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Diabetes, Obesity and Metabolism

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Online ISSN: 1463-1326

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Print ISSN: 1462-8902

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Timelines and the evolution of nomenclature from non‐alcoholic fatty liver disease (NAFLD) and management of metabolic dysfunction–associated steatotic liver disease (MASLD). AASLD, American Association for the Study of Liver Diseases; EASL, European Association for the Study of the Liver.
Global prevalence estimates of metabolic dysfunction–associated steatotic liver disease (MASLD). The percentages provided indicate the prevalence of MASLD in the corresponding regions.
Pathophysiology of metabolic dysfunction–associated steatotic liver disease (MASLD). ECM, extracellular matrix; ER, endoplasmic reticulum; HCC, hepatocellular carcinoma; NAFLD, non‐alcoholic fatty liver disease; NASH, non‐alcoholic steatohepatitis; ROS, reactive oxygen species; T2DM, type 2 diabetes mellitus. Source: Reproduced from Wang Y, Fleishman JS, Li T, Li Y, Ren Z, Chen J, Ding M. Pharmacological therapy of metabolic dysfunction–associated steatotic liver disease‐driven hepatocellular carcinoma. Front Pharmacol. 2024;14:1336216. doi: 10.3389/fphar.2023.1336216.
Risk stratification and diagnosis algorithm of metabolic dysfunction–associated steatotic liver disease (MASLD). ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; cT1, liver multi‐scan; CVD, cardiovascular disease; ELF, enhanced liver fibrosis test™; FIB‐4, fibrosis‐4 index; kPa, kilopascals; LSM, liver stiffness measurement; MRE, magnetic resonance elastography; NAFLD, non‐alcoholic fatty liver disease; PNPLA3, patatin‐like phospholipase domain‐containing 3; T2D, type 2 diabetes. Source: Reprinted with permission from Cusi K, Isaacs S, Barb D, et al. American Association of Clinical Endocrinology Clinical Practice Guideline for the Diagnosis and Management of Non‐alcoholic Fatty Liver Disease in Primary Care and Endocrinology Clinical Settings: Co‐Sponsored by the American Association for the Study of Liver Diseases (AASLD). Endocr Pract. 2022;28(5):528–562. Doi: 10.1016/j.eprac.2022.03.010.
(A) Screening criteria for metabolic dysfunction–associated steatotic liver disease (MASLD).⁷ (B) Cardiometabolic criteria for Asian Indian adults. ALD, alcohol‐related liver disease; BMI, body mass index; BP, blood pressure; DILI, drug‐induced liver injury; F, female; HbA1c, glycated haemoglobin; HDL, high‐density lipoprotein; M, male; MetALD, metabolic dysfunction and alcohol‐related liver disease; SLD, steatotic liver disease; WC, waist circumference. Source: (a) Reprinted with permission from Rinella ME, Lazarus JV, Ratziu V, et al. NAFLD Nomenclature consensus group. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. Hepatology. 2023;78(6):1966–1986. Doi: 10.1097/HEP.0000000000000520. Epub 2023 Jun 24.
Management of metabolic dysfunction–associated steatotic liver disease (MASLD)—An expert consensus statement from Indian diabetologists' perspective

June 2025

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Abdul Hamid Zargar

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Anirban Majumdar

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Aims and scope


Diabetes, Obesity and Metabolism is the only interdisciplinary journal for high-quality research and reviews in the areas of diabetes, obesity and metabolism. We focus on clinical and experimental pharmacology and therapeutics in any aspect of metabolic and endocrine disease, either in humans or animal and cellular systems. We also welcome manuscripts reporting on clinical data relating to novel devices, apps, glucose sensors and insulin pumps used to improve glycaemic control.

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Consort flow diagram of RCT illustrating the screening, participation and completion rates for the Mediterranean diet (Med Diet) and AGHE interventions across the eight‐week study. *COVID‐19 related reasons included being symptomatic, caring for a symptomatic person, fear of contracting COVID‐19, and travel restriction inconvenience.
Mediterranean diet vs. the Australian guide to healthy eating (AGHE) on body composition and glucose metabolism: A randomized controlled trial
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June 2025

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Aims The Mediterranean diet has been extensively studied and shown to reduce chronic disease risk. The Australian Guide to Healthy Eating (AGHE) offers a balanced dietary framework tailored to Australian habits, yet its comparative efficacy with the Mediterranean diet remains unexplored. Thus, this study aims to compare the efficacy of the Mediterranean diet with AGHE on body composition and glucose metabolism. Materials and Methods We conducted a randomised controlled trial including 57 participants (median age 31, IQR: 25–37 years; 71.9% female, BMI = 25.1 kg/m²), with 23 participants randomised to the Mediterranean diet and 34 participants to the AGHE diet for eight weeks. Paired t‐tests were employed for within‐group comparisons, and analysis of covariance (ANOVA) was used for between‐group comparisons, adjusted for age and baseline observations. Results The Mediterranean diet intervention resulted in a significant decrease in waist circumference (−1.3 cm, p = 0.043), body fat percentage (−1.8%, p = 0.014), resting metabolic rate (RMR) (−17.9 kcal/day, p = 0.02) and fasting insulin concentration (−1.2 μIU/mL, p = 0.016), along with an increase in body lean mass percentage (1.7%, p = 0.015) compared to the AGHE group. Conclusion The Mediterranean diet demonstrated greater efficacy in improving body composition and maintaining metabolic variables than the AGHE. These findings may support the use of the Mediterranean diet in improving health outcomes related to obesity and metabolic disorders. However, larger, well‐designed clinical trials are needed to confirm these findings and explore underlying mechanisms.


