogenic diabetes) and managed accordingly. Women who meet the lower glycemic criteria for GDM should be diagnosed with that condition and managed accordingly. Other women should be rescreened for GDM between 24 and 28 weeks of gestation (see Section 14 “Management of Diabetes in Pregnancy,” https://doi.org/10.2337/dc21-S014 ). The International Association of the Diabetes and Pregnancy Study Groups (IADPSG) GDM diagnostic criteria for the 75-g OGTT as well as the GDM screening and diagnostic criteria used in the two-step approach were not derived from data in the first half of pregnancy, so the diagnosis of GDM in early pregnancy by either FPG or OGTT values is not evidence based ( 171 ) and further work is needed.

GDM is often indicative of underlying β-cell dysfunction ( 172 ), which confers marked increased risk for later development of diabetes, generally but not always type 2 diabetes, in the mother after delivery ( 173 , 174 ). As effective prevention interventions are available ( 175 , 176 ), women diagnosed with GDM should receive lifelong screening for prediabetes to allow interventions to reduce diabetes risk and for type 2 diabetes to allow treatment at the earliest possible time ( 177 ).

GDM carries risks for the mother, fetus, and neonate. The Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study ( 178 ), a large-scale multinational cohort study completed by more than 23,000 pregnant women, demonstrated that risk of adverse maternal, fetal, and neonatal outcomes continuously increased as a function of maternal glycemia at 24 – 28 weeks of gestation, even within ranges previously considered normal for pregnancy. For most complications, there was no threshold for risk. These results have led to careful reconsideration of the diagnostic criteria for GDM.

GDM diagnosis ( Table 2.7 ) can be accomplished with either of two strategies:

The “one-step” 75-g OGTT derived from the IADPSG criteria, or

The older “two-step” approach with a 50-g (nonfasting) screen followed by a 100-g OGTT for those who screen positive, based on the work of Carpenter and Coustan's interpretation of the older OʼSullivan ( 179 ) criteria.

Screening for and diagnosis of GDM

Perform a 75-g OGTT, with plasma glucose measurement when patient is fasting and at 1 and 2 h, at 24 28 weeks of gestation in women not previously diagnosed with diabetes.

The OGTT should be performed in the morning after an overnight fast of at least 8 h.

The diagnosis of GDM is made when any of the following plasma glucose values are met or exceeded:

• Fasting: 92 mg/dL (5.1 mmol/L)

• 1 h: 180 mg/dL (10.0 mmol/L)

• 2 h: 153 mg/dL (8.5 mmol/L)

Perform a 50-g GLT (nonfasting), with plasma glucose measurement at 1 h, at 24–28 weeks of gestation in women not previously diagnosed with diabetes.

If the plasma glucose level measured 1 h after the load is ≥130, 135, or 140 mg/dL (7.2, 7.5, or 7.8 mmol/L, respectively), proceed to a 100-g OGTT.

The 100-g OGTT should be performed when the patient is fasting.

The diagnosis of GDM is made when at least two of the following four plasma glucose levels (measured fasting and at 1, 2, and 3 h during OGTT) are met or exceeded (Carpenter-Coustan criteria [ ]):

• Fasting: 95 mg/dL (5.3 mmol/L)

• 1 h: 180 mg/dL (10.0 mmol/L)

• 2 h: 155 mg/dL (8.6 mmol/L)

• 3 h: 140 mg/dL (7.8 mmol/L)

Perform a 75-g OGTT, with plasma glucose measurement when patient is fasting and at 1 and 2 h, at 24 28 weeks of gestation in women not previously diagnosed with diabetes.

The OGTT should be performed in the morning after an overnight fast of at least 8 h.

The diagnosis of GDM is made when any of the following plasma glucose values are met or exceeded:

• Fasting: 92 mg/dL (5.1 mmol/L)

• 1 h: 180 mg/dL (10.0 mmol/L)

• 2 h: 153 mg/dL (8.5 mmol/L)

Perform a 50-g GLT (nonfasting), with plasma glucose measurement at 1 h, at 24–28 weeks of gestation in women not previously diagnosed with diabetes.

If the plasma glucose level measured 1 h after the load is ≥130, 135, or 140 mg/dL (7.2, 7.5, or 7.8 mmol/L, respectively), proceed to a 100-g OGTT.

The 100-g OGTT should be performed when the patient is fasting.

The diagnosis of GDM is made when at least two of the following four plasma glucose levels (measured fasting and at 1, 2, and 3 h during OGTT) are met or exceeded (Carpenter-Coustan criteria [ ]):

• Fasting: 95 mg/dL (5.3 mmol/L)

• 1 h: 180 mg/dL (10.0 mmol/L)

• 2 h: 155 mg/dL (8.6 mmol/L)

• 3 h: 140 mg/dL (7.8 mmol/L)

GDM, gestational diabetes mellitus; GLT, glucose load test; OGTT, oral glucose tolerance test.

American College of Obstetricians and Gynecologists notes that one elevated value can be used for diagnosis ( 189 ).

Different diagnostic criteria will identify different degrees of maternal hyperglycemia and maternal/fetal risk, leading some experts to debate, and disagree on, optimal strategies for the diagnosis of GDM.

One-Step Strategy

The IADPSG defined diagnostic cut points for GDM as the average fasting, 1-h, and 2-h PG values during a 75-g OGTT in women at 24 – 28 weeks of gestation who participated in the HAPO study at which odds for adverse outcomes reached 1.75 times the estimated odds of these outcomes at the mean fasting, 1-h, and 2-h PG levels of the study population. This one-step strategy was anticipated to significantly increase the incidence of GDM (from 5 – 6% to 15–20%), primarily because only one abnormal value, not two, became sufficient to make the diagnosis ( 180 ). Many regional studies have investigated the impact of adopting the IADPSG criteria on prevalence and have seen a roughly one- to threefold increase ( 181 ). The anticipated increase in the incidence of GDM could have a substantial impact on costs and medical infrastructure needs and has the potential to “medicalize” pregnancies previously categorized as normal. A recent follow-up study of women participating in a blinded study of pregnancy OGTTs found that 11 years after their pregnancies, women who would have been diagnosed with GDM by the one-step approach, as compared with those without, were at 3.4-fold higher risk of developing prediabetes and type 2 diabetes and had children with a higher risk of obesity and increased body fat, suggesting that the larger group of women identified by the one-step approach would benefit from increased screening for diabetes and prediabetes that would accompany a history of GDM ( 182 , 183 ). The ADA recommends the IADPSG diagnostic criteria with the intent of optimizing gestational outcomes because these criteria are the only ones based on pregnancy outcomes rather than end points such as prediction of subsequent maternal diabetes.

The expected benefits of using IADPSG to the offspring are inferred from intervention trials that focused on women with lower levels of hyperglycemia than identified using older GDM diagnostic criteria. Those trials found modest benefits including reduced rates of large-for-gestational-age births and preeclampsia ( 184 , 185 ). It is important to note that 80 – 90% of women being treated for mild GDM in these two randomized controlled trials could be managed with lifestyle therapy alone. The OGTT glucose cutoffs in these two trials overlapped with the thresholds recommended by the IADPSG, and in one trial ( 185 ), the 2-h PG threshold (140 mg/dL [7.8 mmol/L]) was lower than the cutoff recommended by the IADPSG (153 mg/dL [8.5 mmol/L]). No randomized controlled trials of treating versus not treating GDM diagnosed by the IADPSG criteria but not the Carpenter-Coustan criteria have been published to date. Data are also lacking on how the treatment of lower levels of hyperglycemia affects a mother's future risk for the development of type 2 diabetes and her offspring's risk for obesity, diabetes, and other metabolic disorders. Additional well-designed clinical studies are needed to determine the optimal intensity of monitoring and treatment of women with GDM diagnosed by the one-step strategy ( 186 , 187 ).

Two-Step Strategy

In 2013, the NIH convened a consensus development conference to consider diagnostic criteria for diagnosing GDM ( 188 ). The 15-member panel had representatives from obstetrics and gynecology, maternal-fetal medicine, pediatrics, diabetes research, biostatistics, and other related fields. The panel recommended a two-step approach to screening that used a 1-h 50-g glucose load test (GLT) followed by a 3-h 100-g OGTT for those who screened positive. The American College of Obstetricians and Gynecologists (ACOG) recommends any of the commonly used thresholds of 130, 135, or 140 mg/dL for the 1-h 50-g GLT ( 189 ). A systematic review for the U.S. Preventive Services Task Force compared GLT cutoffs of 130 mg/dL (7.2 mmol/L) and 140 mg/dL (7.8 mmol/L) ( 190 ). The higher cutoff yielded sensitivity of 70–88% and specificity of 69 – 89%, while the lower cutoff was 88 – 99% sensitive and 66 – 77% specific. Data regarding a cutoff of 135 mg/dL are limited. As for other screening tests, choice of a cutoff is based upon the trade-off between sensitivity and specificity. The use of A1C at 24–28 weeks of gestation as a screening test for GDM does not function as well as the GLT ( 191 ).

Key factors cited by the NIH panel in their decision-making process were the lack of clinical trial data demonstrating the benefits of the one-step strategy and the potential negative consequences of identifying a large group of women with GDM, including medicalization of pregnancy with increased health care utilization and costs. Moreover, screening with a 50-g GLT does not require fasting and is therefore easier to accomplish for many women. Treatment of higher-threshold maternal hyperglycemia, as identified by the two-step approach, reduces rates of neonatal macrosomia, large-for-gestational-age births ( 192 ), and shoulder dystocia, without increasing small-for-gestational-age births. ACOG currently supports the two-step approach but notes that one elevated value, as opposed to two, may be used for the diagnosis of GDM ( 189 ). If this approach is implemented, the incidence of GDM by the two-step strategy will likely increase markedly. ACOG recommends either of two sets of diagnostic thresholds for the 3-h 100-g OGTT—Carpenter-Coustan or National Diabetes Data Group ( 193 , 194 ). Each is based on different mathematical conversions of the original recommended thresholds by O'Sullivan ( 179 ), which used whole blood and nonenzymatic methods for glucose determination. A secondary analysis of data from a randomized clinical trial of identification and treatment of mild GDM ( 195 ) demonstrated that treatment was similarly beneficial in patients meeting only the lower thresholds per Carpenter-Coustan ( 193 ) and in those meeting only the higher thresholds per National Diabetes Data Group ( 194 ). If the two-step approach is used, it would appear advantageous to use the Carpenter-Coustan lower diagnostic thresholds as shown in step 2 in Table 2.7 .

Future Considerations

The conflicting recommendations from expert groups underscore the fact that there are data to support each strategy. A cost-benefit estimation comparing the two strategies concluded that the one-step approach is cost-effective only if patients with GDM receive postdelivery counseling and care to prevent type 2 diabetes ( 196 ). The decision of which strategy to implement must therefore be made based on the relative values placed on factors that have yet to be measured (e.g., willingness to change practice based on correlation studies rather than intervention trial results, available infrastructure, and importance of cost considerations).

As the IADPSG criteria (“one-step strategy”) have been adopted internationally, further evidence has emerged to support improved pregnancy outcomes with cost savings ( 197 ), and IADPSG may be the preferred approach. Data comparing population-wide outcomes with one-step versus two-step approaches have been inconsistent to date ( 198 , 199 ). In addition, pregnancies complicated by GDM per the IADPSG criteria, but not recognized as such, have outcomes comparable to pregnancies with diagnosed GDM by the more stringent two-step criteria ( 200 , 201 ). There remains strong consensus that establishing a uniform approach to diagnosing GDM will benefit patients, caregivers, and policy makers. Longer-term outcome studies are currently underway.

