Search Medical Journals & Research Articles

The Impact of African Caribbean Heritage on the Development of Sight-Threatening Diabetic Retinopathy in a Multiethnic Cohort of People With Type 2 Diabetes

OBJECTIVE Our aim was to identify risk factors for sight-threatening diabetic retinopathy (STDR) in a multiethnic cohort of type 2 diabetes attending a surveillance digital diabetes eye screening service in South London between 2004 and 2018. RESEARCH DESIGN AND METHODS A total of 8,529 people who had no retinopathy at baseline were included in this analysis. Female participants made up 49% of the cohort, 38% were White Caucasian, 43.4% were African Caribbean, and 18.6% were of other racial/ethnic groups. STDR was defined as the presence of any moderate to severe nonproliferative or preproliferative diabetic retinopathy, proliferative diabetic retinopathy, or maculopathy in either eye, per U.K. National Diabetic Eye Screening criteria. Multivariable analyses with STDR as the primary end point and death as a competing event were performed. RESULTS Of the 8,529 people in the cohort, 489 (5.7%) progressed to STDR over a median follow-up of 8.9 years. They had higher baseline median (interquartile range) HbA 1c values (75.9 [58.4, 93.4] vs. 61.7 [49.9, 79.2] mmol/mol) and longer duration of diabetes (11 [7, 15] vs. 4 [2, 9]) years and were more likely to be of African Caribbean heritage (48% vs. 52%; P < 0.001 for all). Given that 2,880 people died before progressing to STDR, we performed a competing risk analysis, in which African Caribbean ethnicity (hazard ratio [HR] 1.35; 95% CI 1.13–1.62), duration of diabetes (HR 1.05, 95% CI 1.05–1.06), HbA 1c (HR 1.02; 95% CI 1.02-1.02), and total cholesterol (HR 1.13; 95% CI 1.05–1.21) emerged as significant independent factors associated with development of STDR. CONCLUSIONS In a multiethnic cohort of type 2 diabetes, we observed an increased risk of STDR in people of African Caribbean ethnicity, which was independent of traditional risk factors.

Familial Hypercholesterolemia in Pediatric Patients With Type 1 Diabetes: Double Challenge for Diagnosis and Treatment

OBJECTIVE Familial hypercholesterolemia (FH) and type 1 diabetes (T1D) are both common and without adequate treatment, lead to premature atherosclerosis and cardiovascular events. We identified children with T1D and probable FH and analyzed their lipid-lowering therapy (LLT). RESEARCH DESIGN AND METHODS This retrospective cohort study was based on the Diabetes Prospective Follow-Up registry, analyzing data of 41,992 children (2014–2023) with pediatric T1D from 384 European centers. Classification of probable FH was >2× LDL cholesterol (LDL-C) >4.9 mmol/L and of possible FH, >2× LDL-C >4.1 mmol/L and ≤4.9 mmol/L. RESULTS A total of 31,862 patients consistently had LDL-C <4.1 mmol/L, 416 (1.2%) had possible FH, and 195 (0.56%) had probable FH. Compared with the LDL-C <4.1 mmol/L cohort, the possible FH and probable FH groups had higher BMI standard deviation scores (0.73 and 0.55 vs. 0.27, P < 0.00001) and higher HbA 1c (8.2% [66 mmol/mol]) and 8.3% [67 mmol/L] vs. 7.5% [58 mmol/mol], P < 0.00001) and were more often female (57% and 62% vs. 44%, P < 0.00001). Odds ratios for LDL-C 2× >4.9 mmol/L were 3.85 (95% CI 2.6–5.7) for HbA 1c >9% (>75 mmol/mol), 2.12 (1.48–3.04) for HbA 1c 7.5–9% (58–75 mmol/mol), 2.10 (1.56–2.81) for female sex, and 1.47 (1.08–2.02) for BMI >70th percentile. In the possible FH and probable FH groups, 20% and 29% were receiving LTT, respectively. CONCLUSIONS The prevalence of probable FH was high (1 in 215 children) in pediatric T1D. We assume that the majority are affected by genetic FH, modified by HbA 1c and BMI. Despite the very high risk for premature atherosclerosis in patients with FH and T1D, only one-third receive LLT.

