Comment on Stone et al. Atypical Diabetes: What Have We Learned and What Does the Future Hold? Diabetes Care 2024;47:770–781

We thank Stone et al. (1) for their comprehensive review of atypical diabetes, across both pediatric and adult populations.


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About the Artist: Saul Krotki

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About the Editor: Stephanie L. Fitzpatrick, PhD: Behavioral and Social Care Interventions for Chronic Disease Prevention and Management

Stephanie Fitzpatrick knew she wanted to help people. Her mother was a phlebotomist, and as a girl growing up in Louisville, Kentucky, Fitzpatrick used to shadow her during her hospital shift. “I saw how gentle she was with her patients,” she says. “Explaining what she was doing before she drew blood, checking in on them after—my mom had an ability to make people feel at ease during a stressful time.” Fitzpatrick wanted to help people, and as a kid, a career in medicine seemed like the best way to do that. She decided to become a medical doctor.


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Effect of SARS-CoV-2 Infection on Incident Diabetes by Viral Variant: Findings From the National COVID Cohort Collaborative (N3C)

OBJECTIVEThe coronavirus 2019 (COVID-19) pandemic has evolved over time by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, disease severity, treatment, and prevention. There is evidence of an elevated risk of incident diabetes after COVID-19; our objective was to evaluate whether this association is consistent across time and with contemporary viral variants.RESEARCH DESIGN AND METHODSWe conducted a retrospective cohort study using National COVID Cohort Collaborative (N3C) data to evaluate incident diabetes risk among COVID-positive adults compared with COVID-negative patients or control patients with acute respiratory illness (ARI). Cohorts were weighted on demographics, data site, and Charlson comorbidity index score. The primary outcome was the cumulative incidence ratio (CIR) of incident diabetes for each viral variant era.RESULTSRisk of incident diabetes 1 year after COVID-19 was increased for patients with any viral variant compared with COVID-negative control patients (ancestral CIR 1.16 [95% CI 1.12–1.21]; Alpha CIR 1.14 [95% CI 1.11–1.17]; Delta CIR 1.17 [95% CI 1.13–1.21]; Omicron CIR 1.13 [95% CI 1.10–1.17]) and control patients with ARI (ancestral CIR 1.17 [95% CI 1.11–1.22]; Alpha CIR 1.14 [95% CI 1.09–1.19]; Delta CIR 1.18 [95% CI 1.11–1.26]; Omicron CIR 1.20 [95% CI 1.13–1.27]). There was latency in the timing of incident diabetes risk with the Omicron variant; in contrast with other variants, the risk presented after 180 days.CONCLUSIONSIncident diabetes risk after COVID-19 was similar across different SARS-CoV-2 variants. However, there was greater latency in diabetes onset in the Omicron variant era.


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Relationship Between Sensor-Detected Hypoglycemia and Patient-Reported Hypoglycemia in People With Type 1 and Insulin-Treated Type 2 Diabetes: The Hypo-METRICS Study

OBJECTIVEUse of continuous glucose monitoring (CGM) has led to greater detection of hypoglycemia; the clinical significance of this is not fully understood. The Hypoglycaemia–Measurement, Thresholds and Impacts (Hypo-METRICS) study was designed to investigate the rates and duration of sensor-detected hypoglycemia (SDH) and their relationship with person-reported hypoglycemia (PRH) in people living with type 1 diabetes (T1D) and insulin-treated type 2 diabetes (T2D) with prior experience of hypoglycemia.RESEARCH DESIGN AND METHODSWe recruited 276 participants with T1D and 321 with T2D who wore a blinded CGM and recorded PRH in the Hypo-METRICS app over 10 weeks. Rates of SDH


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History of the Diabetes Control and Complications Trial and Its Follow-up Epidemiology of Diabetes Interventions and Complications Study: Studies That Changed the Treatment of Type 1 Diabetes

NIH


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The Association Between Depressive Symptoms, Access to Diabetes Care, and Glycemic Control in Five Middle-Income Countries

OBJECTIVEThe relationship between depression, diabetes, and access to diabetes care is established in high-income countries (HICs) but not in middle-income countries (MICs), where contexts and health systems differ and may impact this relationship. In this study, we investigate access to diabetes care for individuals with and without depressive symptoms in MICs.RESEARCH DESIGN AND METHODSWe analyzed pooled data from nationally representative household surveys across Brazil, Chile, China, Indonesia, and Mexico. Validated survey tools Center for Epidemiologic Studies Depression Scale Revised, Composite International Diagnostic Interview, Short Form, and Patient Health Questionnaire identified participants with depressive symptoms. Diabetes, defined per World Health Organization Package of Essential Noncommunicable Disease Interventions guidelines, included self-reported medication use and biochemical data. The primary focus was on tracking diabetes care progression through the stages of diagnosis, treatment, and glycemic control. Descriptive and multivariable logistic regression analyses, accounting for gender, age, education, and BMI, examined diabetes prevalence and care continuum progression.RESULTSThe pooled sample included 18,301 individuals aged 50 years and above; 3,309 (18.1%) had diabetes, and 3,934 (21.5%) exhibited depressive symptoms. Diabetes prevalence was insignificantly higher among those with depressive symptoms (28.9%) compared with those without (23.8%, P = 0.071). Co-occurrence of diabetes and depression was associated with increased odds of diabetes detection (odds ratio [OR] 1.398, P < 0.001) and treatment (OR 1.344, P < 0.001), but not with higher odds of glycemic control (OR 0.913, P = 0.377).CONCLUSIONSIn MICs, individuals aged 50 years and older with diabetes and depression showed heightened diabetes identification and treatment probabilities, unlike patterns seen in HICs. This underscores the unique interplay of these conditions in different income settings.


