BMJ Open Diabetes Research & Care

Aims/hypothesisHuman islet amyloid polypeptide (hIAPP) deposition is a common feature of type-2 diabetes (T2D). Previous studies have demonstrated hIAPP-mediated endothelial cell (EC) dysfunction and inflammation, but little is known about islet microvascular stability or pericyte function in hIAPP-containing islets. This study investigates how islet endothelial cells and pericytes are influenced by hIAPP aggregation. MethodsBulk RNAseq and qPCR were conducted on hIAPP or vehicle treated MS-1 cells and bead-purified human islet CD31+ cells from donors with or without T2D to determine how islet ECs respond to hIAPP exposure. Confocal imaging of living pancreatic slices obtained from hIAPP transgenic mice was conducted to evaluate the effect of hIAPP deposition on islet pericyte function and vasomotor responses. ResultshIAPP-treated MS-1 cells and ECs purified from T2D islets demonstrate downregulation of leading-edge genes associated with extracellular matrix and cell adhesion pathways. Pericytes from hIAPP-expressing mouse islets appear detached from underlying endothelial cells, which was associated with impaired vasomotor responses to constrictive or dilatory stimuli. Conclusions/interpretationhIAPP induces vascular destabilization by downregulating mRNA of key extracellular matrix and cell adhesion molecules in ECs, likely promoting the breakdown of EC-EC and EC-pericyte coupling. hIAPP disrupts EC-pericyte connections, and pericyte detachment ultimately impairs pericytes ability to modulate capillary diameter without impairing intracellular Ca2+ dynamics. Our data suggest that amyloid deposition compromises EC health and survival by altering islet microvascular morphology, stability, and function. This, in turn, may disrupt islet microvascular stability and exacerbate endocrine cell dysfunction in T2D. Research in contextO_ST_ABSWhat is already known about this subject?C_ST_ABS- hIAPP is cytotoxic to islet endothelial cells and beta cells, and contributes to islet failure in type-2 diabetes (T2D) - hIAPP transgenic mice demonstrate islet capillary dilation, loss of vascular structures, and increased pericyte density - Impaired pericyte anchorage and vascular fragmentation drive diabetes-related vasculopathies in other tissues, like the retina, kidney, and brain What is the key question?- How does the surviving microvasculature in islets respond to hIAPP deposition? What are the new findings?- Endothelial cells demonstrate transcriptional downregulation of key genes involved in cytoskeleton, ECM, and cell-adhesion maintenance, including Thbs1, Tln1, and Plec. - Amyloid deposits disrupt homeostatic interactions between endothelial cells and pericytes. - Amyloid-adjacent islet pericytes are detached from endothelial cells and display impaired ability to modulate capillary diameter. How might this impact on clinical practice in the foreseeable future?- Therapies targeting endothelial cell-pericyte interactions may restore islet microvascular stability and improve islet function, especially in the context of early T2D.

Background: Prediabetes is a critical intermediate stage in the development of type 2 diabetes mellitus and is increasingly prevalent in the Eastern Mediterranean Region. In Qatar, high levels of metabolic and lifestyle-related risk factors underscore the need for scalable, non-invasive risk stratification tools within primary care. The Prediabetes Risk Score in Qatar (PRISQ) was developed as a population-specific screening tool; however, its distribution and associated risk patterns within national primary care settings remain insufficiently characterized. This study aimed to assess the population-level distribution of PRISQ scores among adults attending primary care in Qatar and to identify key sociodemographic and clinical correlates of elevated prediabetes risk. Methods: A cross-sectional analysis was conducted among adults ([&ge;]18 years) registered with the Primary Health Care Corporation (PHCC), using data derived from the HEALTHSIGHT study. PRISQ scores were calculated based on five non-invasive clinical parameters: age, sex, body mass index, waist circumference, and blood pressure. Participants were categorized into low, moderate, and high-risk groups using established PRISQ cut-offs. Descriptive analyses summarized risk distributions, and multivariable linear regression was used to identify independent predictors of PRISQ scores. Results: Among 1,116 participants included in the final analysis, the mean PRISQ score was 26.5 {+/-} 11.0. Nearly half of the study population (47.7%) was classified as high risk for prediabetes, while 34.4% and 17.9% were categorized as moderate and low risk, respectively. Increasing age was the strongest contributor to higher PRISQ scores, followed by body mass index, waist circumference, and blood pressure (all p < 0.001). High-risk individuals were more frequently male, older, overweight or obese, and long-term residents of Qatar, with variation across nationality groups. Conclusions: A substantial proportion of adults attending primary care in Qatar are at high predicted risk for prediabetes. These findings support the utility of PRISQ as a risk stratification and engagement tool in primary care to guide early lifestyle counselling and targeted preventive interventions. Longitudinal studies are needed to assess progression to dysglycemia and to further refine risk-based screening strategies.