Suggested citation: American Diabetes Association. 2. Classification and diagnosis of diabetes: Standards of Medical Care in Diabetes—2021 . Diabetes Care 2021;44(Suppl. 1):S15−S33

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Open Access

Peer-reviewed

Research Article

Perception and coping mechanisms of patients with diabetes mellitus during the COVID-19 pandemic in Ibadan, Nigeria

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Software, Validation, Writing – original draft, Writing – review & editing

Affiliation Department of Sociology, University of Wroclaw, Wroclaw, Poland

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Demography and Population Studies, University of Witwatersrand, Johannesburg, South Africa, Department of Public Health, School of Business and Health Studies, York St John University, London, United Kingdom

Roles Writing – original draft, Writing – review & editing

Affiliation Department of Family and Community Health, Fred N. Binka School of Public Health, University of Health and Allied Sciences, Hohoe, Ghana

Affiliation Department of Internal Medicine, College of Medicine, University of Ibadan & University College Hospital, Ibadan, Nigeria

Olajumoke Ololade Tunji-Adepoju,
Obasanjo Afolabi Bolarinwa,
Richard Gyan Aboagye,
Williams O. Balogun

Published: August 27, 2024
https://doi.org/10.1371/journal.pone.0309451
Peer Review
Reader Comments

The 2019 coronavirus disease (COVID-19) ushered in a period of fear and uncertainty, resulting in structural instability across the globe. Vulnerable individuals, such as patients with diabetes mellitus, are predispose to have adverse effects and complications of COVID-19 when infected. We explored the perception of diabetes mellitus patients during the COVID-19 pandemic and their coping mechanisms at the University College Hospital, Ibadan.

We employed an exploratory qualitative study design to explore diabetes mellitus patients’ perceptions and coping mechanisms during the COVID-19 pandemic. A purposive sampling technique was used to recruit 32 participants (2 health professionals and 30 diabetes mellitus patients). In-depth interviews were used to collect the data from the participants. All the recorded audio data were transcribed verbatim and exported to NVivo software for thematic data analyses.

Most diabetes mellitus patients were not fearful of the pandemic but were optimistic that it would not affect their health. Mechanisms such as the usage of herbal medicines and adherence to COVID-19 precautionary measures were noticed among patients. The study also revealed that the hospital’s coping mechanism during the COVID-19 pandemic include prolonged appointments, limiting the number of patients attended per clinic day, and the provision of telehealth service. Patients in our study utilised negative coping mechanisms such as reduced drug dosages, subscriptions to cheaper drug brands, and reliance on religious institutions rather than a clinic for health instructions.

Conclusions

The study has shown that diabetes mellitus patients were not fearful of the COVID-19 pandemic. The utilisation of telehealth, encouragement of daily monitoring of sugar levels, provision of avenues for a medication review, and adherence to the safety protocols were coping mechanisms employed by the health system and diabetes mellitus patients. We recommend that the government and other healthcare stakeholders reinforce the resilience of diabetes mellitus patients by alleviating their health burdens during the pandemic. This could be done by subsidizing the prices of drugs, tests, and consultation fees for patients with diabetes mellitus. Also, more efforts should be made to elevate the health system through the reduction in waiting and appointment times in the diabetes clinic and employing more health personnel in the clinic.

Citation: Tunji-Adepoju OO, Afolabi Bolarinwa O, Aboagye RG, Balogun WO (2024) Perception and coping mechanisms of patients with diabetes mellitus during the COVID-19 pandemic in Ibadan, Nigeria. PLoS ONE 19(8): e0309451. https://doi.org/10.1371/journal.pone.0309451

Editor: Sylla Thiam, Sunu Sante Consulting, SENEGAL

Received: June 26, 2023; Accepted: August 12, 2024; Published: August 27, 2024

Copyright: © 2024 Tunji-Adepoju et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data utilised in this research contain potentially identifying or sensitive patient information; data are owned by the Institute for Advanced Medical Research and Training (IAMRAT). Please get in touch with IAMRAT via [email protected] or the first author for data request and access.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: COVID-19, Coronavirus Disease 2019; IDI, In-depth Interview; KII, Key Informant Interview; NCD, Non-Communicable Diseases; NCDC, Nigeria Centre for Disease Control and Prevention; WHO, World Health Organization

Diabetes Mellitus has been an important global health concern even prior to the outbreak of the 2019 coronavirus disease (COVID-19). Diabetes mellitus is a chronic health condition characterized by high blood glucose due to either the inability of the pancreas to produce adequate insulin or the body’s resistance to available insulin [ 1 ]. Poorly managed diabetes mellitus can result in long-term complications such as amputation, cardiovascular disease, vision impairment, and renal disease [ 1 ]. The prevalence of diabetes mellitus is increasing across the globe. Between 1980 and 2014, the number of patients with diabetes mellitus increased from 108 million to 422 million [ 2 ] and over 500 million in 2020 [ 3 , 4 ]. Diabetes mellitus is projected to be the seventh leading cause of death worldwide by 2030 [ 2 ]. The burden of diabetes is greatly increasing in sub-Saharan Africa, and Nigeria has the largest share of this burden [ 5 , 6 ]. Evidence suggests that an estimated 11 million Nigerians have diabetes [ 7 ]. This implies that more than five percent of the Nigerian population is living with the disease, and it is a major cause of death among many Nigerians below 70 years old [ 8 ].

Research has shown that the presence of excess blood glucose, also known as hyperglycemia in diabetes patients, makes them susceptible to COVID-19 [ 9 , 10 ]. In the same vein, a study reported that patients with diabetes are two times more likely to develop severe conditions or die from COVID-19, while people living with uncontrolled diabetes are about 13 times more likely to die from the virus [ 9 ]. This has instilled fear in many patients with diabetes in Nigeria [ 10 ]. Hence, the fact that patients with diabetes need extra health care and attention during the pandemic remains undisputable [ 11 ]. Measures to prevent and control Non-Communicable Diseases (NCDs), such as diabetes, in developing countries, including Nigeria, have not been effectively implemented. The COVID-19 pandemic worsened the accumulated effects of Nigeria’s failure to improve the healthcare structure and system, particularly the care of people with NCDs. The outbreak of COVID-19 in Nigeria on the 27th of February 2020 [ 12 ] also caused dysfunctionality and complications in the Nigerian social structures, requiring sporadic responses.

Predictably, the response to COVID-19 in Nigeria infringed on treating other diseases, including diabetes mellitus [ 13 ]. For instance, many public hospitals were converted to COVID-19 treatment centers resulting in restricted access of other patients to medical care [ 5 , 14 ]. Also, the World Health Organization (WHO) stipulated in its report that the COVID-19 pandemic negatively impacted the equity regarding essential health service delivery in its member states [ 4 , 17 ]. The report further revealed that more than 50% of its member states experienced disruption in delivering health care services on NCDs, cancer, and mental health disorders. Some of the reasons given for this disruption include shortage of staff due to their transfer to COVID-19 care centers, lack of public transport, and cancellation of planned appointments, while the reasons recorded in 20% of the member states were: the shortage of medicines, diagnostics, and other technologies [ 4 ]. Due to the various forms of hardship or discomfort caused by the pandemic, vulnerable individuals, such as people with diabetes mellitus, are likely to perceive the period differently than healthy people. Patients with diabetes are likely to have a negative perception of the COVID-19 condition, which could influence the adoption of harmful coping mechanisms that could further hamper their health outcomes. Although several perception studies have been done on COVID-19 generally in Nigeria, such as that of Osahon and Memudu [ 15 ] on the perception and healthy attitudes of Nigerians to COVID-19, very little data is available about the perception of diabetes patients of the COVID-19 pandemic. This study explored the perceptions of patients with diabetes mellitus during the pandemic and their coping mechanisms during the period. This is important to illuminate the experiences of patients with diabetes mellitus during the pandemic, and the findings could be beneficial to the government and healthcare stakeholders in formulating policies to help improve the health outcomes of patients with diabetes during the pandemic.

Study design

We adopted an explorative qualitative research approach [ 16 ]. This approach is suitable for understanding the perception of diabetes mellitus patients at University College Hospital and the coping mechanisms during the COVID-19 pandemic. This qualitative research approach also guide the collection of in-depth data from the participants in their natural form [ 16 ].

Study setting

The study was conducted in the University College Hospital, Ibadan. University College Hospital is a tertiary health center that serves Oyo state and neighbouring states where patients with diabetes, including those with suspected COVID-19 cases, are seen. According to statistics from the Nigeria Centre for Disease Control and Prevention (NCDC) [ 17 ], Oyo State is among the COVID-19 most infected states in Nigeria, and Ibadan is its capital city. The University College Hospital was founded in November 1952, located at Oritamefa in the Ibadan North Local Government Area. It is the first teaching hospital in Nigeria to provide in-patient and outpatient health care services. It receives referrals from southwestern and other parts of Nigeria and outside the country. The Diabetes clinic runs every Monday, and an average of 50–70 patients visit the clinic daily.

Participant sampling and sample size

Participants in this study were registered diabetes patients who had been visiting the outpatient diabetes clinic at University College Hospital before the pandemic and are still attending the clinic during the pandemic. We used a purposive sampling technique to recruit 30 participants for the study, which was determined using the data saturation method. These participants constituted those who experienced the phenomena under study. Patients who were living with diabetes mellitus disease prior to the pandemic (at least more than a year) and aged 18 years and above were included. However, those accessible during the data collection period were included. The rationale was that this category of patients with diabetes mellitus could tell the difference between their experiences in the clinic before and during the pandemic. Being coherent, healthy, gave informed consent were other inclusion criteria for the study. Patients who did not consent to the study or were no longer interested in participating even while in the middle of it were excluded from the study. Patients diagnosed with diabetes after the outbreak of COVID-19 and/or who did not attend the diabetes clinic during the study period were not included. Also, patients with acute or chronic debilitating comorbidities were not included in the study.

Data collection procedure

Four (4) trained research assistants were used for the data collection. The research assistants were trained anthropologists, who the authors also trained in areas consisting of the consenting process, interviews, asking probing questions, and recording. The authors developed an interview guide as the data collection tool. Data on the participants’ sociodemographic characteristics and the study objectives were collected after obtaining consent. The probe questions were structured to capture responses to the participants’ perceptions of the COVID-19 pandemic. It also covered responses to the coping mechanisms adopted by diabetes mellitus patients during the pandemic. Prior to the data collection, we informed the participants about any possible discomfort, benefits, and compensation associated with the study. Interviews were conducted once the participants agreed to a date, time, and place of convenience to participants. The participants were approached for recruitment at the end of the medical appointments, and those who consented were interviewed at the premises of the hospital. The data collection lasted for an average of 60 minutes per participant. The participants were compensated with an equivalent gift of three US dollars ($3) at the end of the interview.

About 15 interviews were conducted each week for two weeks by one of the authors with four trained anthropologists who had qualitative fieldwork experiences. The anthropologist helped in administering the interview guide. Interviews were conducted with strict adherence to the COVID-19 precautionary measures. The data collection/interviews were done between the 15 th to 22 nd of March 2021 using a pretested interviewer guide. The participants were recruited using a purposive sampling technique. All the interviews were tape-recorded, and field notes were taken and utilised during the transcription and analysis. Data transcription was carried out after every fieldwork, and this helped in identifying questions that may have been left unanswered during the interview or those needing further probing, as well as identifying the point of saturation where no further interviews were conducted. The research assistants helped with field notes, tape recording and data analysis.

Data analysis

All the audio data was transcribed verbatim on the same day the data was collected. After the transcription by the research assistants, After the transcription of the data, the transcripts were vetted and proofread by OOTA, OAB and WOB. Later, the transcripts were made accessible to OAB, who performed the initial independent thematic analysis [ 18 ]. Using the ‘nodes’ function in NVivo-12 software, where codes were assigned to the text data from the transcripts [ 19 ]. During the analysis, all similar recurring codes were categorised to generate themes and, subsequently, sub-themes [ 18 ]. The extracts and quotes from the themes and sub-themes generated were used to support the results of the study. All the authors approved the extracts and quotes. A pretest of the interview guide was done with two (2) potential respondents (male and female) among those who came for medical appointments prior to the actual commencement of the main data collection. The interview guide pretest results show accurate consistency, but the results were not included in the main study.