Study dose escalation scheme for (A) Cohort 1 (randomization across placebo, 1‐week, and 2‐week escalation arms for 26 weeks' dosing) and Cohort 2 (additional enrollment to placebo and 2‐week escalation arms for 26 weeks' dosing), and (B) Cohort 3 (randomization across placebo and 4‐week escalation arms for 32 weeks' dosing). BID, twice daily.
Disposition of study participants for (A) Cohorts 1 and 2 and (B) Cohort 3. AE, adverse event; BID, twice daily; LTFU, lost to follow‐up; PD, protocol deviation.
Changes in body weight for danuglipron treatment groups and placebo. (A) Least squares mean percentage changes from baseline at the end of treatment. (B) Least squares mean percentage changes over the duration of treatment.† (C) Proportions of participants with ≥5% reductions in body weight from baseline at the end of treatment. End of treatment was Week 26 for Cohorts 1 and 2 and Week 32 for Cohort 3, and measurements collected after discontinuation of study treatment were censored, representing an “on‐treatment” estimand approach for all 3 panels. A mixed model for repeated measures (MMRM) approach was used for Panels A and B, and Panel C incorporated multiple imputation. †Separate plots showing error bars (90% CIs) are presented for the individual dose groups in Figure S1. BID, twice daily; CI, confidence interval; LS, least squares.
Efficacy and safety of danuglipron (PF‐06882961) in adults with obesity: A randomized, placebo‐controlled, dose‐ranging phase 2b study

Aims This randomized, double‐blind, placebo‐controlled Phase 2b study aimed to assess the efficacy, safety, and tolerability of danuglipron (PF‐06882961), an oral small‐molecule glucagon‐like peptide‐1 (GLP‐1) receptor agonist, in adults with obesity. Materials and Methods Eligible participants (aged 18–75 years; with obesity, without diabetes) were randomized to receive danuglipron or placebo twice daily (BID) for 26 or 32 weeks. Danuglipron was escalated to doses of 40–200 mg BID in 1‐, 2‐, or 4‐week intervals. Assessments included body weight, waist circumference, and safety evaluations. Results Overall, 628 participants were randomized; of 626 receiving study treatment (placebo, n = 90; danuglipron, n = 536), 39.3% completed treatment. Approximately 38% of participants discontinued treatment because of adverse events (AEs) and 22% discontinued for other reasons. The primary endpoint was the change in weight from baseline to the end of treatment; all danuglipron groups demonstrated statistically significant reductions with least squares mean percentage decreases from baseline ranging from −5.0% (90% confidence interval [CI] −6.8%, −3.2%) to −12.9% (90% CI −16.1%, −9.5%) relative to placebo. Danuglipron was considered safe. Consistent with the mechanism, the most frequently reported events were nausea and vomiting, and increased rates of gastrointestinal AEs were generally observed at higher doses. Most events were reported as mild, and no other dose‐related trends were observed in safety endpoints. Conclusions In participants with obesity, danuglipron resulted in statistically significant and clinically meaningful reductions in body weight versus placebo over 26 or 32 weeks. The overall safety profile observed in this study was consistent with expectations for the mechanism, although discontinuation rates due to AEs were higher than anticipated across all treatment groups, including placebo. ClinicalTrials.gov identifier: NCT04707313.


PRISMA selection process of studies for systematic review.
Interaction between dietary omega‐3 polyunsaturated fatty acids, obesity and gut microbiota in preclinical models: A systematic review of randomized controlled trials

Emerging research underscores the potential of omega‐3 polyunsaturated fatty acids (PUFAs) in weight reduction and modulation of the gut microbiota. The current review systematically examines the effects of omega‐3 PUFA supplementation on body weight regulation and gut microbiota modulation in high‐fat diet (HFD)‐induced obesity models. The study protocol was registered with PROSPERO (CRD42024559835). Systematic searches were conducted from database inception to May 2025 on PubMed/Embase, Web of Science and selected reference lists. A total of 32 trials were included, with 25 studies employing a HFD along with dietary omega‐3 PUFA supplementation and 7 studies with a HFD prior to dietary omega‐3 PUFA supplementation. Omega‐3 PUFA interventions consistently demonstrated attenuation of HFD‐induced weight gain and adiposity, though body weight remained elevated compared to low‐fat diet controls. Omega‐3 PUFA supplementation also induced significant gut microbiota compositional changes. Specifically, omega‐3 PUFAs effectively reduced the Firmicutes/Bacteroidetes (F/B) ratio, reversing a hallmark feature of HFD‐induced dysbiosis. Enrichment of beneficial taxa, such as Akkermansia muciniphila, Bifidobacterium and Lactobacillus, was consistently observed, correlating with enhanced short‐chain fatty acid (SCFA) production, improved gut barrier integrity and reduced systemic inflammation. Concurrently, omega‐3 PUFAs suppressed pathogenic bacteria, such as Desulfovibrio and Lachnoclostridium, which are associated with endotoxaemia and metabolic dysfunction. These preclinical evidence suggest the potential of omega‐3 PUFAs as a promising dietary intervention for obesity management through gut microbiota modulation. However, variability in outcomes across studies emphasizes the need for further investigation into the optimal duration, dosage and sources of omega‐3 supplementation. Moreover, the synergistic effects of omega‐3 PUFA supplements and lifestyle interventions, such as high‐intensity interval training (HIIT), which further regulates microbial composition and improves metabolic outcomes, are also highly promising.