Background & AimsDiabetes mellitus has been associated with both intestinal barrier dysfunction and peripheral neuropathy leading to increased risk of infection. The mucus layer forms a physical barrier against pathogens and is a critical component of the intestinal barrier that may be impaired in diabetes. This study aimed to assess how diabetes impacts goblet cells (GCs), mucus layer integrity, and innervation in the colon. MethodsFluorescence microscopy was used to investigate GCs, the mucus layer, and innervation in the colon of db/db mice. Custom open-access image analysis pipelines were developed to quantify GC numbers, location and content, mucus thickness, bacterial colonization, and innervation density in intestinal tissue sections. We also treated mice with the clinically used glucagon-like peptide 1 receptor (GLP-1R) agonist liraglutide to assess its capacity to reverse pathological changes to GCs and the mucus layer in a model of established type 2 diabetes (T2DM). ResultsThe mucus layer was significantly thinner in the colon of db/db mice with established diabetes and bacteria more readily colonized the epithelium and crypts. Intercrypt GC numbers were significantly reduced in db/db mice. However, there were significantly more GCs per crypt, and crypts were elongated in the db/db colon. Innervation was reduced in the mucosa and external muscle of the colon, consistent with diabetic neuropathic changes. Liraglutide treatment increased the size of GCs but had no effect on GC numbers, mucus thickness, or innervation in this model of established T2DM. ConclusionsMucus barrier dysfunction and GC hyperplasia is evident in the db/db colon. Increased microbial penetrability through the mucus layer suggests potential implications for the increased risk of gastrointestinal infection in diabetes.

Background and objectivesType 1 diabetes (T1D) is a largely self-managed condition that requires ongoing daily tasks and decisions. Many people living with T1D in Canada manage it alone, which can feel very isolating and negatively affect physical and mental health. Connecting with other people in similar situations may help to reduce the potential burden associated with managing this health condition. We aim to co-develop and evaluate a virtual peer support program called CommuniT1D, led by people with T1D, to improve the overall wellbeing of people across Canada whose lives are affected by T1D. Methods and analysisUsing a community-based participatory design and action research approach and a realist evaluation framework, we will first co-develop CommuniT1D by working together as a group of people with T1D, researchers, and clinicians. Over two thirds of steering committee members live with T1D (their own or their childs.) This collective lived expertise is complemented by experts in mental health, social support, health services research, and other relevant fields. Once the program is ready to welcome members, we will work with our partner organizations, networks, and use tailored ads to recruit CommuniT1D peer leaders and members. We will then form virtual peer support groups of people with shared lived experience. Within the program, we will hold monthly small group meetings led by peer leaders via an online platform. We will also hold monthly large webinars open to all CommuniT1D members and other interested people. To evaluate CommuniT1D, we will conduct surveys at baseline and every 6 months, collecting data about diabetes distress, life challenges, quality of life, wellbeing, management indicators, and access and use of management tools and services. We will analyze quantitative data using repeated measures analysis of variance. We will also conduct individual interviews with CommuniT1D members and peer leaders at two time points. We will analyze interview data thematically, and create a logic model by triangulating results from qualitative and quantitative analyses, applying a realist evaluation lens. DiscussionPeer support may help people with T1D feel less alone and better supported. This protocol outlines the design of a virtual peer support program called CommuniT1D to improve the wellbeing of people whose lives are affected by T1D in Canada. We hope that this program will help better equip people with T1D to cope with T1D-related stressors, thus improving the lives of people with T1D in Canada.

Objective: In this study, we utilized a large-scale clinical database to evaluate the relationship between polypharmacy and adverse outcomes among type 2 diabetes patients in rural Montana to inform strategies that improve adherence, reduce preventable complications, and promote equitable diabetes care in underserved regions. Research Design and Methods: 591 patients from the Big Sky Care Connect Database (BSCC) with type 2 diabetes and medication history were stratified into 3 cohorts based on prescribed number of medications: (1-4 medications, non-polypharmic), (5-9 medications, polypharmic), and ([&ge;]10 medications, hyperpolypharmic). Each cohort was examined for Major Adverse Cardiovascular Events (MACE) and Diabetes Complication Severity Index (DCSI). Descriptive statistics, multivariate logistic regressions, linear regression, and Poisson regression analyses were performed. Results: Medication count was associated with male gender ({beta} = -2.1341, p < 0.001). Both medication count (IRR 1.06 per additional medication, p < 0.001) and age (IRR 1.03 per year, p < 0.001) were significant predictors of MACE. Neuropathy and nephropathy prevalence was statistically significant (p < 0.001) across patient cohorts and increased with medication count.