Rigour and trustworthiness

In every qualitative study, credibility and trustworthiness measures are critical. In achieving this, we allowed two research assistants with experience in qualitative analysis to transcribe and analyze tape-recorded interviews separately. The two research assistants’ themes and sub-themes, as well as the authors, were compared to ascertain their consistency. To strengthen the credibility of the results, direct quotations and precise summaries of participant remarks were used. A week after the transcription and preliminary data analysis, we conducted member-checking with three of the participants to demonstrate trustworthiness. This allowed the participants to attest that the transcripts accurately captured the content of the interviews. Nobody offered changes or voiced complaints about the interviews’ calibre or content in terms of clearly expressing their viewpoints. The participants’ nonverbal cues, their concerns, and the interviewers’ observations were all documented in the field notes that were taken following each interview and consulted throughout the research. The authors who carried out the interviews are qualified healthcare researchers with expertise in conducting IDIs.

Ethical issues

Ethical clearance was sought from the Ibadan/University College Hospital Ethics Committee (UI/UCH EC) with approval number UI/EC/21/0064. In this study, we complied with all the ethical guidelines pertaining to using human participants and peculiar to qualitative studies. We anonymized all the transcripts and audio files by giving them pseudonyms to remove any personal information that may be used to identify the study participants. The participants in the study were given an information sheet that included information on the objectives, methods, potential risks and advantages, compensations, who to contact, and an affirmation of confidentiality, privacy, and autonomy. The participants gave written consent by signing the consent form for participating, and for recording the interviews. Later, the participants’ signed informed consent was requested. This demonstrated that they had read and understood the terms of reference before deciding to participate freely in our study. We also encrypted a passcode and locked the audio files and transcripts to prevent unauthorised individuals from accessing the material.

In-depth interviews were held with thirty patients with diabetes mellitus in the outpatient ward of the endocrinology clinic. Each interview lasted for about an hour.

Demographic characteristics of participants

A total of thirty participants were recruited for the study, consisting of approximately two-thirds females and one-third males. Most participants were elderly, with the oldest being an 84-year-old female and the youngest a 21-year-old male. More than half were Christians, with the remainder being Muslims. All males, except the youngest, were married. Among the females, most were married, with two widows, one single and one separated.

Over half of the participants had tertiary education, a few had secondary education, and a small number had primary education. Only a few females had no formal education, whereas all males had some level of formal education.

Most males were retired, with three employed and one unemployed (the youngest male). Among females, more than two-thirds were employed, three were unemployed, and two were retired. Participants’ socio-economic status ranged from average to low.

Concerning diabetes type awareness, seven out of ten female participants did not know their type, while all but one male participant was aware. Most participants had type 2 diabetes, except for one male and one female in their twenties who had type 1 diabetes.

Emerging themes from the study

Table 1 presents the major themes and sub-themes that emerged from the study. While analyzing data, two key themes emerged: The perception of Diabetes Patients during the COVID-19 Pandemic and the coping mechanisms employed by diabetes mellitus patients during the pandemic.

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https://doi.org/10.1371/journal.pone.0309451.t001

Perception of diabetes mellitus patients during the COVID-19 pandemic

This theme contains three sub-themes (clinic appointments, effects of the COVID-19 pandemic on diabetes patients, and adherence to COVID-19 protocols).

Clinic appointments.

Data from the key informant interviews revealed that the pandemic was perceived as a period that has negatively affected appointments, clinic attendance, and the management of diabetes in the clinic. A participant stated that

Yes, like I just told you, it has affected it a lot because I have been coming for months now, and I have not been able to see the doctor (IDI, Participant 10, Female, 45 years). The pandemic has affected my clinic attendance because, presently, I only come to the clinic when the doctor gives me appointments. Prior to the pandemic, asides from my appointment dates, I come to the clinic every first Monday of the month because we diabetes patients usually hold meetings in the diabetes association office; however, since the emergence of the pandemic, we have stopped holding the meeting (IDI, Participant 9, Male, 21 years)

Effects of the COVID-19 pandemic on patients with diabetes mellitus.

This sub-theme has ten codes, which include the vulnerable groups during the pandemic. The participants revealed a clear understanding of the fact that diabetes patients are vulnerable during the pandemic. A number of the patients demonstrated a clear knowledge of the category of people who are vulnerable to COVID-19 infection. They perceived this category of people as the aged, those who defy preventive measures, and people with comorbidities. However, some of the participants were unaware of who could be susceptible to the virus.

Some of the diabetic patients who were not observing the COVID-19 precautionary measures are vulnerable to the virus, as encapsulated in the excerpt below:

Anybody can contract it, especially those who fail to wash their hands and follow the preventive measures (IDI, Participant 2, Male , 75 years). Those who fail to adhere to the necessary precautions , those who talk with their whole mouth open without using their nose masks and those who stay too close to other people (IDI , Participant 9 , Male , 21 years) . The elderly / people with underlying diseases Yes, people that are already sick before and the elderly ones (IDI, Participant 10, female, 45 years). It cannot have any negative impact on diabetes patients if they take their medications regularly and follow necessary precautions (IDI , Participant 9 , Male 21 years) .

Some participants, however, did not know who could get infected with the virus, as evidenced in the below excerpt:

I can’t say (IDI, Participant 1, female , 74 years). Only God knows (IDI , Participant 4 , female , 84years)

They posited that the COVID-19 virus could have severe impacts on them. The opinion of one participant in this regard is captured in the excerpt below:

The diabetes patient could get infected and the person might not get cured of it. It could even kill such a person (IDI, Participant 8 , Female, 52years).

A few others were of the opinion that COVID-19 cannot have any deadly implications on patients with diabetes since one can be treated if infected.

The impact it can have is for one to get infected, and even if one gets infected, since it can be treated. I don’t think it can bring about any deadly impact except for someone whose time is up on this planet earth already (IDI, Participant 12 , Female 28 years).

Patients with diabetes are not vulnerable in as much as they follow their diabetes regimen:

I don ’ t think there should be any effects if they use their drugs regularly, exercise as well and take away the fear of contracting the disease (IDI , Participant 2 , Male 75 years) .

The in-depth interview further revealed that most of the participants were not afraid of the COVID-19 virus. The submission of a participant is clear on this, as evident in the statement below:

Ehn … It did not make me scared because I firstly did not believe it was real but as time went on and I started hearing that people were really contracting it, it was then I believed that COVID-19 is real. However, till now, I have not seen anyone who has contracted it in my vicinity. As such, that is one of the reasons I did not really get scared about it (IDI, Participant 12, Female 28years).

Patients with diabetes mellitus noted that they were not fearful of the pandemic because they trusted in the Supreme Being, their object of worship (God). The results further showed that a couple of patients with diabetes mellitus were not afraid during the pandemic due to their trust in their medications, the quality of health care provided in the University College Hospital diabetes clinic and their proper adherence to the COVID-19 precautionary measures. The excerpts below capture this:

I’m unruffled. I know we have problems all over the world but I’m a Christian and I’m unruffled (IDI, Participant 2 , Male 75 years). I was not afraid , I don’t believe in it . I have Jesus (IDI , Participant 21 , Male 65 years) .

On the contrary, a few participants perceived that the COVID-19 pandemic was a fearful one, and they perceived it to be the end of their life. This is evident in the excerpts below:

A fearful period

I was thinking I was going to die (IDI, Participant 14 , Female 30years). I was very scared , but God’s grace is sufficient (IDI , Participant 1 , Male 74 years) .

Adherence to COVID-19 protocols.

This sub-theme encompassed the physical presentation of patients only when necessary and allowance of physical presentation of patients with strict adherence to COVID-19 protocols.

Findings from the interviews revealed that the clinic avoided unnecessary physical presentation of diabetes mellitus patients during the pandemic by prolonging appointments. Patients were advised to call doctors on the clinic lines except when there is a pressing health concern that requires a physical presentation of the patient in the clinic. Also, the opinion of a participant revealed that patients are informed to adhere to the COVID-19 precautionary measures whenever they need to be physically present in the clinic. These opinions are encapsulated in the opinions below:

Adherence to the COVID-19 safety protocols through prolonged appointments

They did well before the pandemic, and they answered us on our appointed dates, but since the pandemic started, I’m just coming to see the doctor, it’s over a year already. I’ve been coming in the previous weeks but I was sent back home saying that only when the doctor calls me is when I can come. All these were not there before the pandemic; they kept to their appointments then ((IDI, Participant 18 , Female 80 years). Yes , I am faithful but here , they are not faithful . The staff , attendants and the records officials are not faithful . Sometimes , when I come on my appointment dates , on getting here , they would tell me they have rescheduled my appointment because of COVID-19 (IDI , Participant 10 , Female 45 years) . I didn’t visit the hospital when the pandemic began , but when the hospital was open , I came , and we were told to use our drugs , and I haven’t been able to see the doctor again . It’s been a year I saw a doctor; I just saw the doctor on the first of March this year since all these while . Whenever I have appointments , I use to come , but University College Hospital is not helping matters cause most times I will come , they will say they’ve re-scheduled my appointment many times (IDI , Participant 22 , Female , 72 years) .

One of the diabetes mellitus patients indicated that the COVID-19 precautionary measures were mandatory for all patients in the clinic.

They make sure we use our nose mask, they do temperature checks before you come in, even at the gate, they tell you to put your mask on (IDI, Participants 20 , Male 75 years).

Coping mechanisms adopted by patients with diabetes mellitus

Coping mechanisms emerged as the second theme. The sub-themes were mechanisms adopted by the clinic, coping mechanisms adopted by the patients with diabetes mellitus, reasons for low subscription to telehealth, and dangerous coping mechanisms used by the patients with diabetes mellitus.

Mechanisms adopted by the clinic.

Under this sub-theme, the patients with diabetes mellitus mentioned that the coping mechanisms put in place at the diabetes clinic include the adoption of an online database, provision of avenues to review prescriptions, encouragement of daily monitoring of blood sugar, telehealth, and awareness creation. The following narrative quotes to support this sub-theme;

Now that they’re using technology, things are improving, so little by little, I hope they will do better (IDI, Participants 11 , Female 65 years). They treat me well each time I come. I am always instructed to get an exercise book to write my blood sugar level when I check it every morning and night every day. Once I come to the clinic, I do show the doctor the book. If it is normal, the doctor will not increase my medications, but if it is high, my medications will be increased. That is the way I am attended to (IDI, Participant 12, Female 28 years)

Telehealth.

Participants shared their experiences with the communication services provided by the clinic:

They have call center, they introduced a call center that patients can call and speak to the doctors and nurses, errm I think it’s not 24 hours, but its during working hours (IDI, Participants 17, Male 77 years). I am only aware of the fact that I got a message from the clinic during the early period of the pandemic that I should call some numbers in case an emergency issue arises concerning my health (IDI, Participant 8, Female 52 years).

Coping mechanisms adopted by patients with diabetes mellitus.

The patients utilized positive coping mechanisms such as adherence to preventive measures and reliance on the media for COVID-19 updates. This is captured in the responses below by a number of the participants:

Adherence to the COVID-19 precautionary measures was one of the coping mechanisms the patients with diabetes mellitus adopted in preventing themselves from COVID-19 infection.

They make sure we use our nose mask, they do temperature check before you come in, even at the gate they tell you to put your mask on (IDI, Participants 20 , Male 75 years). I simply follow the laid preventive measures and I keep myself clean in the house’ (IDI , Participant 4 , Female 84 years) . I was just doing what I was supposed to do and didn’t do what i wasn’t supposed to . For example , I have been avoiding crowded places . I have not attended Jumat service since the pandemic began rather , my family and I observe our prayers together at home (IDI , Participant 3 , Male 63 years) .

A couple of the patients with diabetes mellitus relied on the frequent updates on COVID-19 from the mass media as a coping mechanism against the pandemic.

I listened to health programs on the radio and I adhered to their health advices and I also took precautions. It was the precautionary messages and COVID-19 jingles delivered by newscasters on the radio I listened and adhered to (IDI, Participants 8, Female , 52 years).

A few of the participants averred that though they were aware of the telehealth service provided by the clinic, they did not utilize it as a coping mechanism. This is vivid in the opinion of some participants.

During the COVID I received text messages inviting me to come for my check up. But I didn’t come ooo!. But they’re trying (IDI Participants 11, Female 65 years). I didn’t because there was no reason for me to call them ( IDI , Participants 3 , Male 63 years) .

One of the patients opined that they were not aware of the telehealth service provided by the clinic. The provision of the telehealth service was helpful as it came as a timely intervention for some patients who utilized it. This is evident in the response of one of the participants, who opined thus:

Yes during the pandemic when we wanted to see the doctor, we were told to call him on the phone, when I called the doctor I was told the drugs to buy (IDI, Participants 30 , Female 44 years).