Identification of eligible patients for inclusion. ADI, area deprivation index; AOM, anti‐obesity medication; BMI, body mass index; EHR, electronic and health records; MBS, metabolic and bariatric surgery.
Socio‐demographic and clinical factors associated with the receipt of anti‐obesity medication prescriptions and metabolic and bariatric surgery among eligible all of Us participants

June 2025

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10 Reads

Aims There is a paucity of data on socio‐economic characteristics associated with the use of anti‐obesity medications (AOM) and metabolic and bariatric surgery (MBS) when accounting for clinical factors. This study characterized factors associated with the receipt of AOM prescriptions and MBS. Materials and Methods A cross‐sectional study was conducted using the All of Us (AoU) Research (v.8) data. Patients with obesity who received AOM or MBS between 2017 and 2023 were included. Descriptive statistics were used to summarize patient characteristics, while multivariable regression examined factors associated with the receipt of the treatments. Results Only 6.6% of 183 424 patients for AOM analysis, received an AOM prescription, while 1.8% underwent MBS among 93 146 patients. Being a man (vs. woman, adjusted odds ratio [aOR] = 0.62, 95% confidence interval [CI], 0.59–0.65), Medicare insurance holder (vs. private, aOR = 0.78, 95% CI, 0.72–0.84), retiree (vs. employed, aOR = 0.70, 95% CI, 0.66–0.75) and high school degree holders (vs. college, aOR = 0.85, 95% CI, 0.80–0.90) were associated with lower odds of receiving AOM. Being single (vs. married, aOR = 0.84, 95% CI, 0.74–0.96), retired (vs. employed, aOR = 0.63, 95% CI, 0.49–0.80), with body mass index (BMI) 35‐ < 40 (vs. ≥45, aOR = 0.13, 95% CI, 0.11–0.15) were associated with lower odds of MBS. Patients with dyslipidaemia and obstructive sleep apnoea had higher odds of receiving both treatments. Conclusions Disparities in obesity treatment exist. Male sex, older age, lower income and lower BMI were associated with lower odds of treatment, while dyslipidaemia and obstructive sleep apnoea were associated with higher odds.


Stages of type 1 diabetes with the estimated proportion of undiagnosed young children in each stage and the estimated risk of progression to Stage 3b (insulin requirement). Adapted from Insel et al.¹ and Ziegler et al.³
Proportion of new type 1 diabetes cases by age group. Adapted from Thomas et al.¹⁷
Annual incidence of type 1 diabetes amongst children and adolescents aged 0–19 years by region. Source: Data from tab. 1: *Ogle et al.⁶ and fig. 1: Hormazábal‐Aguayo et al.⁹ IDF, International Diabetes Federation.
The Changing Epidemiology of Type 1 Diabetes: A Global Perspective

June 2025

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9 Reads

The prevalence of type 1 diabetes is increasing, with significant implications for public health systems worldwide. This review provides a global overview of the current epidemiology of type 1 diabetes, examining the trends, risk factors, and regional variations in incidence. We explore the influence of genetic, environmental, and socio‐economic factors on the rising incidence of type 1 diabetes. The review also highlights temporal trends in the management of type 1 diabetes and the risk of mortality and morbidity from acute and long‐term complications, including hypoglycaemia, diabetic ketoacidosis, and retinopathy. By synthesizing global and regional data, we aim to provide valuable insights for local health service planning, disease prediction, and tailored interventions. This article underscores the importance of continued research into the epidemiology of type 1 diabetes to better inform prevention, treatment, and management strategies of this growing global health challenge. Plain Language Summary Type 1 diabetes (T1D) is an autoimmune condition that begins silently, with the body attacking insulin‐producing cells in the pancreas. This process occurs in two early, silent stages, detectable through blood tests for antibodies, before symptoms appear. It eventually progresses to stage 3, when symptoms develop and insulin treatment becomes necessary. Prevalence T1D affects about 9 million people globally, including over 1.5 million children. In addition to those with symptoms, many children and adults may unknowingly have early stage T1D. These can be detected through screening and are estimated to affect around 0.3% of the population. Incidence In 2024, there were over 500,000 new diagnoses of T1D worldwide, with cases increasing each year. Rates vary by region, age, and sex. Most diagnoses occur in childhood or early adulthood, with a peak around puberty, though it can develop later in life. Rates are highest in high‐income countries such as Finland and Australia. Lower rates in other regions may reflect limited surveillance. Some countries have reported fluctuating trends, possibly linked to infections. Improved awareness and diagnostics explain and changing risk factors may also play a role. Risk Factors The risk of T1D is impacted by genetic, demographic, and environmental factors. Family history increases risk, though the majority of people diagnosed don’t have a family history. Genetic risk scores can also help identify children at higher risk. Risk changes with age, early signs often appear before age 3, and younger children tend to progress more quickly. Two childhood diagnosis peaks occur at ages 4–7 years and 10–14 years. Researchers are exploring possible subtypes of T1D based on age and disease behaviour. White European populations have the highest rates, but increases are also seen in other groups. Environmental factors like viral infections, caesarean birth, and early diet are being studied. Complications Managing T1D is complex, however poor control can lead to short‐term emergencies like hypoglycaemia or diabetic ketoacidosis (DKA), and long‐term complications affecting the eyes, kidneys, and nerves. In recent decades, treatment has improved with better insulin regimens and technologies such as insulin pumps, continuous glucose monitors, and hybrid closed‐loop systems. These reduce complications and improve quality of life. Yet challenges remain, including high DKA rates at diagnosis—especially in young children and ethnic minorities, and high diabetic retinopathy rates that can impact vision. Early, tight glucose control reduces long‐term risks, but people with T1D still face a higher risk of early death. Future Research Directions Major research gaps remain, especially in low‐ and middle‐income countries. Data on early‐stage and adult‐onset T1D is limited but improving. As new therapies emerge, like teplizumab which is used to delay progression to stage 3, disease patterns may shift. Long‐term data from modern technologies is still developing, with linked administrative data offering a promising solution. Conclusion T1D is rising globally and still carries serious health risks. Understanding who is affected, when, and how the disease progresses is essential to improving prevention, care, and outcomes.