ObjectiveTo evaluate the effectiveness of a multifaceted lifestyle intervention delivered by patient peers and supported by healthcare workers and technology to achieve control and remission of type 2 diabetes. MethodsOpen-label, cluster-randomised controlled trial conducted in rural Assam, India. Type 2 diabetes patients identified through a screening program in 25 villages (clusters) were randomly assigned to intervention or standard care. At baseline, all participants underwent assessment of diet, physical activity, quality of life, medicine intake, physical measurements and biochemical evaluation. The intervention was a contextually designed package, delivered during fortnightly group counselling by patient-peers and healthcare workers, focusing on carbohydrate-restricted healthy diet, physical activity, diabetes management, and medication de-escalation. Nutrition data were transferred to the study management for suggestions and modifications on smartphones. Intervention was implemented for 3 months, when anthropometric and biochemical parameters were reassessed. Primary outcomes were diabetes control (HbA1c, fasting glucose) and remission (HbA1c <6.5% without medications). Modified intention-to-treat analysis has been performed. Results353 patients in rural locations (intervention=193, standard care=160) were enrolled. Baseline sociodemographic, lifestyle, clinical and biochemical parameters were not different in intervention and standard-care groups. At 3 months, in the intervention vs standard-care group there was significantly lower median (interquartile range) HbA1c 7.9% (7.0-8.7) vs 8.6% (7.6-9.8), p<0.001; and fasting glucose 188.0 mg/dl (146.2-253.5) vs 210.0 mg/dl (166.0-282.0), p=0.001. Diabetes remission was in 9 participants (5.0%) in intervention vs 4 (2.7%) in standard care (p=0.249). ConclusionsPatient-peers delivered and healthcare worker- and technology-supported diet and lifestyle intervention for type 2 diabetes led to significant improvement in diabetes control in rural patients in India. Diabetes remission was observed in a low proportion. Trial registrationRegistered with Clinical Trials Registry of India at www.ctri.nic.in; registration number CTRI/2022/03/041302 dated 22 March 2022. STRENGTHS AND LIMITATIONS OF THE STUDYO_LIMultifaceted diet and lifestyle intervention for type-2 diabetes control and remission, delivered by patient-peers with health worker and technology support, is feasible in rural populations in India. C_LIO_LIThis cluster-randomised trial shows that the intervention led to significantly better diabetes control. Diabetes remission occurred in a small proportion. C_LIO_LILarger and longer prospective studies are required to confirm the effectiveness of such lifestyle strategies for diabetes control and remission in India, lower-middle, and low-income countries. C_LI

AimWe examined associations between smoking and HbA1c among U.S. adults, and whether these associations vary by diabetes status. MethodsWe analyzed NHANES data from 2015-2018 for adults aged [&ge;]20 years. Smoking was assessed by self-report and serum cotinine. Survey-weighted multivariable linear regression was used to evaluate the association between smoking and HbA1c in the full population (N=9,214) and in adults without diabetes (N=7,328), adjusting for demographics, blood pressure, waist circumference, lipids, and C-reactive protein. ResultsAfter adjustment for cardiometabolic covariates, there was no significant association between smoking and HbA1c in the full population (former: {beta}=0.029%, p=0.30; current: {beta}=0.053%, p=0.13). Among adults without diabetes, former smoking was not associated with HbA1c, whereas current smoking remained significantly associated (former: {beta}=-0.001%, p=0.923; current: {beta}=0.067%, p<0.001). These findings were similar when cotinine was used as the exposure measure, with active smoking ([&ge;]3.0 ng/mL) associated with higher HbA1c among non-diabetic adults (p<0.001), but not in the full population. ConclusionsAmong adults without diabetes, current but not former smoking was associated with higher HbA1c. The absence of an association in former smokers suggests that this effect may attenuate following cessation. These findings support early cessation interventions and may inform cessation counseling and diabetes screening.

IntroductionDysglycemia is a well-established risk factor for cardiovascular disease (CVD); yet traditional glycemic traits, including fasting plasma glucose (FPG) and HbA1c, do not capture dynamic glucose fluctuations that may inform CVD risk. We cross-sectionally investigated the association of continuous glucose monitor (CGM)-derived metrics and 2-h post-prandial glucose (2-h PPG) with estimated 10-year CVD risk among individuals without diabetes. MethodsWe included 1,360 Framingham Heart Study participants (Third Generation, New Offspring Spouse, and Omni 2 cohorts at exam 4) without prevalent diabetes or CVD who had [&ge;]3 days of CGM data and completed a mixed meal tolerance test (MMTT) with corresponding 2-PPG. We included 7 CGM summary metrics and defined data-driven glucotypes according to CGM measures of glycemic burden and variability. The 10-year CVD risk was estimated using the Predicting Risk of CVD EVENTs (PREVENT) base equations. We performed linear regression on standardized glycemic traits and glucotypes with log-transformed PREVENT risk scores and multinomial regression to relate standardized CGM metrics and 2-h PPG with PREVENT categories (low <5%[reference], borderline 5-<7.5%, intermediate/high [&ge;]7.5%). All models were adjusted for FPG and body mass index (BMI). ResultsAmong participants (55.9% women, 43.4% with prediabetes), mean age was 59.3 years, and mean BMI was 27.9 kg/m2. All CGM-derived metrics and 2-h PPG were positively associated with higher overall 10-year CVD risk (per 1 SD increase of each exposure variable, {beta} range: 0.06-0.16, all p<0.001). A glucotype representing high glycemic burden and high glycemic variability was associated with higher overall 10-year CVD risk, compared with the glucotype representing low glycemic burden and low glycemic variability. Higher CGM-derived metrics and 2-h PPG were also associated with higher odds being in the intermediate/high CVD risk (OR range: 1.20-1.65, all p<0.001), adjusting for FPG and BMI. ConclusionDynamic glycemic traits, including novel glucotypes that capture glycemic burden and variability, may provide novel insights into CVD risk prevention among individuals without T2D.