Reasons for low subscription to telehealth.

The findings of the study revealed that despite the provision of telehealth service as a coping mechanism, there are however some limitations to its use among patients with diabetes mellitus in University College Hospital.

One of the diabetes mellitus patients opined that he did not use it because a need to utilize the service did not arise. The excerpt below encapsulates this.

I didn’t because there was no reason for me to call them (IDI, Participants 3, Male 63 years)

Also, a level of full awareness regarding telehealth has not been reached among diabetes mellitus patients in the clinic; as such, a few patients did not utilize the service because they were unaware of it.

No, I did not. I wasn’t aware of that service (IDI, Participants 4, Female 84 years). No, I am not aware of it (IDI, Participants 12, Female 28 years).

Dangerous mechanisms employed by patients with diabetes mellitus in the clinic.

The study revealed the employment of negative mechanisms by diabetes mellitus patients in the clinic. This is evident in the excerpts below:

The use of herbal medicines

I used some traditional herbs to also compliment my medications. I drank the juice from boiled mango leaves and ginger. I also took my injections. I stayed indoors and maintain social distancing the few times I go out. Most times even if I feel like going out, my parents will not allow me go out because they know that I am more vulnerable to COVID-19 ( IDI, Participants 12, female, 28 years). I do a lot of steaming , herbal steaming , I cook dongoyaro leaves and the bark , we boil it , and we drink on the first day and subsequent days we just steam . Everybody in my house steams , we use menthol , we add menthol to it and we take a lot of supplements , vitamin C and D , that’s all we’ve done so far ( IDI , Participants 17 , Male 77 years) .

Usage of old prescriptions

I continued buying the drug that was prescribed to me since the last time I came to the clinic. By the time my health deteriorated recently and I have been coming to the clinic, the prescription was changed, but I was already used to my old prescription (IDI, Participant 12, Female, 28 years).

Inconsistency in clinic attendance

Many at times, most of us do not come to the clinic because we do not have money (IDI, Participant 9, Male 21 years).

Suggested coping mechanisms for the management of the University college hospital clinic and the government.

The patients with diabetes mellitus gave some recommendations on how the management of the University College Hospital Diabetes Clinic and the government can assist in easing the stressful conditions of diabetes mellitus patients during the COVID-19 pandemic. They are captured in the excerpts below:

Some participants want their medications to be subsidized and be easy to get.

What I think can be done is….You see, there is a saying that someone who has diabetes and does not want to die early needs money because it is not easy if I would be honest with you. I think what they can do is if they can help us subsidize our drugs. If we are given free drugs once in a while even if it is one drug, it would go a long way. What can be done is if they can help us that way once in a while then if they can help us find means through which our medications will not be scarce to get and they should help us such that it would not be too expensive than what we can bear. See… if it is not too expensive, there is nobody that does not want to use their medications and be healthy but the inability to afford the drugs makes one not to be faithful with the medications. Those are the ways I think they can help us ( IDI, Participant 12, Female 28 years). They can make the drugs cheaper, some can’t afford it and it led to their death(IDI, Participant 18, Female 52years) They should provide free drugs for us . Many at times , most of us do not come to the clinic because we do not have money ( IDI , Participant 9 , Male 21 years) .

Some patients with diabetes mellitus mentioned that the consultation fees should be reduced and this is captured in the narratives below.

One thing they can do is to reduce the consultation fees. Sometimes after paying the money, there won’t be anything left anymore. And sometimes, if we pay and the doctor is not around, the hospital won’t refund the money; that one is gone ( IDI, Participants 30, Female 44 years). We are not equal and not all buoyant . The consultation fee can be reduced and some things can be given for free , even if it is a few drugs ( IDI , Participants 13 , Female 49 years) .

Reduction of waiting time was one of the recommendations suggested by patients with diabetes for the management of University College Hospital. This is supported by the quote below;

Ah the major thing is that they should answer us in time. I understand that they will first do ward round but immediately they come back they should answer us ( IDI, Participants 11, Female 65 years).

One of the participants opined that there should be continuous or regular meetings which can be held in an open space within the clinic in other for them to be updated on their next line of action such as receiving medications, medication review, and adherence to COVID-19 protocols. The except below summarises this assertion.

We have an association but University College Hospital is not allowing us to hold meetings now, and its affecting a lot, through the association, we have had numerous lectures from physiotherapist and dieticians, to teach us more about our condition but our venue is small and due to COVID-19 regulations, those meetings can’t hold but we have pleaded with the management to allow us to do it outside in the open. Because the absence of those meetings is affecting some of us who have no clue as to go about something regarding our ailment ( IDI, Participants 26, Female 68 years).

Other suggested coping mechanisms include: opening more call lines to ensure efficient telehealth services, ensuring patients are treated politely in the clinic, and provision of hygienic toilet facilities.

This study explored the perception and coping mechanisms employed by patients with diabetes mellitus during the COVID-19 pandemic. We found that most participants were not fearful due to the pandemic; rather, they were optimistic while they played their part in ensuring they were safe. This is consistent with the findings of a study conducted in India [ 20 ], which revealed that most of the participants in their study were not so anxious about the pandemic but were rather optimistic. Also, the participants in this study demonstrated a clear understanding of those vulnerable to COVID-19, as some posited that anybody who defies the COVID-19 precautionary measures, people with underlying diseases such as diabetes, are susceptible to the virus. This attests to the supposition that COVID-19 sensitization and training were done in communities and health facilities. Also, surveillance mechanisms were improved in communities in Nigeria [ 20 ].

Literature has revealed that some health facilities had to shut down the entire clinic, including diabetes outpatients, to protect the health care providers and patients from contracting the virus [ 21 ]. Similarly, our findings show that the vulnerable nature of the patients informed why all appointments in the University College Hospital diabetes clinic were cancelled during the early period of the pandemic, after which they were rescheduled till January 2021. Furthermore, our study confirms compliance with WHO’s [ 4 ] recommendation on the use of telemedicine in other to bridge the health access gap caused by the pandemic. Hence, the physical presentation of patients during the pandemic was only encouraged when necessary. However, the study also revealed that patients who attend the diabetes clinic have been adhering to the COVID-19 precautionary protocols such as wearing masks and social distancing most especially when they attend the clinic since it reopened.

Contrary to the assertion made by Ahmed [ 5 ] that most of the public hospitals have been converted to COVID-19 treatment centers, which made lots of patients with comorbidities stranded when they needed medical attention, this study found that the University College Hospital diabetes clinic was only closed during the early period of the pandemic in order to ensure the safety of its staff and patients. In addition, the study revealed that the patients were not left stranded by the clinic as telehealth was provided as an alternative was provided. Patients also had access to healthcare personnel on an appointment basis after the clinic reopened in January 2021. Interestingly, the study revealed that patients were encouraged by the clinic to monitor their blood glucose daily by keeping records of it in a book. Another measure instituted was reducing the crowd in the outpatient clinic by extending patients’ appointment dates. This had the negative effect of limiting access to healthcare personnel during the pandemic. As a result, many patients with diabetes have had their routine screening deferred [ 11 ].

The findings of this study revealed that COVID-19 precautionary measures were strictly adhered to in the clinic, and patients have been compliant. This is, therefore, consistent with the recommendations of the WHO that preventive measures such as social distancing, the use of masks, and hand sanitisers should be adhered to [ 4 ]. Awareness of the availability of the telehealth service was high among the participants. However, awareness goes beyond knowing that a service exists. It is concerned with understanding and utilizing that knowledge [ 22 ].

Contrary to the findings of Hartmann-Boyce [ 23 ], which showed that many patients could not utilize the telehealth service because of their inability to afford the equipment needed for the process, findings from the in-depth interviews revealed that most patients did not utilize telehealth because they did not have reasons to use it. However, very few participants who claimed to utilize the service in this study reported that it was helpful.

The religious nature of Nigerian society is evident in the findings of this study, as most of the participants found succor from the worries and fears of the pandemic in the “Supreme Being”. This is consistent with the supposition that most patients with diabetes eased their fear during the pandemic by trusting the divine being and seeking supernatural protection from the same [ 24 ]. Reliance on the media for sensitization and updates on the pandemic was noted in the study. This affirms the views of Effiong et al. [ 25 ] in Nigeria, where the media was utilized to disseminate messages to the masses on how the virus can be spread and how it can be prevented. Some patients coped by being regular on their medications. This finding is consistent with similar studies [ 26 , 27 ], as it also revealed that some patients with diabetes in University College Hospital were able to cope when the clinic was closed during the early period of the pandemic by using their last prescriptions before the pandemic to procure more drugs.

Furthermore, the use of traditional herbs alongside medications was shown in the study. This is consistent with the findings from the key informant interviews. This confirms that most non-COVID-19 patients relied more on local medications and homemade remedies to cater for their health during the pandemic [ 28 ]. Evidence shows that the burden of diabetes management is more on patients with diabetes mellitus in Nigeria, as about 74.5% of the health care expenditure is self-financed by patients while the government provides only 25.5% [ 29 ]. This study found that interventions such as subsidisation, availability of drugs, and reduction of consultation fees would help patients cope better during the pandemic. In addition, approval of the resumption of the University College Hospital diabetes association meeting, shortening waiting time in clinics, creation of more call lines, polite treatment of patients, increased sensitization, and the provision of hygienic toilet facilities would help alleviate the stress of the pandemic on diabetes patients in University College Hospital.

Strengths and limitations

The study’s main strength is that it examined the perception and coping mechanisms of patients with diabetes mellitus in a tertiary health center during the COVID-19 pandemic. The qualitative nature of the study only permitted a small number of participants in the hospital to be interviewed; therefore, it is important to evaluate our findings carefully before extrapolating them to the entire country.

Implications for public health research

Based on the study’s findings, it is imperative for health professionals to routinely conduct psychological assessments for diabetes mellitus patients. Also, the health service managers can design a guidance and assistance programme for patients with diabetes mellitus intended to improve their ability to adopt coping mechanisms.

The study has shown that patients with diabetes mellitus were not fearful of the COVID-19 pandemic despite their status as diabetes mellitus patients. Diabetes mellitus patients were found to be adherent to the COVID-19 precautionary protocols. The health systems’ coping mechanisms to avert the pandemic’s negative implications were telehealth, encouragement of daily monitoring of sugar levels, and the provision of avenues for a medication review. Additionally, the patients relied on mass media advice and adherence to safety protocols to cope with COVID-19. Based on the study’s outcomes, the government and other healthcare stakeholders must reinforce the resilience of diabetes mellitus patients by alleviating their health burdens during the pandemic. This could be done by subsidizing the prices of drugs, tests, and consultation fees, improving the waiting and appointment system in the clinic, creating an online presence for the University College Hospital Diabetes Association Office, and employing more health personnel in the clinic.

Supporting information

S1 checklist. strengthening the reporting of observational studies in epidemiology statement checklist..

https://doi.org/10.1371/journal.pone.0309451.s001

S1 File. Study questionnaire.

https://doi.org/10.1371/journal.pone.0309451.s002

Acknowledgments

The authors express their appreciation to the University College Hospital, Ibadan, for the privilege of conducting the study within its diabetes clinic. We also thank everyone for their various contributions and assistance during the study.

1. Organization WH. Global report on diabetes: World Health Organization; 2016.
2. Organization WH. Diabetes 2022 [3rd November, 2022]. Available from: http://www.who.int/mediacentre/factsheets/fs312/en/ .
3. Programme UND. The Impact of the COVID-19 Pandemic in Nigeria: A Socio-Economic Analysis 2020 [4th November, 2022].
4. Organization WH. Rapid assessment of continuity of essential health services (EHS) during the COVID-19 pandemic 2020 [3rd November, 2022].
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A case report: First presentation of diabetes mellitus type 1 with severe hyperosmolar hyperglycemic state in a 35-month-old girl

Affiliations.