Risk of Acute Pancreatitis and Biliary Events After Initiation of Incretin-Based Medications in Patients With Type 2 Diabetes

OBJECTIVE Patients with type 2 diabetes (T2D) are at increased risk of acute pancreatitis (AP) and biliary events. Evidence remains mixed regarding the association between incretin-based therapies, such as glucagon-like peptide 1 receptor agonists (GLP-1RAs) and dipeptidyl peptidase 4 inhibitors (DPP-4is), and these outcomes. We examined the association between incretin medication use and risk of incident AP or biliary disease in patients with T2D. RESEARCH DESIGN AND METHODS Using Medicare Fee-for-Service (FFS) and two U.S. commercial claims databases (2014–2021), we identified three pairwise cohorts of propensity score (PS)–based fine stratification–weighted patients aged ≥18 years (≥65 years in Medicare FFS) with T2D without prior AP or biliary disease who initiated treatment with GLP-1RAs versus sodium–glucose cotransporter 2 inhibitors (SGLT2is), DPP-4is versus SGLT2is, or GLP-1RAs versus DPP-4is. PS was estimated using 92 covariates. Weighted hazard ratios (HRs) with 95% CIs for hospitalization because of AP and biliary events were estimated using Cox models. RESULTS Each cohort included >1.2 million patients. After weighting, GLP-1RA and DPP-4i initiators had similar risk of AP compared with SGLT2i initiators (HR 1.01; 95% CI 0.90–1.13 and HR 1.00; 95% CI 0.85–1.15, respectively). However, both GLP-1RA and DPP-4i initiators showed a modestly increased risk of biliary disease compared with SGLT2i initiators (HR 1.15; 95% CI 1.05–1.26 and HR 1.22; 95% CI 1.03–1.46, respectively), equivalent to fewer than one additional event per 1,000 person-years. There was no difference in risk of AP (HR 1.08; 95% CI 0.95–1.22) or biliary disease (HR 0.95; 95% CI 0.86–1.04) between GLP-1RAs and DPP-4is. CONCLUSIONS In patients with T2D, GLP-1RAs and DPP-4is were associated with a small increase in risk of biliary disease, but not of AP, compared with SGLT2is.

Incidence of Type 2 Diabetes With Verapamil Compared With Other Calcium Channel Blockers

OBJECTIVE Evidence that the calcium channel blocker (CCB) verapamil slows type 1 diabetes progression suggests possible preventive benefits among people at risk of developing type 2 diabetes. We compared type 2 diabetes incidence between users of verapamil versus other CCBs in a population-based cohort. RESEARCH DESIGN AND METHODS From a random sample of Australians in national subsidized health care databases, we identified 90,026 individuals who initiated treatment with a CCB (at least two supplies) between July 2003 and December 2014. Incident diabetes was captured by subsequent receipt of glucose-lowering treatment or registration with the National Diabetes Services Scheme. Individuals were followed from first CCB supply until discontinuation, diabetes onset, death, or end of 2014. Multistate Poisson regression models characterized associations of CCB subclass with type 2 diabetes incidence and death (the competing event), after multivariable propensity score adjustment. RESULTS The cohort comprised 4,485 verapamil users (5.0%) and 85,541 treated with other CCBs (mostly dihydropyridines). During a median 1.6-year follow-up, 101 individuals treated with verapamil developed type 2 diabetes (8.8 per 1,000 person-years) compared with 2,622 people treated with other CCBs (11.4 per 1,000 person-years). This translated to an incidence rate ratio of 0.77 (95% CI 0.63–0.94) in favor of verapamil (fully adjusted) and a lower probability of type 2 diabetes at 6 years (4.2% [95% CI 3.3–5.3] vs. 5.4% [4.7–6.3] for a typical clinical profile; absolute risk difference 1.3% [95% CI –0.1–2.4]). Results were robust across multiple sensitivity analyses. CONCLUSIONS Verapamil use is associated with a lower incidence of type 2 diabetes compared with other CCBs.