Abstract Context Lipoprotein(a) [Lp(a)] is a genetically determined and independent cardiovascular risk factor, traditionally considered stable across the lifespan, supporting a single lifetime measurement strategy. However, its longitudinal behavior during childhood and adolescence remains poorly characterized, particularly in individuals with type 1 diabetes who are at increased lifetime risk of cardiovascular disease. Objective We aimed to characterize intra- and inter-individual trajectories of Lp(a) in youth with type 1 diabetes and to assess the implications of variability for cardiovascular risk classification. Methods We conducted a retrospective single-center cohort study of children and adolescents with type 1 diabetes followed at Geneva University Hospitals between 2012 and 2023. Annual fasting Lp(a) concentrations were analyzed longitudinally. Variability was assessed in participants with more than two measurements. Clinically relevant thresholds were used to evaluate risk reclassification. Statistical analyses included paired Wilcoxon tests, Pearson and Kendall correlations, and Holm-adjusted p-values. Results A total of 287 participants contributed 1,408 Lp(a) measurements over a median follow-up of 6.2 years (IQR 2.9-9.6). At baseline, 26% had elevated Lp(a) (above or equal 300 mg/L). Among participants with serial measurements, 32% exhibited intraindividual fluctuations exceeding 50% of their maximum value. Reclassification across the 300 mg/L threshold occurred in 11.9% of participants. Lp(a) concentrations peaked between ages 10 and 13 years and declined thereafter. Modest seasonal variation was observed, with higher levels in autumn and winter (P < 0.05). Conclusions In youth with type 1 diabetes, Lp(a) demonstrates clinically relevant intraindividual variability over time. These findings suggest that reliance on a single lifetime measurement may lead to misclassification of cardiovascular risk and support repeated assessment, particularly during adolescence, to improve risk stratification.

BackgroundOptimal management of Type 1 diabetes (T1D) requires precise insulin dosing and sick-day decision-making; deficiencies in either predispose to hypoglycemia, suboptimal glycaemic control, and diabetic ketoacidosis. We developed DiaBuddy, a guideline-aligned mobile decision support tool, and evaluated its accuracy versus expert guidance and its clinical impact in children with T1D. MethodsThe preclinical validation compared DiaBuddy and family recommendations (N = 37) for 20 insulin-dosing and 20 sick-day vignettes against a pediatric endocrinologist gold standard. The prospective single-arm pilot study evaluated its impact on HbA1c, CGM metrics, and quality of life in 20 children. ResultsIn the preclinical study, DiaBuddy showed lower absolute relative deviation for basal (5.0 {+/-} 6.7% vs 24.2 {+/-} 25.9%), bolus (6.9 {+/-} 10.9% vs 45.3 {+/-} 48.8%), and combined doses (6.3 {+/-} 9.3% vs 39.0 {+/-} 37.8%; all P < 0.001) than families. DiaBuddy achieved [&ge;]90% accuracy across all sick-day domains versus 27-70% for families; adherence would have prevented 94.5% of family errors including all hospitalization decision errors. In the clinical study, HbA1c declined from 9.18 {+/-} 1.99% to 8.48 {+/-} 1.44% (P = 0.049), PedsQL QOL score increased from 76.5 {+/-} 8.6 to 89.1 {+/-} 7.1 (+12.6 points, P < 0.001) with no change in CGM metrics. Application satisfaction was high (mean score 44.1 {+/-} 4.1 out of 50) with 96% wishing to continue using it. ConclusionsDiaBuddy delivers guideline-aligned guidance, substantially outperforming family decisions in preclinical vignette testing and showing preliminary signals of improvement in glycaemic control and quality of life in a small uncontrolled pilot study. The results support the conduct of larger randomised controlled trials.

Background: Lifestyle interventions incorporating medically-tailored meal delivery may support rapid behavior change among pregnant individuals with gestational diabetes (GDM). Purpose: To examine the feasibility and acceptability of a multicomponent lifestyle intervention for pregnant individuals with GDM. Primary outcomes included recruitment, retention, intervention receipt, and acceptability. Methods: We conducted a pilot randomized feasibility trial among pregnant individuals with GDM recruited from maternal fetal medicine clinics in the Hartford, Connecticut area. Participants were randomized to usual GDM care or the Meals4Moms intervention plus usual care. The intervention included medically-tailored meal delivery, personalized physical activity support, and multimodal education with digital tools. Participants completed a survey and three 24-hour dietary recalls at baseline and post-intervention. Meals4Moms participants also completed a semi-structured interview at follow-up. Intervention receipt was tracked by study staff. Results: Of 30 individuals approached, we screened 80% (n=24), of whom 75% (n=18/24) were eligible; we randomized 8 participants. Seventy-five percent (n=6/8) completed at least one component of the follow-up assessment (100%, n=4/4 Meals4Moms, 50%, n=2/4 Usual Care). One participant spent [&ge;]80% of her total food budget (n=1/4, 25%), and no participants completed [&ge;]80% of prescribed exercise sessions (range: 0-50%). All (n=4) Meals4Moms participants reported they would be very likely to participate in the program if they had GDM again, and 100% (n=4) would be very likely to recommend the program to a friend with GDM. Conclusions: While the Meals4Moms intervention was highly acceptable to participants, procedural refinements are needed prior to conducting a full-scale efficacy trial.