Weight and waist reduction efficacy estimand indirect treatment comparison (ITC) results. Forest plots for efficacy estimand ITC results comparing tirzepatide (10 and 15 mg once per week [QW]) versus semaglutide 2.4 mg QW for change from baseline (CfB) in weight (kg), CfB in weight (%) and CfB in waist circumference (cm). The point indicates the mean difference (MD) and the lines indicate the 95% confidence intervals (CIs). Point estimates to the left of the dotted line indicate where tirzepatide was associated with an improvement over semaglutide, and statistical significance is indicated where the 95% CIs do not overlap the dotted line.
Diabetes and glycaemic parameters efficacy estimand indirect treatment comparison (ITC) results. Forest plots for efficacy estimand ITC results comparing tirzepatide (10 and 15 mg once per week [QW]) versus semaglutide 2.4 mg QW for change from baseline (CfB) in glycated haemoglobin (HbA1c) (%) and CfB in fasting plasma glucose (FPG) (mmol/L). The point indicates the mean difference (MD) and the lines indicate the 95% confidence intervals (CIs). Point estimates to the left of the dotted line indicate where tirzepatide was associated with an improvement over semaglutide, and statistical significance is indicated where the 95% CIs do not overlap the dotted line.
Indirect comparative efficacy and safety of tirzepatide 10 and 15 mg versus semaglutide 2.4 mg for the management of obesity and overweight in patients with type 2 diabetes

June 2025

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3 Reads

Aims This indirect treatment comparison (ITC) compared the efficacy and safety of tirzepatide with semaglutide for managing obesity or overweight in participants with type 2 diabetes (T2D), informed by the pivotal trials SURMOUNT‐2 and STEP 2. Materials and Methods Participants had body mass index (BMI) ≥ 27 kg/m², with ≥1 unsuccessful prior dietary weight reduction effort and glycated haemoglobin (HbA1c) 7%–10% on stable therapy. A heterogeneity assessment confirmed that study and patient baseline characteristics were similar. Bucher ITCs compared tirzepatide 10 and 15 mg once‐weekly (QW) to semaglutide 2.4 mg QW via placebo, all adjunct to a reduced‐calorie diet and increased physical activity. Results Tirzepatide 10 and 15 mg were associated with statistically significant greater reductions in weight, BMI and HbA1c versus semaglutide. Tirzepatide 15 mg was associated with statistically significant greater odds versus semaglutide of ≥5% and ≥15% weight reduction and statistically significant improvements in several cardiometabolic risk factors, including waist circumference, fasting plasma glucose and triglycerides. Both tirzepatide doses showed non‐significant trends of greater improvements in high‐density lipoprotein, low‐density lipoprotein, systolic blood pressure and diastolic blood pressure versus semaglutide as well as a generally comparable safety profile to semaglutide. Conclusions In this ITC versus semaglutide 2.4 mg, tirzepatide 10 and 15 mg were associated with statistically significant greater weight, BMI and HbA1c reduction and tirzepatide 15 mg with statistically significant improvements in multiple cardiometabolic risk factors crucial in managing obesity or overweight among patients with T2D. Both tirzepatide doses also had a generally similar safety profile to semaglutide. Plain Language Summary What is the context and purpose of this research study? Excess weight and type 2 diabetes (T2D) are strongly connected, where most patients with T2D have obesity or overweight. Weight management is crucial for improving T2D outcomes and preventing its progression. Weight management comprises behavioural interventions, psychological support, dietary changes and physical activity programmes. Medications may also be prescribed or surgical options may also be considered. Two such medications for weight management are tirzepatide (up to 15 mg) and semaglutide (up to 2.4 mg), which are injected subcutaneously once per week to help control appetite by prolonging patients' feeling of fullness. These medications are also used at different doses to treat T2D. Because there were no clinical trials directly comparing tirzepatide and semaglutide, particularly in patients with both T2D and either obesity or overweight, this study aimed to indirectly compare the effectiveness and safety of tirzepatide and semaglutide for weight management in patients with overweight or obesity and T2D. What was done? We indirectly compared the efficacy and safety of two doses of tirzepatide (10 and 15 mg per week) versus semaglutide 2.4 mg per week for weight management in adults with both T2D and either obesity or overweight. We used data from two large clinical trials, SURMOUNT‐2 and STEP 2, which tested tirzepatide and semaglutide, respectively, against a placebo, all adjunct to diet and exercise. An indirect treatment comparison of tirzepatide and semaglutide was then possible via the placebo arm acting as the common comparator. The similarity of study design and patient populations in the two trials was evaluated and found to be sufficiently close to allow meaningful comparisons. Appropriate statistical methodology was used to facilitate comparisons of the two trials. What were the main results? Compared to semaglutide 2.4 mg, the higher dose of tirzepatide (15 mg) was associated with a statistically significant improvement in several outcomes such as weight reduction, glycaemic outcomes and triglycerides, while the lower dose of tirzepatide (10 mg) was associated with some statistically significant improvements (e.g., weight reduction and HbA1c) and had otherwise comparable outcomes to semaglutide. However, both doses of tirzepatide were associated with statistically significant greater reductions in glycated haemoglobin A1c (HbA1c) compared to semaglutide, which is a key target of T2D treatment. Both doses of tirzepatide had a generally similar safety profile compared to semaglutide. What is the originality and relevance of this study? Currently, there are no clinical trials that compare tirzepatide and semaglutide directly for the management of obesity and overweight in patients with T2D. Previous studies have compared tirzepatide and semaglutide results from different clinical trials for weight management in patients without T2D, not specifically focusing on patients with T2D. This is the first study to indirectly compare tirzepatide and semaglutide for weight management in people with T2D who also have obesity or overweight. The findings of this study suggest that higher doses of tirzepatide may be more effective than semaglutide for weight reduction and improving other health‐related outcomes in these patients.