Natural Language Processing for Automated Extraction of Continuous Glucose Monitoring Data

OBJECTIVE Continuous glucose monitoring (CGM) is essential in diabetes care and research; however, extracting key data (e.g., time above, in, or below range) from CGM reports is manual, time-consuming, and inefficient. Natural language processing (NLP) can extract data from unstructured sources (e.g., images), but its application in CGM remains unexplored. We aimed to evaluate the accuracy of extracting CGM data using NLP. RESEARCH DESIGN AND METHODS We analyzed CGM reports stored as PDF files from the electronic health record at New York University Langone Health. The steps of our algorithm pipeline consist of 1 ) performing optical character recognition (OCR) to obtain glucose matrix data from CGM reports, 2 ) determining the type of CGM documents based on keywords in OCR results, 3 ) extracting variables of glucose based on CGM document type, and 4 ) storing the extracted glucose data in a structured database. Two experts with experience in CGM research and clinical practice conducted an independent manual review of 1% of the documents ( n = 226). We calculated accuracy (correct extraction of CGM data) by comparing the algorithm’s results with the manual review. RESULTS Of the documents analyzed, 36.8% were Freestyle Libre and 63.2% were Dexcom. For information extraction, the agreement in evaluating Libre results between two experts was 99.93%. When comparing algorithm accuracy with manual review, the accuracy for Libre was 99.87% and, for Dexcom, 100.00%. CONCLUSIONS Using an NLP approach to extract valuable glucose data from CGM PDF files is feasible and accurate, which can benefit clinical practice and diabetes research.

Effects of Modern Glucose Monitoring and Insulin Delivery Technologies on Patient-Reported Outcomes and Experiences in Individuals With Type 1 Diabetes: A Systematic Review and Meta-analysis

BACKGROUND Use of technology is central to the management of type 1 diabetes (T1D), while patient reported outcomes measures (PROMs) can support in the management of these individuals. PURPOSE To assess the effect of diabetes technologies on patient-reported outcome measures (PROMs) in type 1 diabetes (T1D). DATA SOURCES Cochrane Library CENTRAL, Embase, MEDLINE, Scopus, and Web of Science were searched for relevant articles from 2013 to August 2025. STUDY SELECTION We included longitudinal diabetes technology studies assessing validated PROMs in nonpregnant adults with T1D. DATA EXTRACTION Study characteristics and PROM data were extracted, and standardized mean differences (SMDs) for PROs were pooled using a random-effects meta-analysis. DATA SYNTHESIS We identified 4,885 articles, comprising 81 independent studies ( n = 19,148 participants) and 70 different PROMs. The Hypoglycemia Fear Survey (HFS) was most commonly used ( k = 39 studies), followed by the Diabetes Treatment Satisfaction Questionnaire (status [DTSQs] or change version [DTSQc]; k = 38), Diabetes Distress Scale (DDS; k = 25), and Problem Areas in Diabetes (PAID) scale ( k = 24). Technology use was associated with lower HFS total score compared with control (SMD −0.177; 95% CI −0.319, −0.036; P = 0.014; I 2 = 0.0%), with the largest effect observed in automated insulin device users. A moderate positive effect of diabetes technologies was observed on DTSQs and DTSQc scores (SMD 0.429; 95% CI 0.206, 0.653; P < 0.001; I 2 = 72.3%), with a small to moderate reduction in DDS and PAID scores (SMD −0.265; 95% CI −0.363, −0.166; P < 0.001; I 2 = 0.0%). LIMITATIONS Differences in type of technology, varied use and incomplete reporting of PROMs, and different duration of studies. CONCLUSIONS Diabetes technologies offer psychological benefits in adults with T1D. The large number of reported PROMs suggests a need to standardize their use.

Screening Natriuretic Peptide Levels Predicts Heart Failure and Death in Individuals With Type 1 and Type 2 Diabetes Without Known Heart Failure

OBJECTIVE Heart failure (HF) is common in diabetes and may be asymptomatic in early stages. N-terminal pro-brain natriuretic peptide (NT-proBNP) and B-type natriuretic peptide (BNP) (collectively natriuretic peptides [NPs]) are markers that can be used to detect early HF in asymptomatic individuals who may benefit from disease-modifying therapies. We examined the prognostic role of NP levels in people with type 1 diabetes (T1D) or type 2 diabetes (T2D) without known HF. RESEARCH DESIGN AND METHODS Optum’s de-identified Market Clarity Data were queried for adults (aged ≥18 years) with T1D or T2D without known HF who received an outpatient NP test between 2017 and 2023. Associations between NP levels and incident HF or death were assessed using multivariable Cox proportional hazard models. RESULTS Among 116,466 eligible adults ( n = 2,990 with T1D; n = 113,476 with T2D) followed for up to 7 years (54% female; median age 64 years; mean HbA 1c 7.1% at baseline), approximately 39.6% of individuals with T1D and 42.3% of individuals with T2D had BNP ≥50 pg/mL or NT-proBNP ≥125 pg/mL. In adjusted Cox models, increased NT-proBNP level was significantly associated with increased risk of incident HF or mortality among individuals with T1D (for NT-proBNP level 125–300 pg/mL: HR [95% CI] 2.04 [1.35–3.07], for NT-proBNP level >300 pg/mL: 4.48 [3.11–6.47], reference: NT-proBNP <125 pg/mL) and T2D (for NT-proBNP level 125–300 pg/mL: HR [95% CI] 1.85 [1.74–1.97], for NT-proBNP >300 pg/mL: 3.58 [3.39–3.78], reference: NT-proBNP <125 pg/mL). Similar findings were observed for BNP. CONCLUSIONS Increased NP levels among individuals with diabetes are highly prognostic for future risk of HF or mortality. These findings support the implementation of NP screening for HF risk assessment in people with diabetes.