Background: Parental diabetes and obesity influence offspring phenotype, but their relative contributions remain unclear. Aim: To examine the relative contributions of parental diabetes and obesity to offspring overweight-obesity and glucose intolerance. Methods: We studied 200 offspring of mothers with diabetes in pregnancy (ODM; 176 indexes, 24 siblings), 176 mothers (133 gestational diabetes (GDM), 22 type 1, 21 type 2 diabetes), and 150 fathers. Controls included 177 offspring of non-diabetic mothers (ONDM), 177 mothers without diabetes in pregnancy, and 163 fathers. Overweight-obesity was defined by WHO criteria, central obesity as waist-to-height ratio >0.5, and glucose intolerance by ADA criteria (fasting glucose for <10 years; oral glucose tolerance test (OGTT) for >=10 years). Generalized linear mixed-effects models assessed parental determinants of offspring outcomes. Results: ODM were more overweight-obese, centrally obese, and glucose intolerant than ONDM. Younger ODM had higher capillary glucose (5.6 vs 5.1 mmol/L, p<0.001). Among ODM >=10 years, 37% had prediabetes and 5% diabetes versus 20% and 0% in ONDM. Overweight-obesity was associated with maternal (OR 7.81; 95% CI 2.19-27.85), paternal (OR 6.21; 95% CI 1.57-24.53), and biparental obesity (OR 9.59; 95% CI 2.73-33.69), but not parental diabetes. Glucose intolerance was associated only with maternal diabetes in pregnancy (OR 3.90; 95% CI 2.05-7.41). Conclusions: Preventing offspring obesity will require addressing parental obesity, whereas preventing glucose intolerance will require optimal glycemic control in the mothers before and during pregnancy.

Background: Older in-patients have a higher prevalence of diabetes and cognitive impairment. Cognitive impairment can make blood glucose management more challenging, since patients might not remember to measure blood glucose or report symptoms. Investigating the accuracy of continuous glucose monitoring (CGM) compared to usual care will inform clinical interpretations in this vulnerable population. Aim: To compare CGM derived glucose metrics and point-of-care tests (POCT) in older in-patients with T2DM and cognitive impairment and to investigate CGM accuracy compared to POCT in the hospital settings with the same population. Methods: Thirty-two older people with comorbid T2DM and cognitive impairment were recruited within a tertiary care hospital in the UK. All participants were naive to CGM and were asked to wear blinded Dexcom G7 sensors for up to 10 days. All participants received usual care in their hospital stay including the use of POCT. Key accuracy metrics comprised the mean absolute relative difference (MARD), median absolute relative difference (median ARD), and Clarke Error Grid (CEG), correlation (R2) analysis. In addition, the percentage of CGM readings falling within +/-20% of reference glucose values when the reference was >5.6 mmol/L, or within +/-1.1 mmol/L when the reference was <=5.6 mmol/L (+/-20%/1.1 mmol/L) was calculated to assess analytical and clinical accuracy. Results: Thirty participants completed the study. CGM derived mean glucose for time in range (TIR= 4-10 mmol/mol) was 36.23% (min= 0%, max= 90%), time above range (TAR >= 10 mmol/mol) was 62.87% and time below range (TBR <= 3.9 mmol/mol) was 1.03%. Mean TIR based on available POCT readings was 40.84%, TAR was 57.24% and TBR 1.81%, showing similar readings as CGM derived glucose metrics. Comparison of the two resulted in a MARD of 17.4%, and median ARD of 12.2% and the outcome of +/-20%/1.1 mmol/L analysis was 72.3%. CEG analysis revealed that 99.3% of the data points fell within the clinically acceptable zones (Zone A and Zone B), and there was a strong correlation (R2=0.82) between CGM and POCT. CGM captured more hypoglycaemic readings in our participants. Conclusion: Our study suggests that CGM and POCT derived glucose metrics are largely similar for in-patients with diabetes and cognitive impairment. CGM remains as a safe and clinically acceptable tool, and able to capture more nocturnal hypoglycaemia compared to POCT in a subgroup of patients. These initial findings show that CGM might be a viable alternative for people with comorbid T2DM and cognitive impairment.