Cox proportional hazards model showing the risk of developing diabetic ketoacidosis by (A) use of sodium‐glucose cotransporter 2 inhibitor (SGLT2i) and (B) by use of SGLT2i and HbA1c level at baseline.
Bivariate Cox proportional models showing the effect of sodium‐glucose cotransporter 2 inhibitor (SGLT2i) on the incidence of diabetic ketoacidosis within each subgroup of interest. Hazard ratios and 95% confidence intervals are shown. BMI, body mass index; eGFR, estimated glomerular filtration rate; UACR, urinary albumin creatinine ratio.
Predictors of diabetic ketoacidosis in patients with insulin‐deficient diabetes phenotype initiating SGLT2 inhibitors

June 2025

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2 Reads

Aims To identify predictors of diabetic ketoacidosis (DKA) in patients with an insulin‐deficient phenotype initiating sodium‐glucose cotransporter 2 inhibitor (SGLT2i) therapy. Materials and Methods This retrospective cohort study analysed data from 31 900 patients with diabetes aged 18–70 identified as having an insulin‐deficient phenotype. After applying inclusion and exclusion criteria, patients were matched and divided into SGLT2i users (n = 6572) and non‐users (n = 6382). The primary endpoint was the first DKA event in patients with no prior history of DKA. Independent risk factors for DKA were assessed using Cox regression. Results Over a median follow‐up of 4.4 years, 239 patients experienced DKA (143 [2.22%] SGLT2i users vs. 96 [1.54%] non‐users; HR [95% confidence interval, CI] 1.39 [1.07–1.79]; p = 0.014). The adjusted model confirmed an increased DKA risk with SGLT2i use (adjusted hazard ratio, aHR [95% CI] 1.50 [1.15–1.95]; p = 0.003). Baseline HbA1c >9% was associated with a 53% higher risk (aHR [95% CI] 1.53 [1.18–1.99]; p = 0.0016), while body mass index (BMI) ≤25 kg/m² was linked to a 61% increased risk (aHR [95% CI] 1.61 [1.24–2.09]; p = 0.0003). Insulin use further heightened risk (aHR [95% CI] 2.35 [1.71–3.23]; p < 0.0001). Conclusions SGLT2i use in patients with an insulin‐deficient phenotype is associated with increased DKA risk, particularly in those with HbA1c >9% and BMI ≤25 kg/m². Clinicians should exercise caution in these patients, carefully assessing risks and implementing mitigation strategies to ensure safe use.


Flow chart of the selection of the study populations. AGEs, advanced glycation end products; MVD, microvascular dysfunction.
Mediation diagram showing the total and direct effects of type 2 diabetes on incident clinically relevant depressive symptoms, and the indirect effect by the microvascular dysfunction score (composite score of venular and arteriolar dilatation, blood biomarkers of microvascular dysfunction and urinary albumin excretion) (A), the neurodegeneration composite score (total retinal thickness and brain parenchyma volume) (B), the low‐grade inflammation score (C), the AGEs composite score (plasma AGEs and skin autofluorescence) (D), the arterial stiffness composite score (carotid distensibility coefficient and pulse wave velocity) (E). Explanation: The total effect indicates the association between type 2 diabetes and the hazard of incident clinically relevant depressive symptoms after adjusting for MVD composite score, neurodegeneration composite score, low‐grade inflammation score, AGEs composite score or arterial stiffness composite score; pathway A the difference per higher SD of MVD composite score, neurodegeneration composite score, low‐grade inflammation score, AGEs composite score or arterial stiffness composite score between individuals with and without type 2 diabetes; pathway B the association between a higher SD of MVD composite score, neurodegeneration composite score, low‐grade inflammation score, AGEs composite score or arterial stiffness composite score and the hazard of incident clinically relevant depressive symptoms; the direct effect the association between type 2 diabetes and the hazard of incident clinically relevant depressive symptoms without adjusting for MVD composite score, neurodegeneration composite score, low‐grade inflammation score, AGEs composite score or arterial stiffness composite score; and the indirect effect the mediation effect by MVD composite score, neurodegeneration composite score, low‐grade inflammation score, AGEs composite score or arterial stiffness composite score in the association between type 2 diabetes and incident clinically relevant depressive symptoms. Pathway A is expressed as standardized regression coefficient (β) with corresponding 95% confidence interval and all other effects are expressed as hazard ratio (HR) and corresponding 95% confidence interval. N = 6091 for the microvascular dysfunction composite score, N = 5236 for the neurodegeneration composite score, N = 2487 for the low‐grade inflammation score, N = 5548 for the AGEs composite score, N = 5053 for the arterial stiffness composite score. HR, Hazard ratio; MVD, microvascular dysfunction.
Type 2 diabetes and depression via microvascular dysfunction, neurodegeneration, inflammation, advanced glycation end products (AGEs), arterial stiffness