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Excess Risk of Injury in Individuals With Type 1 or Type 2 Diabetes Compared With the General Population

OBJECTIVETo estimate the relative risk (RR) and excess hospitalization rate for injury in individuals with diabetes compared with the general population.RESEARCH DESIGN AND METHODSData were obtained from the Australian National Diabetes Services Scheme, hospitalization data sets, the Australian Pharmaceutical Benefits Scheme, the National Death Index, and the census spanning from 2011 to 2017. Hospitalizations for injury were coded as head and neck, lower-extremity, upper-extremity, or abdominal and thoracic injury; burns; or other injury. Poisson regression was used to estimate the age- and sex-adjusted RR of hospitalization for injury.RESULTSThe total number of hospitalizations for any injury was 117,705 in people with diabetes and 3,463,173 in the general population. Compared with that in the general population, an elevated adjusted risk of admission was observed for any injury (RR 1.22; 95% CI 1.21, 1.22), head and neck (1.28; 1.26, 1.30), lower extremity (1.24; 1.23, 1.26), abdominal and thoracic (1.29; 1.27, 1.30), upper extremity (1.03; 1.02, 1.05), burns (1.52; 1.44, 1.61), and other injury (1.37; 1.33, 1.40). The adjusted RR of any injury was 1.62 (1.58, 1.66) in individuals with type 1 diabetes, 1.65 (1.63, 1.66) in those with type 2 diabetes who were taking insulin, and 1.07 (1.06, 1.08) in individuals with type 2 diabetes not using insulin. Falls were the primary cause of injury in individuals with diabetes.CONCLUSIONSIndividuals with diabetes, especially those using insulin, had a higher risk of hospitalization for injury compared with the general population.


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Receipt of Diabetes Specialty Care and Management Services by Older Adults With Diabetes in the U.S., 2015–2019: An Analysis of Medicare Fee-for-Service Claims

OBJECTIVEWe characterized the receipt of diabetes specialty care and management services among older adults with diabetes.RESEARCH DESIGN AND METHODSUsing a 20% random sample of fee-for-service Medicare beneficiaries aged ≥65 years, we analyzed cohorts of type 1 diabetes (T1D) or type 2 diabetes (T2D) with history of severe hypoglycemia (HoH), and all other T2D annually from 2015 to 2019. Outcomes were receipt of office-based endocrinology care, diabetes education, outpatient diabetes health services, excluding those provided in primary care, and any of the aforementioned services.RESULTSIn the T1D cohort, receipt of endocrinology care and any service increased from 25.9% and 29.2% in 2015 to 32.7% and 37.4% in 2019, respectively. In the T2D with HoH cohort, receipt of endocrinology care and any service was 13.9% and 16.4% in 2015, with minimal increases. Age, race/ethnicity, residential setting, and income were associated with receiving care.CONCLUSIONSThese findings suggest that many older adults may not receive specialty diabetes care and underscore health disparities.


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Hemoglobin A 1c Trajectories During Pregnancy and Adverse Outcomes in Women With Type 2 Diabetes: A Danish National Population-Based Cohort Study

OBJECTIVETo identify and characterize groups of pregnant women with type 2 diabetes with distinct hemoglobin A1c (HbA1c) trajectories across gestation and to examine the association with adverse obstetric and perinatal outcomes.RESEARCH DESIGN AND METHODSThis was a retrospective Danish national cohort study including all singleton pregnancies in women with type 2 diabetes, giving birth to a liveborn infant, between 2004 and 2019. HbA1c trajectories were identified using latent class linear mixed-model analysis. Associations with adverse outcomes were examined with logistic regression models.RESULTSA total of 1,129 pregnancies were included. Three HbA1c trajectory groups were identified and named according to the glycemic control in early pregnancy (good, 59%; moderate, 32%; and poor, 9%). According to the model, all groups attained an estimated HbA1c


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Enhancing Perioperative Diabetes Care: Strategies and Challenges

People with diabetes are more likely to have surgical interventions than the general population and account for as many as 25% of surgical cases (1). They face increased risks of postoperative surgical and dysglycemic complications, prolonged lengths of stay, increased readmissions, and elevated mortality rates (2–4). To mitigate these challenges and reduce the financial burden on health care systems, it is crucial for specialist diabetes teams and perioperative/surgical teams to implement effective systems for safer perioperative diabetes care.


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Issues and Events

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Werner Syndrome and Diabetes: Opportunities for Precision Medicine

The precision diagnosis of diabetes is an increasingly important part of understanding the full spectrum of disease heterogeneity, and several groups have recently outlined current and future roles for precision medicine approaches in diabetes (1–4). Patients with monogenic or syndromic diabetes are often misdiagnosed as having type 1 or type 2 diabetes (5,6), so it remains a pressing question how patients with atypical presentations of diabetes should be evaluated and what role precision medicine should have in their care. This exact question is raised in the thought-provoking case report presented by Spira et al. (7) in this issue of Diabetes Care, who describe a patient found to have a previously unidentified variant in the WRN gene, which is associated with Werner syndrome (WS) as well as diabetes, insulin resistance, and hirsutism.


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