Introduction/Aim: Type 2 diabetes (T2D) is a growing global health burden, with lifestyle behaviors playing a key role in its management. Physical activity (PA), sedentary behavior (SB), and sleep are increasingly conceptualized as interdependent components of 24-hour movement behaviors. While behavior change techniques (BCTs) are commonly used to target individual behaviors, their effectiveness across multiple behaviors in adults with T2D remains unclear. This systematic review and meta-analysis aimed to evaluate the effectiveness of behavior change interventions incorporating BCTs on PA, SB, and sleep outcomes, and to identify effective BCT clusters. Methods: A systematic search of PubMed, Web of Science, and Embase was conducted from inception to December 18, 2023. Randomized and non-randomized controlled trials including adults with T2D were eligible if they evaluated behavior change or lifestyle interventions targeting PA, SB, and/or sleep and included at least one BCT. Data extraction, BCT coding (using the BCT Taxonomy), and risk of bias assessment (Cochrane RoB 2) were performed independently by multiple reviewers. Meta-analyses using random-effects models were conducted for relevant outcomes. Subgroup analyses examined the effects of three common BCT clusters: goals and planning, feedback and monitoring, and social support. Results: Sixty-six studies (n = 18,725 participants) were included. Interventions significantly improved several PA outcomes, including steps/day (+1991 steps/day; p<0.001), total PA (SMD=0.36; p=0.02), moderate-to-vigorous PA (SMD=0.55; p<0.001), and light-intensity PA (SMD=0.62; p=0.01). Sedentary time decreased significantly (SMD=-0.32; p=0.008). Sleep quality improved (MD=-1.39; p=0.02), whereas sleep duration showed no significant change. Subgroup analyses demonstrated that BCT clusters involving goals and planning, feedback and monitoring, and social support were consistently associated with improvements in PA and SB, with comparable effect sizes to overall analyses. Effects on sleep outcomes were limited due to the small number of studies. Conclusion: Behavior change interventions incorporating BCTs effectively increase PA, reduce SB, and improve sleep quality in adults with T2D. BCTs such as goal setting, self-monitoring, feedback, and social support appear particularly beneficial. However, sleep - especially duration - remains underexplored. Future interventions should adopt a 24-hour movement behavior perspective and more explicitly integrate and report BCTs to optimize long-term diabetes management.

Prediabetes is a high-risk dysglycemic state. We used a real-world endocrine/diabetes clinic registry from Najaf, Iraq to characterize patients labeled as having pre-diabetes and to explore factors associated with follow-up engagement. We identified prediabetes visits using keyword-based case finding (English and Arabic terms including prediabetes/pre-diabetes, IFG, IGT, and impaired fasting glucose/tolerance) across semi-structured registry fields. Visit-level data were collapsed to patient-level records. Binary indicators of hypertension, dyslipidemia/statin use, obesity/weight management, smoking, and common glucose-lowering therapies were derived from registry text using keyword/brand-name matching. The primary outcome was follow-up engagement defined as [&ge;]2 recorded visits. The prediabetes subset comprised 242 unique patients and 302 visits. Median age was 45 years (IQR 35-55); 47 patients (19.4%) had [&ge;]2 visits. Median follow-up duration was 0 days (maximum 321). Obesity/weight-management indicators were frequent (71.1%), as were hypertension (43.4%) and dyslipidemia/statin indicators (46.3%). In multivariable logistic regression, no evaluated predictor reached conventional statistical significance for follow-up engagement. Registry enhancements to capture laboratory confirmation and standardized follow-up fields may improve the ability to evaluate diabetes prevention pathways.

ObjectivesDyslipidemia is prevalent among Nigerians living with diabetes, but the rate and extent of treatment have not been well-studied. The objective of this study was to determine the prevalence, treatment rates and control of dyslipidemia among diabetes patients in northern Nigeria. MethodsWe conducted a multicenter, cross-sectional study of diabetes clinic patients. We noted cardiovascular risk factors, lipid-lowering treatments and examination findings, including body mass index, blood pressure, glycated hemoglobin, lipid profile, glomerular filtration rate and urinalysis. Outcome measures were the rate of dyslipidemia, the proportion of patients treated for dyslipidemia, and the proportion of patients with low density lipoprotein cholesterol goal and target for primary prevention of cardiovascular disease. ResultsThe study enrolled 403 participants (58.8% females), of whom 59.6% had dyslipidemia. Female gender and proteinuria were independently associated with dyslipidemia, with odds ratios of 1.74 and 2.26, respectively. Other cardiovascular risk factors of participants were hypertension (56.8%), obesity (52.6%), chronic kidney disease (36.5%), atrial fibrillation (7.9%), heart failure (5.0%), cigarette smoking (4.7%), excess alcohol use (2.0%), and previous cardiovascular disease (14.4%). In those with dyslipidemia, 51.3% took lipid-lowering treatments comprising statins (49.6%), clofibrate (1.7%) and statins combined with clofibrate (1.2%). None took other lipid-lowering treatments beside dietary control, probably due to high costs compared to statins. Only 17.1% of all participants attained the target for primary prevention of cardiovascular disease in people with diabetes. ConclusionMost patients had dyslipidemia, which was more prevalent in females. Only a sixth of all patients had attained the treatment target. Treatment for dyslipidemia was limited to statins and fibrates, contrary to guideline recommendations for the use of ezetimibe, bempedoic acid, icosapent ethyl, or PCSK9 inhibitors for those who failed intensive statin therapy. There is a need for physician adherence to practice guidelines for the treatment of dyslipidemia, and improved access to treatment in northern Nigeria.