Aims Type 2 diabetes increases the risk of depression, but the mechanisms underlying this association are incompletely understood. We investigated whether microvascular dysfunction, neurodegeneration, low‐grade inflammation, advanced glycation end products (AGEs) and arterial stiffness, pathologies that are more common in diabetes, explain, or mediate the association between type 2 diabetes and incident clinically relevant depressive symptoms. Materials and Methods We used prospective data from The Maastricht Study, a population‐based cohort study. Diabetes status and potential mediators were assessed at baseline. Clinically relevant depressive symptoms (PHQ‐9 score ≥10) were assessed at baseline and each year during a median of 8.1 (IQR 4.2, 10.1) years of follow‐up. Mediation analysis was employed to investigate the mediating effect of microvascular dysfunction (retinal, blood and MRI biomarkers), neurodegeneration (retina and MRI biomarkers), low‐grade inflammation (blood biomarkers), AGEs (skin and blood biomarkers) and arterial stiffness (tonometry and ultrasound biomarkers). Results Data of 6091 participants (age, 59.4 years [SD 8.6]; 51.3% women; 23.6% type 2 diabetes) were available. Type 2 diabetes was associated with a higher incidence of clinically relevant depressive symptoms (HR:1.37; 95% CI 1.13, 1.65). This association was partly mediated by microvascular dysfunction (proportion mediated:10.4% [95% CI:3.6%, 17.2%]); neurodegeneration (proportion mediated:12.1% [95% CI: 3.9%, 20.3%]); AGEs (proportion mediated:5.4% [95% CI: 3.0%, 8.8%]); and arterial stiffness (proportion mediated:8.4% [95% CI: 3.3%, 13.5%]); but not by low‐grade inflammation. Conclusions The association between type 2 diabetes and a higher risk of clinically relevant depressive symptoms is partly mediated by microvascular dysfunction, neurodegeneration, AGEs and arterial stiffness.



Restricted cubic spline (RCS) for the associations between systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure and gestational diabetes mellitus (GDM). The lines represent odds ratios (ORs, solid lines) and 95% confidence intervals (CI, long dashed lines) after multivariable adjustment for maternal age (continuous, years), gestational age (continuous), pre‐pregnancy BMI (<18.5, 18.5–24, ≥24 kg/m²), parity (0, ≥1), physical activity (low, moderate and high), smoking status (never, ever, current), alcohol consumption (never, ever, current), exposure to secondhand smoke during pregnancy (yes and no) and family history of diabetes (yes and no) based on the RCS models for SBP, DBP and PP. The reference values (OR = 1) were set at the 10th percentiles, and the knots were set at 10th, 50th and 90th percentiles of SBP, DBP and pulse pressure. The histograms represent the distribution of concentrations of blood pressure in our study.
Different systolic blood pressure trajectories throughout pregnancy. Among 14 990 pregnant women included in our study, four different systolic blood pressure trajectories throughout pregnancy from early pregnancy registration to 20 weeks of gestation were identified. Solid lines show class‐specific mean predicted gestational systolic blood pressure levels as a function of gestational week estimated from the best fitting growth mixture model (4‐class quadratic latent class growth mixture modelling). Dashed lines indicate estimated 95% confidence intervals of gestational systolic blood pressure. Class 1 was the peak blood pressure group (n = 396, 2.6%), class 2 was the medium and high‐stable blood pressure group (n = 3904, 26.0%), class 3 was the medium‐stable blood pressure group (n = 7110, 47.4%), and class 4 was the low‐stable blood pressure group (n = 3580, 24.0%).
Association between early pregnancy blood pressure characteristics and the risk of incident GDM in pregnant women across different maternal age, parity, pregnancy weeks and pre‐pregnancy BMI groups. Model adjusted for the variables in maternal age (continuous, years) gestational age (continuous, weeks), parity (0, ≥1), physical activity (low, moderate and high), smoking status (never, ever, current), alcohol consumption (never, ever, current), exposure to secondhand smoke during pregnancy (yes and no), and family history of diabetes (yes and no).
Gestational diabetes risk associated with early pregnancy blood pressure characteristics and trajectories: A Chinese prospective cohort study

Background Limited evidence exists regarding early pregnancy pulse pressure (PP) and blood pressure (BP) trajectories in gestational diabetes mellitus (GDM) development. Understanding these associations may provide valuable insights for early interventions to mitigate the risk of GDM. Methods Included were 16 020 pregnant women from the Shenzhen Maternity and Child Healthcare Hospital. Early pregnancy BP characteristics were determined based on BP measurements recorded at the initial prenatal visit, including systolic blood pressure (SBP), diastolic blood pressure (DBP), and PP. Early pregnancy SBP trajectories up to 20 weeks' gestation were identified using latent class growth mixture models (LCGM) based on multiple prenatal visits. Multivariate logistic regression analyses were performed to assess the association between early pregnancy BP characteristics and SBP trajectories with the risk of GDM. Results Among participants, 23.91% (3830/16 020) developed GDM. Moderate BP (SBP 120–139 mmHg and/or DBP 80–89 mmHg) was associated with elevated GDM risk (OR = 1.24, 95% CI 1.14–1.35), with isolated moderate SBP (120–139 mmHg) demonstrating a stronger association (OR = 1.27, 95% CI 1.16–1.38), while early pregnancy hypertension conferred an additional 32% risk elevation (OR = 1.32, 95% CI 1.02–1.71). Linear associations were observed for SBP (each 10 mmHg increase: OR = 1.14, 95% CI 1.10–1.18), DBP (each 5 mmHg: OR = 1.07, 1.05–1.09), and PP (each 5 mmHg: OR = 1.04, 1.02–1.07) with GDM risk. The highest PP tertile demonstrated a 20% elevated risk versus the lowest (OR = 1.20, 1.09–1.32). Trajectory analysis revealed four distinct SBP patterns, with escalating risks: medium‐stable (OR = 1.31), medium‐high stable (OR = 1.61), and peak pattern (OR = 1.98) compared with low‐stable reference (all p < 0.01). Conclusions Poor early pregnancy BP characteristics and unfavourable BP trajectories are associated with an elevated risk of GDM. These findings suggest that monitoring BP throughout early pregnancy could serve as an essential strategy for identifying women at higher risk for GDM, potentially enabling timely preventative measures.