1 Division of Pediatric Intensive Care Department of Pediatrics Shiraz University of Medical Sciences Shiraz Iran.
2 Division of Pediatric Metabolism and Endocrinology Department of Pediatrics Shiraz University of Medical Sciences Shiraz Iran.
PMID: 34765201
PMCID: PMC8572339
DOI: 10.1002/ccr3.4984

Hyperglycemic hyperosmolar syndrome (HHS) is a rare complication of diabetes mellitus among pediatric patients. Since its treatment differs from diabetic ketoacidosis (DKA), hence, pediatricians should be aware of its diagnosis and management.

Keywords: case report; diabetes mellitus; hyperglycemic hyperosmolar syndrome (HHS); pediatric patients; rhabdomyolysis; thrombosis.

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World J Diabetes
v.7(1); 2016 Jan 10

Milestones in the history of diabetes mellitus: The main contributors

Correspondence to: Marianna Karamanou, MD, PhD, Department of History of Medicine, Medical School, University of Athens, Greece 4 str, Themidos, Kifissia, 11527 Athens, Greece. rg.aou.dem@uonamarakm

Telephone: +30-210-7461437 Fax: +30-210-8235710

Diabetes mellitus is a group of metabolic diseases involving carbohydrate, lipid, and protein metabolism. It is characterized by persistent hyperglycemia which results from defects in insulin secretion, or action or both. Diabetes mellitus has been known since antiquity. Descriptions have been found in the Egyptian papyri, in ancient Indian and Chinese medical literature, as well as, in the work of ancient Greek and Arab physicians. In the 2 nd century AD Aretaeus of Cappadocia provided the first accurate description of diabetes, coining the term diabetes, while in 17 th century Thomas Willis added the term mellitus to the disease, in an attempt to describe the extremely sweet taste of the urine. The important work of the 19 th century French physiologist Claude Bernard, on the glycogenic action of the liver, paved the way for further progress in the study of the disease. In 1889, Oskar Minkowski and Joseph von Mering performed their famous experiment of removing the pancreas from a dog and producing severe and fatal diabetes. In 1921, Frederick Banting and Charles Best extended Minkowski’s and Mering’s experiment. They isolated insulin from pancreatic islets and administrated to patients suffering from type 1 diabetes, saving thus the lives of millions and inaugurating a new era in diabetes treatment.

Core tip: Diabetes mellitus has been known since antiquity and despite therapeutic advances it still remains an incurable chronic disease. In our historical article, we attempt to provide the most important steps in the history of diabetes mellitus from antiquity till nowadays. The contribution of leading medical figures such as Aretaeus of Cappadocia, Thomas Willis, Claude Bernard, Oskar Minkowski, Joseph von Mering, Frederick Banting and Charles Best is mentioned, in an attempt to highlight the development of our current knowledge in diabetes mellitus.

INTRODUCTION

Diabetes mellitus is a group of metabolic diseases involving carbohydrate, lipid, and protein metabolism. It is characterized by persistent hyperglycemia, as a result of defects in insulin secretion, insulin action or a combination of both, defective secretion and incorrect action. There are two main types of diabetes mellitus: Type 1 (insulin-dependent), and type 2 (non-insulin-dependent). Type 1 diabetes results by the autoimmune destruction of the β-cells of the pancreatic islets and type 2 diabetes is caused from impaired insulin secretion and resistance to the action of insulin[ 1 ].Current epidemiological data reveal that 9% of adults, 18 years of age and older, has diabetes mellitus while it was estimated that in 2012, 1.5 million people died due to the disease. According to the World Health Organization, diabetes will be the 7 th leading cause of death in 2030[ 2 - 4 ].

The disease has a long history reaching back into antiquity. However, during that period, due to a poor knowledge of anatomy, pathophysiology and lack of diagnostic tools, the disease remained extremely perplexing to physicians.

Nevertheless, physicians in antiquity observed the distinctive features of diabetes and proposed several therapeutic approaches. In Ebers papyrus, dated back to 1500 BC, we may find passages describing patients who suffer from excessive thirst, copious urination and they are treated by plants’ extracts. However, according to the Egyptian endocrinologist, historian of medicine and translator of the Ebers papyrus Paul Ghalioungui (1908-1987), the description of a probable diabetes, in Ebers, is regarded as unsatisfactory and probably wrong. In Kahun papyrus (c. 2000 BC) there is just the title of a recipe for the “Treatment of a thirsty woman”, but the text is missing[ 5 ]. So, we may assume that ancient Egyptians could not recognize behind the symptoms of specific disease entity such as diabetes.

Around the 5 th century BC, the famous Indian surgeon Sushruta, in his work Samhita, identified diabetes, by using the term madhumeha (honey-like urine) and pointed out not only the sweet taste of the urine but also its sticky feeling to the touch and its ability to attract the ants (!). Sushruta further mention that diabetes affects primarily the rich castes and is related to the excessive food consumption as the rice, cereals and sweets[ 6 ].

In ancient China, Chang Chung-Ching (ca. 160-ca. 219), referred to as “the Chinese Hippocrates”, described polyuria, polydipsia and loss of weight as symptoms of a specific disease, while in 7 th century AD Chen Chuan recorded the sweet urine in diabetes mellitus and named the disease Hsiao kho ping mentioning its characteristic symptoms: intense thirst, copious drinking and large amounts of urine which is tasted sweet. In an attempt to treat that disease his colleague Li Hsuan proposed the abstinence from wine, salt and sex[ 6 ].

From the 8 th century onwards, physicians observed the tendency of diabetic patients to develop skin infections as furuncles, rodent ulcers and troubles of the eyesight. In 11 th century AD, the celebrated Arabo-islamic physician Avicenna (980-1037) in his textbook El-Kanun (Canon of Medicine) described diabetes and mentioned gangrene and sexual dysfunction as its complication. Years later, the medieval scholar Moises Maimonides (1138-1204) described in detail diabetes, including the symptoms of acidosis[ 6 ].

Ancient Egyptians, Indians, Chinese and Arabs tried to describe the clinical signs and symptoms of diabetes mellitus. However, few are the main protagonists in the history of diabetes mellitus who contributed significantly, not only to its diagnosis and treatment but also to the development of our current notions on the disease, paving the way for further study and establishing a new medical sub specialty, diabetology.

ARETAEUS OF CAPPADOCIA (2 nd CENTURY AD) AND THE FIRST ACCURATE DESCRIPTION OF DIABETES

Aretaeus, surnamed the Cappadocian, is probably the greatest physician of the Greco-Roman antiquity after Hippocrates, and at least equal of Galen. He was born in Cappadocia, a region in eastern Asia Minor, studied medicine in Alexandria and practiced in Rome probably during the 2 nd century AD. Areataeus’ medical practice was based on the principals of the Pneumatic school believing not only in the vital role of pneuma (air) but embracing also the theory of the four humors (heat, coldness, moisture, dryness). In his two treatises, De causis et signis morborum acutorum et diuturnorum (on the causes and symptoms of acute and chronic diseases) and De curatione morborum acutorum et diuturnorum (on the cure of acute and chronic diseases), written in Ionic dialect, Aretaeus impresses us by the vividness and the simplicity of his descriptions. Among others he described, in an accurate way for his time, leprosy, asthma, pneumonia cancer, tetanus, hysteria, epilepsy, gout[ 7 , 8 ] (Figure (Figure1 1 ).

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The distinguished physician Aretaeus of Cappadocia. (Source: Wellcome Library, London).

Before Aretaeus, ancient Greek medical authors such as Rufus of Ephesus (c. 1 st century AD) and Galen (130-c.201) were mentioning that diabetes was provoking excessive thirst, polyuria, emaciation of the human body, leading sometimes to death. The symptom of polyuria gives the idea to Galen, who according to his own writings he has seen the disease only twice, to name diabetes diarrhea urinoma (diarrhea of the urine). Later, the term diabetes was introduced into medical nomenclature by Aretaeus. It arises from the Greek verb διαβαινω (diabaino) which means I pass through and diabetes, the condition that the fluid runs through.

In the following passage of Areateus’ work, we may admire the clinical presentation and interpretation of diabetes: “Diabetes is a wonderful affection, not very frequent among men… The course is the common one, namely, the kidneys and the bladder; for the patients never stop making water, but the flow is incessant, …. The nature of the disease, then, is chronic, and it takes a long period to form; but the patient is short-lived, if the constitution of the disease be completely established; for the melting is rapid, the death speedy. Moreover, life is disgusting and painful; thirst; excessive drinking, which, however, is disproportionate to the large quantity of urine, for more urine is passed; and one cannot stop them either from drinking or making water. Or if for a time they abstain from drinking, their mouth becomes parched and their body dry; they are affected with nausea, restlessness, and a burning thirst; and at no distant term they expire. Thirst, as if scorched up with fire... But if it increase still more, the heat is small indeed, but pungent, and seated in the intestines; the abdomen shriveled, veins protuberant, general emaciation, when the quantity of urine and the thirst have already increased; and when, at the same time, the sensation appears at the extremity of the member, the patients immediately make water”. For the treatment of the disease he proposes the consumption of cereals, milk and wine, the topical application of cataplasms and the administration of Theriac, the famous cure all remedy of antiquity[ 7 , 8 ].

However, it remains unknown how Aretaeus made such a precise description of a relatively rare disease during that period, just by observation.

THOMAS WILLIS (1621-1675) AND THE TERM “MELLITUS”

The English anatomist and physician Thomas Willis, is considered one of the greatest physicians in 17 th century. He lived in a period that England was in political and religious turmoil and he needed to interrupt several times his studies. Willis studied classics and then medicine at Oxford where he was appointed Professor of Natural Philosophy to the highly prestigious Sedleian chair. During his career, he wrote several books and articles on medicine and his work on the anatomy of the brain and nervous system, based on his own dissections, remains very celebrated. Willis provided the description of the autonomic nervous system, the spinal cord, the vasculature at the base of the brain (circle of Willis) and the cranial nerves, including the accessory nerve (Willis’ nerve)[ 9 ].

Willis, as physician, belonged to the Iatrochemical School of medicine which believed that chemistry was the basis of human function. Concerning diabetes, in his Pharmaceutice rationalis, Willis devoted a chapter to the “pissing evil”. He commented on the sweetness of the urine in diabetic patients, coining also the term mellitus[ 10 ]. It was actually a rediscovery, as in the 7 th century BC the Indian physician Sushruta mentioned the sweet urine of the disease but this work apparently was unknown to Willis. So, he was the first European medical writer who mentioned the sweet taste of the urine in diabetes mellitus. It seems that he saw several cases of diabetes mellitus and he believed that it was due to an affection of the blood rather of the kidneys. He attributed it to the eating habits and psychological status “an ill manner of living and chiefly an assiduous and immoderate drinking of cider, beer and sharp wines; sometimes sadness, long grief”. He recognized also diabetic neuropathy in the sufferers describing it as “stinging and other…frequent contractions or convulsion, twinging of the tendons and muscles and other disturbances”[ 9 - 11 ].

Concerning the sweet taste of the urine, he reported a case of “a certain noble earl” who suddenly “became much inclined to excessive pissing… in the space of twenty-four hours, he voided almost a gallon and a half of limpid, clear, and wonderful sweet water, that tasted as if it has been mixed with honey”. Therapeutically he considered beneficial for the disease a “thickening and moderately cooling diet and cordials” and he mentioned that slimy vegetables, rice, white starch may improve patient’s status. He also suggested a milk drink which was distilled with cypress tops and egg whites, two powders (a mixture of gum arabic and gum dragant), rhubarb and cinnamon. Following Willis’ therapeutic advices, patient’s condition improved in a month but immediately after his recovery, he returned to his past dietary habits[ 9 ].

However Willis could not explain “why the urine is wonderfully sweet like sugar or honey”. The explanation was given 100 years later, by another English physician, Matthew Dobson (1732-1784) of Liverpool, who experimentally demonstrated the presence of sugar in urine. He actually boiled urine to dryness and noticed that the residue, a crystalline material, had the taste of brown sugar[ 11 ].