Background: Obesity has become increasingly common among US adults with hypertension. However, national data are limited on weight-loss efforts among adults with hypertension and overweight/obesity, and whether these efforts have translated into clinically meaningful weight loss at the population level. Methods: We analyzed repeated cross-sectional data from the National Health and Nutrition Examination Survey, 1999-2023. Adults aged 20 years with hypertension and body mass index 25 kg/m2 were included. Weight-loss attempt was defined as self-report of trying to lose weight during the prior 12 months. Among those attempting weight loss, successful weight loss was defined as 5% or 10% reduction in body weight over the prior year. Survey-weighted logistic regression was used to assess temporal trends and associations between strategies and successful weight loss. Results: Overall, 57.6% reported a weight-loss attempt, increasing from 55.9% in 1999-2000 to 60.4% in 2021-2023 (P for trend=0.002). The most reported strategies were eating less food (65.3%) and exercise (52.4%). Among those attempting weight loss, 33.4% achieved 5% weight loss and 14.7% achieved 10% weight loss; neither improved over time (P for trend=0.976 and 0.174, respectively). Weight-loss surgery was strongly associated with success but was rarely reported (0.35%). Eating less fat and changing eating habits were also positively associated with successful weight loss, whereas skipped meals and use of diet foods or products were inversely associated. Conclusions: Weight-loss attempts increased, but clinically meaningful weight-loss success did not improve, highlighting a persistent gap between effort and outcome in hypertension care.

BackgroundPET-CT scans of radioactive exendin-4, a ligand of the GLP-1 receptor, are claimed to provide a biomarker of pancreatic beta cell mass (BCM), although the GLP-1 receptor is expressed also in the exocrine pancreas (PX). Parotid glands may be a reference tissue for GLP-1 receptor expression in exocrine cells of the GI system. Our aims were 1. To assess biomarker(s) of BCM derived from 68Ga-NODAGA-exendin-4 PET-CT scans in participants with long-standing type 1 diabetes (T1DM) or in subjects with obesity (OBESE); 2. To investigate the relationship between biomarker(s) of BCM and a biomarker of beta cell functional mass (BCFxM) in OBESE. MethodsT1DM (n=8, Age: 50.4{+/-}3.8 yrs; T1DM duration: 34.2{+/-}3.0 yrs; BMI: 26.6{+/-}1.1 kg/m2; HbA1c: 7.5{+/-}0.36%) and OBESE (n=9; Age:48.2{+/-}2.2 yrs; BMI: 37.4{+/-}1.1 kg/m2; HbA1c: 5.4{+/-}0.17%) underwent two studies: 1) 68Ga-NODAGA-exendin-4 PET-CT scan of both PX and parotid glands 45-60 after i.v. injection and with CT-assessment of PX volume to compute biomarkers of BCM based on SUV (BCMSUV) or clearance (CLEAR; BCMCLEAR); 2) Mixed meal test (MMT), with measurement of plasma glucose, C-peptide, GLP-1 and GIP curves to assess BCFxM with state-of-art mathematical modeling. ResultsThe C-peptide response to the MMT in T1DM participants was absent or negligible, whereas the OBESE displayed a robust BCFxM. The PX volume was smaller in T1DM than in OBESE (51.7{+/-}6.6 vs 92.9{+/-}10.9 cc; p=0.007). The biomarkers of BCM, as assessed by 68Ga-NODAGA-exendin-4 SUV or CLEAR, were 6.6-fold (p=0.003) and 5.0-fold (p=0.002) lower, respectively, in T1DM than in OBESE. BCFxM was correlated in OBESE to both biomarkers of BCM (r=0.91 p<0.001, and r=0.82 p=0.006, respectively). Conclusion/interpretation68Ga-NODAGA-exendin-4 derived biomarkers of BCM can discriminate T1DM from OBESE. In OBESE 68Ga-NODAGA-exendin-4 derived BCM appears to be a pivotal determinant of the beta cell response to MMT and may be valuable to compare and monitor BCM both in research and in clinical settings. Research in contextO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIChanges in pancreatic beta cell functional mass are at the heart of alterations in glucose regulation, including diabetes mellitus. Beta cell functional mass can be assessed by mathematical modeling of the in vivo beta cell response to intravenous or oral challenges. C_LIO_LIBeta cell functional mass is the product of beta cell mass times beta cell function per mass unit, i.e. the result of two distinct entities, mass and function. No in vivo methods can dissect out beta cell mass and function. C_LIO_LIPancreatic 68Ga-exendin-4 uptake, as measured by PET-CT, has been proposed as a non-invasive biomarker of beta cell mass. However, the ratio of 3.6:1 between endocrine and exocrine pancreas 68Ga-exendin 4 uptake suggests that there is room for improvement. C_LI What are the key questions?O_LIDoes an improved 68Ga-exendin4 method provide a better separation between participants with type 1 diabetes and expected zero/nil beta cell mass vs people with nondiabetic obesity? C_LIO_LIWhat is the role of beta cell mass in determining beta cell functional mass in people living with obesity? C_LI What are the new findings?O_LIThe improvement in the quantitation of beta cell 68Ga-exendin-4 binding to beta cells resulted in a clearcut separation of participants with type 1 diabetes and expected zero/nil beta cell mass from people living with obesity C_LIO_LIIn people living with obesity, beta cell mass, as assessed by 68Ga-exendin-4 PET-CT scan, is a pivotal determinant of beta cell functional mass, as assessed by mathematical modeling of a frequently sampled mixed meal test C_LI How might this impact on clinical practice in the foreseeable future?O_LIThis method has the potential to track changes in beta cell mass both between-subjects and within-subjects over time C_LIO_LINatural history of glucose (in)tolerance and the impact of disease modifier candidates in diabetes mellitus can be assessed with the present method C_LI