Percentage of time in range of 70–180 mg/dL between two intervention phases. The x‐axis represents the weeks since randomization, divided into weekly intervals starting from a run‐in period. The y‐axis denotes the mean percentage of TIR (70–180 mg/dL[3.9–10.0 mmol/L]) for 24 h/day. The blue line represents the SAP phase, while the orange line represents the AAPS phase. Error bars indicate the standard deviation from the mean for each weekly measurement. The graph illustrates the glycaemic benefit of AAPS over SAP, with a favourable effect that is apparent within one week of AAPS initiation and sustained throughout the 12‐week intervention period. AAPS, Android artificial pancreas system; SAP, sensor‐augmented pump; TIR, time in range.
Efficacy and safety of a tubeless open‐source hybrid automated insulin delivery use at home among adults with type 1 diabetes mellitus: Results from a 26‐week, free‐living, randomized crossover trial
Mengyun Lei

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Ping Ling

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Beisi Lin

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[...]

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Wen Xu

Aim This study aims to evaluate the efficacy and safety of a tubeless open‐source hybrid automated insulin delivery (OS‐AID) in managing adults with type 1 diabetes mellitus (T1DM) in China, where commercial AID systems are not accessible. Methods In this open‐label randomized crossover study, adults with T1DM aged 18–75 years, glycated haemoglobin (HbA1c) 7%–11% (53‐97 mmol/mol) and who have never used AID previously, were assigned to either Android‐version hybrid OS‐AID (AAPS) or sensor‐augmented insulin pump (SAP) therapy for three months, followed by a crossover to the alternative treatment for an additional three months. The primary endpoint was the percentage of time in range (TIR, 70‐180 mg/dL [3.9–10.0 mmol/L]) during the final two weeks of each treatment phase. Results A total of 28 adults with T1DM, with a mean age of 33.6 ± 10.4 years and a T1DM duration of 12.6 ± 7.0 years, were enrolled in this study. The percentage of TIR (70‐180 mg/dL [3.9–10.0 mmol/L]) during the AAPS phase was 75.6 ± 10.3%, significantly higher than the 60.4 ± 15.1% observed during the SAP phase (p < 0.01). AAPS was notably more effective in managing nocturnal glucose levels compared to diurnal glucose levels (80.9 ± 13.6% vs. 73.8 ± 10.2%, p < 0.01). No significant differences in time below range were observed between the two phases. No severe hypoglycaemia or serious adverse events occurred in either treatment phase. Conclusion In this 26‐week trial involving adults with T1DM who had never previously used AID, the tubeless AAPS use at home resulted in a significantly higher percentage of time in the target glucose range without increasing hypoglycaemia risk compared to SAP therapy.


AdipoRon attenuates steatosis, inflammation and fibrosis in murine diet‐induced NASH via inhibiting ER stress

Aim The rising global prevalence of obesity has accelerated the incidence of metabolic dysfunction‐associated steatotic liver disease (MASLD), with nonalcoholic steatohepatitis (NASH) representing its progressive and life‐threatening phenotype. Despite its clinical urgency, no pharmacotherapy is currently approved for NASH. AdipoRon, an orally active adiponectin receptor agonist, exhibits dual regulatory effects on glucose/lipid homeostasis alongside anti‐inflammatory and antioxidant properties. However, its therapeutic potential in metabolic stress‐driven NASH remains underexplored. This study elucidates the efficacy and molecular mechanisms of AdipoRon in mitigating metabolic stress‐induced NASH. Materials and Methods We employed a multi‐modal approach combining in vitro and in vivo models: palmitic acid (PA)‐challenged alpha mouse liver 12 (AML12) hepatocytes and mice fed a Western diet (WD) or a methionine‐choline‐deficient (MCD) diet. Proteomic profiling integrated with bioinformatics analysis was utilized to dissect AdipoRon's mechanism. Pharmacological validation via endoplasmic reticulum (ER) stress modulation (e.g., cinchonine) further clarified pathway specificity. Results In vitro, AdipoRon attenuated PA‐induced lipid accumulation and inflammatory cytokine release in hepatocytes. In vivo, AdipoRon administration markedly reduced hepatic injury, steatosis, lobular inflammation and collagen deposition in diet‐induced NASH mice. Mechanistically, proteomic analysis identified ER stress suppression as a central pathway, with rescue experiments confirming that cinchonine (an ER stress activator) abrogated AdipoRon's hepatoprotection. Conclusions Our findings establish AdipoRon as a potent inhibitor of ER stress, effectively counteracting metabolic stress‐induced NASH pathogenesis. These results highlight its translational promise as a targeted therapy for NASH, addressing critical unmet clinical needs.