Potential Benefits of Remission of High Childhood BMI Keep Increasing

Obesity is a chronic disease defined by excess adiposity that presents a risk to health (1). As a consequence of the rise in obesity prevalence, diabetes, chronic kidney disease (CKD), and cardiovascular disease (CVD) prevalence have also increased. Recently, the American Heart Association released a definition of a combined cardiovascular-kidney-metabolic (CKM) syndrome: “CKM syndrome is a systemic disorder characterized by pathophysiological interactions among metabolic risk factors, CKD, and the cardiovascular system, leading to multiorgan dysfunction and a high rate of adverse cardiovascular outcomes; CKM syndrome includes both individuals at risk for CVD due to the presence of metabolic risk factors, CKD, or both and individuals with existing CVD that is potentially related to or complicates metabolic risk factors or CKD” (2). Although treatment of the individual components may slow disease progression, the conditions are not typically curable (3,4), highlighting the need for prevention. Evidence clearly supports the premise that adiposity is the common underlying cause of CKM syndrome (5).

Revisiting the Link Between Meat Intake and the Risk of Type 2 Diabetes in American Indians: Insights Based on Lipidomic Profiles

Type 2 diabetes is a burgeoning health crisis, affecting more than 500 million people worldwide ( 1 ). More alarmingly, the majority have developed complications when diagnosis is made ( 2 ). The epidemiology of type 2 diabetes differs among various racial and ethnic populations ( 3 ). In the U.S., prevalence of type 2 diabetes is highest among American Indians and is more than twice that among non-Hispanic Whites ( 4 ). Given the daunting diabetes disparities that American Indians face, effective intervention strategies are urgently needed to curb the high burden of type 2 diabetes in this population. The role of diet as one of the key modifiable factors in determining the risk of type 2 diabetes has been well established ( 5 ). Accumulating evidence from both large prospective studies and meta-analyses demonstrated positive associations of high consumption of processed meat and unprocessed red meat with risk of type 2 diabetes ( 6–9 ). Red meat contains heme iron and saturated fat, while meat processing can produce harmful chemicals like nitrates and advanced glycation end products, all of which were related to reduced insulin sensitivity, pancreatic β-cell function, or both and thereby were associated with increased risk of type 2 diabetes ( 10–12 ). However, the biological mechanisms that link processed and red meat intake with altered glucose hemostasis are not yet fully characterized. Further, data among minority populations, especially Indian Americans, remain limited.

Additive Benefits of Control-IQ+ AID to GLP-1 Receptor Agonist Use in Adults With Type 2 Diabetes

OBJECTIVE To assess the effect of automated insulin delivery (AID) on glycemic and insulin outcomes in adults with insulin-treated type 2 diabetes using a glucagon-like peptide-1 receptor agonist (GLP-1 RA). RESEARCH DESIGN AND METHODS In a randomized trial comparing Control-IQ+ AID versus continuation of prestudy insulin delivery method plus continuous glucose monitoring (CGM group), 143 (45%) of the 319 participants were using a GLP-1 RA at baseline, which was continued during the trial. RESULTS Among GLP-1 RA users, mean HbA 1c decreased by 0.8% from a baseline of 8.0 ± 1.2% with AID, which represented a mean improvement of −0.5% (95% CI −0.8 to −0.3, P < 0.001) compared with the CGM group. Time-in-range 70–180 mg/dL and other CGM metrics reflective of hyperglycemia also showed comparable statistically significant improvements using AID when added to GLP-1 RA use. For GLP-1 RA users, there was no significant difference in weight after 13 weeks with AID compared with the CGM group (0.9 kg, 95% CI −0.2 to 2.1, P = 0.10), whereas, in GLP-1 RA nonusers, there was a mean weight gain of 1.9 kg with AID compared with CGM (95% CI 0.5 to 3.2, P = 0.007). CONCLUSIONS The benefits of AID appear to be substantial for a broad spectrum of insulin-treated patients with type 2 diabetes, including those already receiving contemporary and guideline-directed therapy, such as a GLP-1 RA medication. These additive benefits of AID in GLP-1 RA users included significant reductions in HbA 1c levels with simultaneous reduction in insulin use, along with no statistical increase in weight despite very significant improvements in glycemic control.