CLAUDE BERNARD’S (1813-1878) BRILLIANT DISCOVERY ON THE GLYCOGENIC ACTION OF THE LIVER

Born to a poor family in Beaujolais region, south of France, Claude Bernard at the age of 19 was apprenticed to an apothecary. His passion for the theatre led him to write two plays La Rose du Rhône and Arthur de Bretagne but soon after arriving to Paris, he was discouraged by the literary critic and politician Saint-Marc Girardin (1801-1873) who counseled him to enroll in medicine. In Medical School of Paris, Bernard was not considered a brilliant student and unwilling to practice medicine, he was appointed assistant to the Professor of Physiology and pioneer of experimental physiology François Magendie (1783-1855). However, Bernard’s research career was very successful. In 1854, he became member of the Academy of Sciences and later on he succeeded Magendie to the chair of experimental physiology at the College de France. The Emperor Napoleon III admired him so much that created two laboratories for him and made him a Senator. Among Bernard’s several discoveries we may cite: the vasomotor innervation, the principle of physiological determinism, the concept of internal secretion, the concept of milieu intérieur or internal environment (meaning the interstitial fluid, and its physiological capacity to ensure protective stability for the tissues and organs), the nature and function of curare, carbon monoxide and other poisons (Figure (Figure2). 2 ). Unfortunately, the only way to understand and discover all these phenomena, promoting our knowledge to physiology, was through animals’ vivisections. This was the reason for his wife to divorce him and join with his children the antivivisection movement, campaigning actively on the issue[ 12 ].

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Portrait of the French physiologist Claude Bernard. (Source: Wellcome Library, London).

Bernard’s contribution in the study of metabolism and diabetes remains leading. In 19 th century, scientists hypothesized on the role of pancreas in the physiopathology of diabetes as they found in the post-mortem examination of the diseased, atrophic or stone filled pancreases. However, as they believed that pancreas was an exocrine organ, they interpreted these post-mortem findings as a chance phenomenon. During that period the French experimental physiologist, Claude Bernard decided to test this hypothesis[ 1 , 12 ].

At the beginning, he falsely believed that “diabetes was a nervous affection of the lungs”. However, during an experiment, he injected grape sugar into the jugular vein of a dog, extracting at the same time blood from the carotid artery. This blood contained a large amount of sugar and he realized that glucose was not destroyed in the lungs, because blood must pass by these organs in order to move from the jugular vein to the carotid artery. He was then fed dogs on a carbohydrate-rich diet, the blood from the hepatic veins and vena cava contained sugar which was not destroyed in the liver and was also present in heart ventricles, so the theory of lungs’ role in diabetes was rejected. In further experiments, Bernard proved that animal blood contains sugar even if it is not supplied by food. Testing the theory that sugar absorbed from food was destroyed when it was passing through tissues, Bernard put dogs in carbohydrate diet and killed them immediately after feeding. To his surprise he observed large amounts of sugar in hepatic veins. The same observation was done in the control group, animals that were fed only by meat. He then moved to the analysis of liver tissue samples and in every liver he examined he found large quantities of glucose which was missing from other organs. He concluded that liver was storing a water insoluble starchy substance that he named glycogen which was converted into sugar or glucose and secreted into the blood. He assumed that it was an excess of this secretion that caused diabetes[ 13 , 14 ].

Moving toward, Bernard demonstrated the connection between the central nervous system and diabetes. Using a needle, he stimulated the floor of the fourth brain ventricle and produced temporary “artificial diabetes” which lasted less than one day. He named this procedure piqûre diabétique and linked for the first time glucose homeostasis and the brain to the pathogenesis of diabetes[ 15 ] (Figure (Figure3 3 ).

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Sites of punctures of 4 th ventricle from Bernard’s book «Leçons sur la Physiologie et la Pathologie du Système Nerveux», 1858. (Source: Wellcome Library, London).

The work of Claude Bernard on glycogenic action of the liver illuminated the pathway of gluconeogenesis and promoted the study of diabetes.

OSKAR MINKOWSKI (1858-1931) AND JOSEPH VON MERING (1849-1908): THE DISCOVERY OF “PANCREATIC DIABETES”

A turning point in the history of diabetes mellitus took place in 1889 after the experiments of Minkowski and von Mering.

In 1886, three years before their first meeting, von Mering discovered that phlorizin, a glucoside, could cause transient glucuresis. In 1889, while von Mering was working in Hoppe Seyler’s Institute at the University of Strasbourg, Minkowski, assistant at that time to the German leading authority on diabetes Professor Bernard Naunyn (1839-1925), he visited the Institute to look at some chemical books of the library. They met accidentally and talked about Lipanin, an oil containing free fatty acids and von Mering used to administrate to patients suffering from digestive disturbances. Minkowski was not in favor of Lipanin intake and then their conversation turned on whether the pancreas had a role in digestion and absorption of fats. As a result of the discussion, the two men decided the same evening to perform a pancreatectomy in a dog in Naunyn’s laboratory. The animal remained alive and was closely observed by Minkowski, as von Mering left urgently to Colmar because of a family issue. Soon after the operation, the dog developed polyuria. Minkowski examined the urine and found that it contained 12% sugar. Initially Minkowski believed that the dog developed diabetes due to the fact that von Mering had treated it for a long time with phlorizin. So he repeated the pancreatectomy in three more dogs which had no sugar in their urine previous to operation and all of them developed glycosuria[ 13 , 16 ].

Furthermore Minkowski implanted a small portion of pancreas subcutaneously, in depancreatized dogs, and observed that hyperglycemia was prevented until the implant was removed or had spontaneously degenerated[ 13 ].

Minkowski and von Mering experiment demonstrated that pancreas was a gland of internal secretion important for the maintenance of glucose homeostasis. They also paved the way for Banting and Best to conduct their experiments and to meet with success.

FREDERICK BANTING (1891-1941), CHARLES BEST (1899-1978), JAMES BERTRAM COLLIP (1892-1965) AND JOHN MACLEOD (1876-1935): THE DISCOVERY OF INSULIN

In 1923 the Nobel Prize in Medicine was awarded to Frederick Banting and John MacLeod for the discovery of insulin. It was actually a story of success that provoked a great scientific conflict.

Frederick Banting was a young Canadian surgeon, who was admitted into the laboratory of the eminent biochemist, interested in diabetes, Professor John Macleod, at the University of Toronto[ 13 ]. In 1920, Moses Barron, physician in Minnesota, published an article on “The relation of the islets of Langerhans to diabetes, with special reference to cases of pancreatic lithiasis[ 17 ] which was mentioning that the continuation of experiments of Minkowski and von Mering could lead to the discovery of a substance capable to control diabetes. Influenced by this article, Banting focused on the study of diabetes[ 13 ]. During that period the distinguished English physiologist Ernest Starling (1886-1927) was mentioning: “We don’t know yet how the pancreas affects sugar production or utilization in the same animal. It is generally assumed that it secretes into the bloodstream a hormone which may pass to the tissues and enable them to utilize sugar or pass to the liver and inhibit the sugar production of this organ… but we have been unable to imitate the action of the pancreas still in vascular connection with the body, by injection or administration of the extracts of this organ”[ 18 ].

On 16 May 1921, Banting started to collaborate with Charles Best, a young medical student. Experimenting in dogs they initially ligate the pancreatic ducts, achieving atrophy of the exocrine region and almost ten weeks later they removed dog’s degenerated pancreas. They crushed the atrophied pancreatic glands in a cool mortar and froze it in salt water. Then the mass was ground down and added to 100 mL of physiological salt. Afterwards, they administrated 5 mL of this extract intravenously to a depangreatized dog. Within 2 h its blood sugar had considerably dropped. They repeated several times the experiment with other diabetic dogs, gaining similar results and they experimented also with fetal calf pancreas using different ways of administration such as subcutaneous and rectal[ 19 , 20 ] (Figure (Figure4 4 ).

An external file that holds a picture, illustration, etc.
Object name is WJD-7-1-g004.jpg

The Nobel laureate Frederick Banting in his laboratory with a dog. (Source: Wellcome Library, London).

At the end of 1921 the skilled chemist James Collip joined the team and developed a better extraction and purification technique. Obtained substance was initially named by the team insletin and later on by MacLeod insulin[ 13 ].

The next step was to test insulin in humans. So on 11 January 1922, insulin was administrated to Leonard Thompson a 14-year-old boy treated for diabetes in Toronto Hospital[ 13 ]. It’s worth mentioning that after the introduction of Apollinaire Bouchardat’s (1806-1886) pioneering dietary treatment for diabetes, physicians repeated in several generations of diabetics his motto: “mangez le moins possible” (eat as little as possible)[ 21 , 22 ]. Thomson was also following a strict fasting diet proposed by Frederick Madison Allen (1879-1964) and he was in critical state. He received 15 mL of insulin, injected in his buttock but he developed abscesses at the injection site and became even sicker. Collip further improved the quality of insulin and on January 23, Thompson received a second injection. The results were excellent. His blood glucose from 520 mg/dL fell to 120 mg/dL in 24 h and urinary ketones disappeared. Thompson continued the treatment with insulin and lived another 13 years. He died of pneumonia at 27 years old[ 13 ]. Similar is the story of Elizabeth Hughes Gossett (1907-1981). Daughter of the United States politician Charles Evans Hughes, Elisabeth was diagnosed with diabetes at age 11. Initially she was also treated by Allen and in August 1922 began the use of insulin. She survived, graduated from College, got married, had three children and died suddenly of a heart attack at 74 years old[ 23 ].

The pioneering work of Banting and Best saved millions of lives and diabetics started to live a normal life. Lilly Pharmaceutical Company collaborated with the two scientists and in 1923 introduced Iletin, the world’s first commercially available insulin product[ 13 ].

However in 1923 the Nobel Committee decided to award Banting and MacLeod for insulin’s discovery. Banting became furious as he believed that he should share the prize with Best instead of MacLeod and he decided to share with Best his cash award. In his turn, MacLeod shared also his award with Collip[ 13 ].

Another black spot in the history of insulin discovery was also the discovery of pancreatin, an extract of bovine pancreas discovered by the Romanian Professor of Physiology Nicolae Constantin Paulescu (1869-1931) in 1916, published a few years later because of the war in 1921 and patented in April 1922. Even if Paulescu was the first to provide a detailed demonstration of the antidiabetic and antiketogenic effect of a pancreatic extract, pancreatine was not used in humans and passed over silently[ 24 ].

A crucial step in the history of diabetes has been completed. Over the next years insulin purification methods improved and new insulin formulations were developed such as Protamine–zinc insulin, a long-acting insulin in 1930s, neutral protamine Hagedorn in 1940s and Lente series in 1950s[ 13 ].

For more than 3000 years physicians quested the causes and treatment of diabetes mellitus (Figure (Figure5). 5 ). However, an important progress has been made over the last two centuries thanks to the development of chemistry, physics and pharmacology. Over the next years scientists continued to make significant discoveries: The structure of insulin was delineated in 1955 by the Nobel laureate Fred Sanger (1918-2013); in 1967 proinsulin was discovered by Donald Steiner (1930-2014) and with his colleagues he produced the radioimmunoassay for C-peptide which is used today to measure endogenous insulin production; in the same year, the first pancreas transplant in a human was performed by William Kelly, Richard Lillehei (1927-1981) and colleagues at the University of Minnesota; in 1972 the U100 insulin was introduced to promote better accuracy in administration; ten years later, in 1982, recombinant human insulin became available and in early 1990’s insulin pen delivery devices become popular following by the discoveries of short (1996) and long (2001) acting insulin analogues[ 1 ].

An external file that holds a picture, illustration, etc.
Object name is WJD-7-1-g005.jpg

Timeline table presenting the main contributors in the history of diabetes mellitus.

Since biotechnology helps medicine to progress, nobody knows what the future will bring. We are sure of just one thing: History of diabetes is being still written.

Conflict-of-interest statement: There is no conflict of interest associated with any of the senior author or other coauthors contributed their efforts in this manuscript.

Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

Peer-review started: August 13, 2015

First decision: September 17, 2015

Article in press: December 18, 2015

P- Reviewer: Charoenphandhu N, Hssan M, Masaki T, Tarantino G S- Editor: Gong XM L- Editor: A E- Editor: Wu HL

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Published: 28 August 2024

Exposure to gestational diabetes mellitus in utero impacts hippocampal functional connectivity in response to food cues in children

Sixiu Zhao 1 , 2 ,
Lorenzo Semeia ORCID: orcid.org/0000-0002-2079-7147 1 , 2 ,
Ralf Veit ORCID: orcid.org/0000-0001-9860-642X 1 , 2 ,
Shan Luo 3 , 4 , 5 , 6 ,
Brendan C. Angelo ORCID: orcid.org/0000-0003-3558-2840 3 , 4 ,
Ting Chow 7 ,
Andreas L. Birkenfeld ORCID: orcid.org/0000-0003-1407-9023 1 , 2 , 8 ,
Hubert Preissl ORCID: orcid.org/0000-0002-8859-4661 1 , 2 , 8 , 9 ,
Anny H. Xiang 7 na1 ,
Kathleen A. Page 3 , 4 , 10 na1 &
Stephanie Kullmann ORCID: orcid.org/0000-0001-9951-923X 1 , 2 , 8 na1

International Journal of Obesity ( 2024 ) Cite this article

Metrics details

Risk factors

Intrauterine exposure to gestational diabetes mellitus (GDM) increases the risk of obesity in the offspring, but little is known about the underlying neural mechanisms. The hippocampus is crucial for food intake regulation and is vulnerable to the effects of obesity. The purpose of the study was to investigate whether GDM exposure affects hippocampal functional connectivity during exposure to food cues using functional magnetic resonance imaging (fMRI).

Participants were 90 children age 7–11 years (53 females) who underwent an fMRI-based visual food cue task in the fasted state. Hippocampal functional connectivity (FC) was examined using generalized psychophysiological interaction in response to food versus non-food cues. Hippocampal FC was compared between children with and without GDM exposure, while controlling for possible confounding effects of age, sex and waist-to-hip ratio. In addition, the influence of childhood and maternal obesity were investigated using multiple regression models.

While viewing high caloric food cues compared to non-food cure, children with GDM exposure exhibited higher hippocampal FC to the insula and striatum (i.e., putamen, pallidum and nucleus accumbens) compared to unexposed children. With increasing BMI, children with GDM exposure had lower hippocampal FC to the somatosensory cortex (i.e., postcentral gyrus).

Conclusions

Intrauterine exposure to GDM was associated with higher food-cue induced hippocampal FC especially to reward processing regions. Future studies with longitudinal measurements are needed to clarify whether altered hippocampal FC may raise the risk of the development of metabolic diseases later in life.

Food craving-like episodes during pregnancy are mediated by accumbal dopaminergic circuits

Maternal pre-pregnancy BMI associates with neonate local and distal functional connectivity of the left superior frontal gyrus

Genetically-predicted prefrontal DRD4 gene expression modulates differentiated brain responses to food cues in adolescent girls and boys

Introduction.

Gestational diabetes mellitus (GDM) is traditionally defined as glucose intolerance with first-time diagnosis during pregnancy [ 1 ]. It develops in approximately 10% of pregnancies, making it one of the prevalent complications during gestation [ 2 ]. Intrauterine exposure to GDM increases the risk of developing obesity in offspring [ 2 ]. It is not yet clear which factors might drive these conditions later in life, but early neurodevelopmental processes appear sensitive to intrauterine hyperglycemia, hyperinsulinemia and neuroinflammation caused by maternal overnutrition, including hyperglycemia [ 3 , 4 ]. Furthermore, intrauterine exposure to GDM may lead to increased food intake, which is regulated by multiple brain regions, as the hypothalamus, striatum, insula, hippocampus etc. [ 5 , 6 ]. Significantly, functional imaging data demonstrated that food cue reactivity in these brain regions can predict weight gain including in children [ 7 , 8 ].

Children exposed to GDM display higher food cue reactivity in the orbitofrontal cortex [ 9 ], fail to inhibit hypothalamic activity after glucose ingestion [ 10 ] and exhibit hypothalamic inflammation [ 11 ]. Moreover, data from animals and humans suggests the development of the hippocampus is sensitive to adverse in utero environmental exposures (e.g., GDM) [ 4 , 12 , 13 , 14 , 15 ]. In animals, intrauterine exposure to diabetes caused decreased neuronal density and reduced synaptic integrity in the hippocampus [ 4 , 12 , 13 ]. GDM exposure in utero and maternal obesity also associated with reduced thickness and volume in the hippocampus in children [ 14 , 15 ].

The hippocampus is known for its major role in learning and memory and is believed to influence food intake by integrating learned experiences with interoceptive signals (for review, see [ 16 ]). Animal models and behavioral studies in humans suggest that even a brief exposure to a diet rich in dietary fat and sugar can impair hippocampal-dependent learning and memory [ 17 , 18 ]. Behavioral data in healthy humans showed that influencing meal memory can reduce or enhance later food intake [ 19 , 20 ]. Furthermore, amnesic patients fail to interpret interoceptive signals related to hunger and satiety [ 21 ]. Using fMRI, the hippocampus has been shown to be responsive to the ingestion of sugar, visual food cues, and postprandial hormones in healthy adults [ 16 , 22 , 23 ]. Hence, hippocampal dysfunctions may impair the ability to retrieve memories of meals, detect interoceptive signals, which may lead to overeating (for reviews, see [ 24 ]).

However, there is currently no available research on the hippocampus functional network in response to visual food cues in children with GDM exposure, who exhibit higher risk of developing obesity [ 2 ]. Thus, the current study investigates the relation between GDM exposure and functional connectivity (FC) of the hippocampus in children.

We examined task-based FC of the bilateral hippocampus in children with and without GDM exposure using generalized psychophysiological interaction (gPPI) in response to visual food cues (food minus non-food) in the BrainChild Cohort [ 9 , 25 ]. Prior studies [ 26 , 27 , 28 , 29 , 30 , 31 , 32 ] indicate higher food-cue-induced neural reactivity of reward regions and alterations in hippocampal FC in both children and adults with obesity. Hence, we hypothesized that hippocampal FC is higher to reward-related regions during food cue presentation in children with GDM exposure when compared to children without exposure. In addition, we explored the relationship between adiposity measures of children and mothers and hippocampal FC. Given prior evidence suggesting that GDM has distinct effects on the left and right hippocampus in children [ 14 ], we conducted separate exploratory analyses on the FC of the left and right hippocampus.

Participants

Participants included 112 children from the larger BrainChild study assessing the impact of exposure to GDM in utero on neural and endocrine systems underlying risk for obesity and diabetes [ 10 ]. The BrainChild study included typically developing children aged 7–11 years recruited from Kaiser Permanente Southern California (KPSC) [ 9 , 25 ]. Inclusion criteria included KPSC’s electronic medical records, which documented maternal GDM or normal glucose tolerance during pregnancy, uncomplicated singleton birth, and children with no history of medical/psychiatric disorders or taking medicines affecting metabolism. Twenty-two participants were excluded due to excessive movement, image artifacts, or the presence of brain lesions. The final analyses included a total of 90 participants. Based on the sample size of N = 90 and the detected effect size of 0.8 (primary analysis: GDM versus Non-GDM), we achieved a statistical power of 0.96 at an alpha level of 0.05.

Ethics approval and consent to participate

The institutional review board at both KPSC (# 10282) and University of Southern California (USC) (# HS-14-00034) approved this study. This study was in accordance with the Declaration of Helsinki. Parents and children were provided with written informed consent and informed child assent prior to the study.

Maternal GDM exposure

GDM during pregnancy was determined based on one of the following laboratory plasma glucose values during pregnancy: (1) plasma glucose values ≥ 200 mg/dL from a 50 g 1-hr glucose challenge test, (2) at least two plasma glucose values meeting or exceeding the following values on either the 75 g 2-hrs or 100 g 3-hrs oral glucose tolerance test: fasting, 95 mg/dL; 1 h, 180 mg/dL; 2 h, 155 mg/dL; and 3 h, 140 mg/dL [ 33 ].

Study procedures

The data for this study were collected over two visits conducted after a 12-h overnight fast. The first visit consisted of metabolic phenotyping, including assessments of anthropometric measures. The second visit was a neuroimaging visit, including functional magnetic resonance imaging (fMRI) measurement during a food cue task after the overnight fast.

First visit: anthropometric measurement

During the first visit, anthropometric data, including height, weight, waist and hip circumferences of both the mother and child, tanner stage of child were collected at the Clinical Research Unit of the USC Diabetes and Obesity Research Institute as previously reported [ 10 ]. Specific to children, BMI z -scores (BMI-z) were calculated using the Center for Disease Control (CDC) guidelines [ 34 ].

Second visit: MRI measurement

After the overnight fast, fMRI measurements of the children were performed at the USC Dana and David Dornsife Neuroimaging Center. Children first underwent training on a mock scanner, after which they were imaged in a 3 T MRI scanner. All children were scanned between 8 and 10 am following 12-h of overnight fasting. They completed a visual food cue task in the scanner (For more details, see [ 25 ]). Briefly, children were presented high-calorie food (e.g., ice cream) and non-food (e.g., pencils) pictures and instructed to watch the pictures attentively. The stimuli were selected based on pilot studies of children’s ratings of familiarity and appeal of the food and non-food items. And, the food and non-food tems were also selected to include similar characteristics such as contrast, salience, color, shape and complexity. A total of 12 blocks of stimuli were included, comprising an equal distribution of 50% food images and 50% non-food images. Each block included three images and each image was displayed for 4 s with 1 s consistent inter-stimulus interval between pictures. The sequence of the blocks was randomized. The food cue task lasted 196 s in total. The task was designed to be particularly efficient for differential effects (food versus non-food) with a short stimulus onset asynchrony and not for common task effects or task effects versus implicit baseline.

Image acquisition and preprocessing

The imaging was conducted on a Siemens MAGNETOM Prismafit 3 T MRI scanner with a 20-channel head coil. Functional images were obtained using a 2D single-shot gradient echo planar imaging sequence with the following parameters: repetition time (TR) = 2000 ms; echo time = 25 ms; flip angle = 85°; voxel resolution 3.4 × 3.4 × 4 mm 3 ; 32 axial slices. A high-resolution structural image was also acquired at 1 × 1 × 1 mm 3 resolution. For more details, see publication [ 25 ].

The preprocessing of the fMRI data was performed using SPM12 ( http://www.fil.ion.ucl.ac.uk/spm ). Slice timing and realignment were performed for each fMRI time series. Movement criteria was movement > 2° or 2 mm in any direction, or mean framewise displacement of more than 0.3 mm. The resulting mean functional image and the structural image was coregistered. Unified segmentation was performed to the anatomical image and normalization parameters were estimated. Then, these parameters were applied to the functional images and normalized into Montreal Neurological Institute (MNI) space, using the same method applied in our previous paper by Luo et al. [ 25 ] and in other studies [ 35 , 36 ] with children within the same age range. The data were then smoothed with an 8 mm field-width half-maximum (FWHM) Gaussian kernel. Physiological noise signals in the white matter and cerebrospinal fluid were extracted using Principal Component Analysis (PCA) using the PhysIO toolbox [ 37 ].

Region of interest (ROI) definition

To specifically investigate the effect of GDM on the hippocampus FC, we used an anatomical ROI-based approach. Left, right and bilateral ROIs of the hippocampus were created using the AAL atlas 3 (AAL3, https://www.oxcns.org ) (Fig. 1 ).

Hippo, Hippocampus; L, left; R, right.

Generalized psychophysiological interaction (first level analysis)

For each participant, the brain response to high-calorie food and non-food images was convolved with a canonical hemodynamic response function, and then added to the General Linear Model (GLM). The six motion parameters, and three components each of the white matter and cerebrospinal fluid signals extracted by PCA were also included in the GLM as confounds. High-pass filtering was applied using bandwidth = 0.0078 (1/128) Hz.

Task-based FC between anatomical seed region of the hippocampus (i.e., bilateral hippocampus) and all other brain voxels was assessed using a generalized psychophysiological interaction (gPPI) approach ( https://www.nitrc.org/projects/gppi version 13.1). In an exploratory analysis, FC was assessed for the right and left hippocampus separately in the same way.

First, the time series from the seed region were extracted. Second, the PPI interaction terms were generated for food and non-food stimuli according to the time series. Finally, FC of the seed region was computed for food and non-food stimuli for each participant.