Plantar tissue adaptation during activity is thought to contribute to diabetic foot ulceration (DFU), yet most existing studies only measure compressive quasi-static properties. This pilot study developed an ultrasound-loadcell measurement tool, PlantarSense, and used an infrared thermometer to measure dynamic compressive and shear energy dissipation ratio (EDR) and temperature of plantar-tissue at the first metatarsal head (1stMTH) and calcaneus in people living with and without diabetes at baseline, post-walk, and post-recovery. People living with diabetes showed significantly greater post-walk temperature increases (11.0 % vs 6.9% in controls at calcaneus, p=0.03) and less complete thermal recovery than controls. Baseline compressive EDR at the 1stMTH was significantly higher in people living with diabetes (67.8% vs 56.0% in controls, p=0.04). EDR modulation was greater from shear loading (21.5%) than compression (5.4%) and post-walk induced reductions in EDR were present in all participants, but people living with diabetes showed a 20% lower recovery than controls. Impaired thermoregulation and tissue adaptation in people living with diabetes was demonstrated by plantar temperature and EDR differences in post-walk and post-recovery. Future work is needed to test more participants with a greater range of diabetes progression to quantify statistically significant plantar tissue differences to inform DFU risk management.

ObjectivesAn update to the NICE Type 2 diabetes (T2DM) guideline in February 2022 recommended an SGLT2 inhibitor be offered to people with cardiovascular disease (CVD) or heart failure (HF) as comorbidities and considered for people at high CVD risk. We report uptake of this guideline in England 18 months after its publication. DesignObservational cohort study. SettingGeneral practices contributing to the Clinical Practice Research Data Link, linked to hospital admission records. Participants587,826 people aged over 18 years with T2DM on 1st September 2023, stratified according to their CVD category (CVD only; HF only; CVD and HF; high CVD risk score; low CVD risk score) and chronic kidney disease (CKD) status, and further by age, gender, ethnicity, deprivation, and T2DM diagnosis duration. Main outcome measuresPercentage of patients with a current SGLT2 inhibitor prescription; odds ratios for association between patient characteristics and a current prescription. ResultsIn people with T2DM, the percentage with a current SGLT2 inhibitor prescription was 19.5% for people with CVD, 29.4% for people with HF, 30.5% for people with both CVD and HF, and 19.9% and 20.2% respectively for people at high and low CVD risk. In age-stratified analyses, uptake ordered from lowest to highest was as follows: low CVD risk score, high CVD risk score, CVD only, HF only, CVD and HF. In models adjusted for clinical and patient characteristics uptake was lower in people aged >60, women, Black people, and people living in areas of higher deprivation. ConclusionsWhilst prescribing of SGLT2 inhibitors continues to rise in England, an opportunity remains to increase uptake and to reduce inequalities in people with T2DM in 2026. We report inequalities by ethnicity and deprivation, and lower uptake for people with CVD without HF than people with HF, despite an equal guideline recommendation for these two groups. Additional evidence is needed on the effectiveness of SGLT2 inhibitors in frailer populations. What is already known on this topic?O_LIIn 2020 approximately 10% of people with type 2 diabetes (T2DM) and cardiovascular disease (CVD) and 14% of people with T2DM but without CVD in England had a current SGLT2 inhibitor prescription. C_LIO_LIIn February 2022 NICE recommended that an SGLT2 inhibitor should be offered to people with T2DM with heart failure or CVD, and considered for people with T2DM at high risk of CVD; network meta-analyses have found 10% to 40% lower odds of cardiovascular mortality with treatment in these groups. C_LIO_LIUptake of NICE guidelines in general practice has historically been variable, although higher when accompanied by pay-for-performance schemes such as the Quality and Outcomes Framework. C_LI What this study addsO_LIBy September 2023 the percentage of people with T2DM with a current SGLT2 inhibitor prescription had reached 19.5% in those with CVD as a comorbidity, 30.5% in those with heart failure, and 19.9% in those at high risk of CVD. C_LIO_LIWomen, people of Black ethnicity, and people living in areas of high deprivation had lower odds of a current prescription in analyses adjusted for age, gender, cardiovascular comorbidity, and renal function. C_LI How might these results change the focus of research or clinical practice?O_LIThe results highlight the need for ongoing surveillance of uptake of NICE-recommended treatments for T2DM, and consideration of actions to address barriers to uptake. This is particularly important in the context of broader eligibility for SGLT2 inhibitor treatment in type 2 diabetes in England from 2026. C_LIO_LIThese results support the development of initiatives and quality improvement programmes to improve evidence-based prescribing and address inequalities between clinical and demographic subgroups. C_LI