Disparities in Continuous Glucose Monitor Uptake Among Veterans With Diabetes Despite Universal Coverage

We commend Alkabbani et al. (1) for their important work highlighting differences in continuous glucose monitor (CGM) uptake among insulin-treated older adults with type 2 diabetes. The authors found that CGM use was low (<10%) and that disparities remained by race, ethnicity, and socioeconomic status (SES), with SES markedly increasing disparity.

Comment on Samovski et al. Effect of Marked Weight Loss on Adipose Tissue Biology in People With Obesity and Type 2 Diabetes. Diabetes Care 2025;48:1342–1351

We congratulate Samovski et al. (1) for their meticulous translational study in Diabetes Care demonstrating that marked weight loss remodels adipose tissue extracellular matrix (ECM) gene expression and attenuates circulating small extracellular vesicle (sEV) microRNAs, effects that are tightly linked to improved whole-body insulin sensitivity in adults with obesity and type 2 diabetes. The integration of deep molecular phenotyping with rigorous metabolic clamp methodology is an important advance. Nevertheless, several points merit consideration to refine causal inference and guide clinical translation.

About the Editor: Namratha R. Kandula, MD, MPH—Cross-Cultural Understanding and Prevention Strategies for Immigrant Populations

By the age of four, Namratha R. Kandula had lived in as many countries. “England, India, Canada, the U.S.,” she says. But her family settled in Bethlehem, a small town in Pennsylvania. “We were one of the first Indian families to move there,” Kandula says. “My parents were both physicians and they helped establish the first Hindu temple in that area. Many other families moved in after we did. I remember parties when I was young, where the adults talked upstairs as the kids played in the basement. It was a very tight-knit community.”

Now Is the Time to Remove Barriers to AID Treatment for Those With Detectable C-Peptide

In an automated insulin delivery (AID) system, data from an individual’s continuous glucose monitor (CGM) are fed into a mathematical algorithm that uses their glucose data to modulate insulin delivery via an insulin pump. AID systems have been demonstrated to provide protection against both low and high glucose levels in type 1 diabetes (1–5) and are also associated with improvements in quality of life (6–7). Assessment of clinical effectiveness and cost-effectiveness (8) by bodies that can influence policy is a key element of ensuring access to treatments for those who stand to benefit. For example, in England and Wales, assessments are undertaken by the National Institute for Health and Care Excellence (NICE). Their publication of a supportive assessment (Technology Appraisal 943) (9) is now driving the national provision of the use of AID systems in people with type 1 diabetes who meet clearly defined prespecified criteria. This is one example of AID systems becoming the standard of care for people with type 1 diabetes internationally.

Remission of Type 2 Diabetes: Many Paths to the Same Goal

The global prevalence of type 2 diabetes continues to rise inexorably, translating to millions of individuals at risk of developing debilitating and life-threatening vascular and metabolic complications (1). The current treatment paradigm for type 2 diabetes, aiming at restoring and maintaining euglycemia through a combination of lifestyle modification and pharmacotherapy, does not adequately attenuate this risk, particularly since individuals might have accumulated considerable magnitude and duration of hyperglycemia prior to diagnosis. Therefore, attention has recently been focused on inducing remission of type 2 diabetes, i.e., returning individuals to a state of euglycemia without ongoing need for glucose-lowering medications (2). Several approaches have been trialed to achieve this goal, including intensive lifestyle modification, pharmacotherapy, and surgery. Most evidence for the effectiveness of such programs comes from developed countries, with limited diversity of target populations, and little data exist on the benefits of multimodal pharmacotherapy interventions for type 2 diabetes remission.