Statistical analyses

Hippocampal functional connectivity in response to food minus non-food cues.

To evaluate intrauterine exposure to GDM on food-cue induced hippocampal FC, the gPPI contrast maps of food minus non-food were entered into a second-level two-sample t-test model with the GDM exposure (GDM vs. Non-GDM) as grouping factor. Age and sex were included in the model as covariates due to their potential effects on hippocampal structure and function [ 14 , 38 ]. Waist-to-hip ratio (WHR) rather than BMI has been reported to be positively correlated with hippocampus activity in response to food cues [ 39 ] and we recently reported higher WHR in children with GDM exposure [ 9 ]. Therefore, WHR was adjusted for the possible impact of adiposity.

The statistical parametric maps were thresholded using an uncorrected threshold of p < 0.001 and a cluster-level family-wise error (FWE) corrected threshold of p < 0.05. In addition, small volume correction (SVC) was performed for the insula and striatum (caudate, putamen, nucleus accumbens, pallidum), based on their activation in response to food reward processing and influenced by obesity in children and adolescents [ 40 , 41 ]. The striatal mask and the insular mask were generated based on AAL3 ( https://www.oxcns.org ) and the wfu pick atlas ( https://www.nitrc.org/projects/wfu_pickatlas/ ). Multiple comparison was implemented for two masks using corrected threshold p < 0.025.

Correlation between task-based hippocampal functional connectivity and obesity measures of children and mothers

To explore the effect of children’s obesity and maternal adiposity on bilateral hippocampal FC in children, a second-level multiple regression model was created using SPM 12 at the whole-brain level. This analysis was performed separately for children with and without GDM exposure. These models included the gPPI food minus non-food contrast as intercept, with WHR, BMI z -score, maternal current BMI or maternal prepregnancy BMI as the regressors of interest, adjusted for age and sex. An uncorrected threshold of p < 0.001 and a cluster-level FWE corrected threshold of p < 0.05 were used. The correlations were assessed for the right and left hippocampus separately in the same way.

Demographics

The demographics of the 90 participants included in this study are shown in Table 1 (ages 7–11 years, 53 females, 50 GDM exposed), and 89% of children were in Tanner Stage 1. There were no significant differences in children’s age, sex, BMI z -score, or maternal current BMI or maternal prepregnancy BMI among GDM exposed vs. unexposed groups ( p > 0.05, Table 1 ). There was a trend towards a higher WHR for children exposed to GDM than unexposed (t [88] = 1.97, p = 0.052, Table 1 ).

We observed higher FC in children with GDM exposure compared to children without GDM exposure between the bilateral hippocampus and the left insula ( p FWE = 0.037) and left putamen, which extended to the left pallidum ( p FWE = 0.019, SVC) (Table 2 , Fig. 2 ).

In an exploratory analysis, FC was assessed for the right and left hippocampus separately. In children with GDM exposure compared to children without exposure, we observed higher FC between the left hippocampus and the right putamen ( p FWE = 0.007), left putamen ( p FWE = 0.017, SVC), right insula ( p FWE = 0.017), left insula ( p FWE = 0.011, SVC), and left nucleus accumbens (NAcc, p FWE = 0.013, SVC) (Table 2 , Fig. 2 ). The cluster of the right putamen extended to the right insula. The cluster of the left putamen extended to the left pallidum. No group differences were found for the right hippocampus.

a Children with GDM exposure showed higher FC between bilateral hippocampus and left insula, left putamen/pallidum. b Children with GDM exposure showed higher FC between left hippocampus and the bilateral putamen, insula, and left NAcc. The cluster of the right putamen extended to the right insula. The cluster of left putamen extended to the left pallidum. Color map corresponds to T values ( p < 0.001 uncorrected for display) overlaid on the normalized average T1 weighted image of the children. Hippo hippocampus, FC functional connectivity, GDM gestational diabetes mellitus, NAcc nucleus accumbens, L left, R right.

Association between task-based hippocampal functional connectivity and obesity measures of children and mothers

No significant correlation was observed between the FC of the bilateral hippocampus and WHR, BMI z -score, maternal current or maternal prepregnancy BMI in both the GDM and Non-GDM groups (all p FWE-corrected > 0.05).

Further analysis of the FC of the left or right hippocampus separately revealed significant correlations. In the GDM group, there was a negative correlation between BMI z -score and the FC of the left hippocampus and the right postcentral gyrus (peak-voxel (MNI) x: 57, y: −34, z: 26); r = −0.607; p FWE-corrected < 0.001) (Fig. 3 ). In the Non-GDM group, a positive correlation was found between the maternal current BMI and the FC of the left hippocampus to the right superior frontal gyrus (peak-voxel (MNI) x: 18, y: 59, z: −1); r = 0.574; p FWE-corrected = 0.001).

a Children with GDM exposure showed lower FC between the left hippocampus and the right postcentral gyrus with higher BMI z -score. Color map corresponds to T values (Multiple regression analysis with BMI z -score; p < 0.001 uncorrected for display) overlaid on the normalized average T1 weighted image of the children. b Negative correlation between BMI z -score and the extracted cluster of the FC of the left hippocampus and the right postcentral gyrus in the GDM group. Error bars indicate 95% confidence interval. Hippo hippocampus, FC functional connectivity, GDM gestational diabetes mellitus, L left, R right.

The current study investigated the relationship between intrauterine GDM exposure and food cue induced hippocampal functional connectivity in children aged 7–11 years in the fasted state. Consistent with our hypothesis, children with GDM exposure compared to unexposed showed higher hippocampal FC to reward processing regions (i.e., putamen, pallidum, NAcc and insular cortex) and lower hippocampal FC to the somatosensory cortex with increasing BMI.

We observed higher functional coupling between hippocampus and striatal regions and insula in children with intrauterine GDM exposure compared to children without exposure, primarily driven by the left hippocampus. A previous structural MRI report found reduced left hippocampal thickness in children with GDM exposure compared to unexposed children [ 14 ]. Therefore, GDM may affect both the structure and function of the hippocampus.

Hippocampal neurons interact with other neurons in the mesolimbic system receiving dopamine projections to communicate rewarding properties of environmental stimuli [ 16 , 42 ]. As potent rewards, palatable foods can trigger associations with reward and motivational behaviors that potentially could lead to overeating and, eventually, weight gain [ 42 ]. These food cues tend to evoke heightened memories and mental simulations of consumption in children [ 43 ]. Moreover, a meta-analysis indicated that the hippocampus-striatum connection may play a role in craving and the formation of habits associated with obesity [ 44 ]. Concomitantly, higher activation in the striatum and insula in response to food images were observed in children and adolescents with obesity compared to their healthy-weight peers [ 40 , 41 , 45 ]. In the resting state, higher striatal and insular network FC was also linked to eating in the absence of hunger, food craving, disinhibited eating, weight gain and obesity in both children and adults [ 46 , 47 , 48 , 49 ]. In the current study, no significant influence of WHR or BMI was identified on these hippocampal connections in children. However, BMI negatively correlated with the left hippocampus to the somatosensory cortex FC in children exposed to GDM, aligning with resting-state studies in children with obesity [ 50 ]. The oral somatosensory cortex is known to sense fat and food texture [ 51 ] and children and adolescents with obesity show greater activation in the somatosensory cortex to food [ 8 , 52 ]. The higher preference for high-fat foods in children is a predictor of future weight gain [ 53 ]. Nonetheless, it is yet unknown whether altered hippocampal to somatosensory connectivity patterns in children with GDM exposure predict the development of obesity later in life.

Our study points to a distinct effect of intrauterine GDM exposure on the hippocampal network primarily to reward processing regions, rather than obesity itself at this young age. These results align with animal studies [ 4 , 12 , 13 ] and provide evidence to support the hypothesis that prenatal exposure to diabetes might result in changes in brain pathways. These changes, in turn, may contribute to the increased risk of weight gain and obesity in affected children at a later age. Interestingly, previous studies suggest that hyperactivity in the brain’s reward system might be a susceptibility factor for weight gain [ 8 , 54 ]. Similarly, our previous study showed that children exposed to GDM had higher daily energy intake [ 9 ]. Moreover, parental obesity has been related to greater striatum and insula activation in response to food rewards and higher ad libitum intake even in adolescents of healthy-weight [ 8 , 55 ]. In the current study, we also found higher food-cue induced hippocampal FC to the frontal cortex in children of mothers with higher BMI. Although this connection in relation to maternal obesity has not yet been fully investigated, higher FC between temporal and frontal regions has been reported in adolescent obesity [ 56 ]. Future studies with longitudinal measurements are necessary to evaluate whether hippocampal changes in FC result in weight gain and raise the risk of developing obesity later in life.

Our study includes some limitations. Given the limited size of our sample, each subgroup, based on GDM exposure, included a relatively small number of subjects. In addition, food intake and behavioral assessments were not assessed, and future studies are necessary to provide a more detailed understanding how the observed functional alterations in the hippocampus are related to cognitive and metabolic processes. Moreover, longitudinal data are needed to examine the association between functional alterations in the hippocampus and future weight gain in children.

Our study suggests that intrauterine exposure to GDM alters hippocampal food cue processing network in children. During palatable food picture presentation, children with GDM exposure exhibited higher hippocampal connectivity specifically to reward processing regions and lower hippocampal connectivity, with increasing BMI, to the somatosensory cortex. These alterations may be associated with a potential risk for future weight gain. Longitudinal research is required to determine if altered hippocampal functional connectivity during exposure to food cues leads to future weight gain and a higher likelihood of metabolic disorders, including obesity.

Data availability

Data is available upon reasonable request from KAP.

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Acknowledgements

The authors would like to thank the volunteers who participated in this study.

This work was supported by an American Diabetes Association Pathway Accelerator Award (#1-14-ACE-36) (principal investigator: KAP) and in part by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health, grants R03DK103083 (principal investigator: KAP), R01DK116858 (principal investigator: KAP, AHX), and K01DK115638 (principal investigator: SL). A Research Electronic Data Capture, database was used for this study, which is supported by the Southern California Clinical and Translational Science Institute (SC CTSI) through U.S. Department of Health and Human Services (DHHS) grant UL1-TR-001855. SXZ is funded by China Scholarship Council (CSC). ALB, HP, RV and SK were partially funded by a grant (01GI0925) from the Federal Ministry of Education and Research (BMBF) to the German Center for Diabetes Research (DZD e.V.). Open Access funding enabled and organized by Projekt DEAL.

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These authors contributed equally: Anny H. Xiang, Kathleen A. Page, Stephanie Kullmann.

Authors and Affiliations

Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany

Sixiu Zhao, Lorenzo Semeia, Ralf Veit, Andreas L. Birkenfeld, Hubert Preissl & Stephanie Kullmann

German Center for Diabetes Research (DZD), Tübingen, Germany

Division of Endocrinology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

Shan Luo, Brendan C. Angelo & Kathleen A. Page

Diabetes and Obesity Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

Department of Psychology, University of Southern California, Los Angeles, CA, USA

Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA

Ting Chow & Anny H. Xiang

Department of Internal Medicine, Division of Diabetology, Endocrinology and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany

Andreas L. Birkenfeld, Hubert Preissl & Stephanie Kullmann

Department of Pharmacy and Biochemistry, Eberhard Karls University Tübingen, Tübingen, Germany

Hubert Preissl

Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA

Kathleen A. Page

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Contributions

SXZ and SK conceptualized and conducted the analysis, drafted the manuscript; RV and LS supported the analysis and discussed the results; HP, AHX, KAP and SK provided critical review and revisions to the manuscript; AHX and KAP conceptualized the original study, have full access to all data in the study and take responsibility for the integrity of the data; SL, BCA, and TC managed and coordinated the study execution; ALB, HP, SK supervised the work. All authors discussed the results and implications, reviewed and edited the manuscript and approved its final version. KAP, AHX and SL provided funding for this study.

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Correspondence to Stephanie Kullmann .

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Zhao, S., Semeia, L., Veit, R. et al. Exposure to gestational diabetes mellitus in utero impacts hippocampal functional connectivity in response to food cues in children. Int J Obes (2024). https://doi.org/10.1038/s41366-024-01608-1

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DOI : https://doi.org/10.1038/s41366-024-01608-1

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