Flow chart of data screening.
Body mass index (BMI) trajectories groups from 2012 to 2022. (A) Trajectories of group with underweight; (B) trajectories of group with normal weight; (C) trajectories of group with overweight; (D) trajectories of group with obesity.
Trajectories of body mass index and diabetes mellitus risk among elderly Chinese adults: A 10‐year longitudinal study

Aims This study aimed to identify trajectories of body mass index (BMI) for elderly Chinese adults, evaluate the impact of BMI trajectories on the risk of diabetes mellitus (DM) or impaired fasting glucose (IFG) among normoglycaemic elderly and compare the incidence of progression to DM and reversion to normoglycaemia between BMI trajectories among IFG elderly to prevent the occurrence of diabetes. Materials and Methods This study included 148 970 participants. Group‐based trajectory modelling was used to identify BMI trajectories. Cox proportional hazards regression models were used to examine the associations between BMI trajectories and the incidence of DM, IFG and reversion to normoglycaemia. Results A total of six patterns of trajectory were identified: minor decrease, sharply decrease, stable, slight increase, moderate increase and significant increase among 148 970 elderly Chinese adults. For normoglycaemic elderly, compared with normal weight‐stable trajectory, the trajectories with higher DM risk are the obese‐pronounced decrease group, the obese‐marginal increase group, and the obese‐minor decrease group. The adjusted hazard ratios (HRs) were: 2.70 (95% confidence interval [CI]: 2.35, 3.11), 2.55 (95% CI: 2.28, 2.86) and 2.41 (95% CI: 2.24, 2.60), respectively. The trajectories with higher IFG risk are the obese‐marginal increase group, the obese‐minor decrease group and the overweight‐moderate increase group, with adjusted HRs of 2.26 (95% CI: 2.08, 2.45), 1.96 (95% CI: 1.86, 2.07) and 1.91 (95% CI: 1.79, 2.04), respectively. Conclusions Among 148 970 participants, normoglycaemic elderly with increased BMI trajectories showed elevated DM and IFG risks in groups with underweight and normal weight. Regardless of the BMI trajectory, the risk of DM was increased in both the obese and overweight groups. For IFG elderly, the highest DM incidence was presented in the decreasing trajectories.


Senescence and oxidative stress markers. Markers of (A) senescence and (B) oxidative stress at gestational Weeks 14–16, 22–24, 36–38‐ and 5‐year follow‐up between women who subsequently developed GDM (blue) and controls (red). Data, presented as relative expression, are shown as estimated marginal means and 95% confidence intervals (coloured area) from linear mixed model analysis adjusting for age and BMI. The adjusted p‐values (*) represent expression levels comparing the markers between GDM and controls at each timepoint, 22–24 and 36–38, from the linear mixed model analysis. *p < 0.05; **p < 0.01 and ***p < 0.001.
Associations between senescence/oxidative stress markers and CVD risk markers. (A) Associations between AOPP, β‐galactosidase, XRN1, DCP2, TERC and glucose metabolism and lipoprotein ratios at gestational weeks 14–16, 30–32‐ and 5‐year follow‐up in the total cohort. Scatterplot showing the association between (B) AOPP, β‐galactosidase and β‐cell function and (C) AOPP, β‐galactosidase and TG/HDL‐C ratio in controls (blue) and GDM (red) at 14–16 weeks gestation. Scatterplot showing the association between (D) XRN1, DCP2 and PWV and (E) XRN1, DCP2 and β‐cell function in controls (blue) and GDM (red) at 5‐year follow‐up. r = correlation coefficient, *p < 0.05; **p < 0.001.
Structural equation models (SEM) for biological markers and GDM. Circle plots based on SEMs showing association between normalized levels (i.e., log/SD) of markers for glucose homeostasis, demographic factors, senescence, oxidative stress and dyslipidemia early (14–16 weeks) in pregnancy and later diagnosis of GDM. (A) shows unfiltered associations between variables while (B) shows filtered associations (p < 0.1). The interaction edges (i.e., width) are made based on the weight of the relationship between variables. A submerged edge indicates the origin of the association and if two variables have non‐submerged edges the association goes both ways. In (C), the association between markers in B and GDM were assessed by univariate and stepwise multivariable logistic regression. R² refers to Nagelkerke R². R² of the final multivariable model was 0.53. (D) Potential model for interaction between senescence and oxidative stress in immune cells, lipids and glucose homeostasis and GDM.
Oxidative stress, senescence and mRNA decay in peripheral blood mononuclear cells of women with gestational diabetes mellitus‐link to increased cardiovascular disease risk

Aims Women who develop gestational diabetes mellitus (GDM) have a pancreatic β‐cell defect that cannot compensate for the insulin resistance of pregnancy. The glucose intolerance may, in addition to direct effects, negatively impact lipid metabolism, promote vascular dysfunction and contribute to cardiovascular disease (CVD). We assessed associations between oxidative stress and senescence markers with indices of glucose and lipid metabolism in women developing GDM and with CVD risk after 5 years. Materials and Methods The oxidative stress and senescence markers NRF2, GPX4, TERC, XRN1 and DCP2 were assessed in peripheral blood mononuclear cells (PBMCs), advanced oxidation protein products (AOPP) and β‐galactosidase in plasma, from healthy (n = 253) and women with GDM (n = 31) during pregnancy and at 5‐year follow‐up, from the STORK study. We investigated their associations with established markers of disease activity and later CVD. Results Plasma AOPP and β‐galactosidase were increased early in pregnancy in women developing GDM later and associated with indices of glucose metabolism and TG/HDL‐Cholesterol. RNA levels of transcripts involved in telomer maintenance and antioxidant responses were decreased in women with GDM during pregnancy and at follow‐up. DCP2 and XRN1 expression were positively associated with β‐cell function at all timepoints and with pulse wave velocity at 5‐year follow‐up in women with previous GDM. Conclusions Markers of vascular oxidative stress and senescence are increased and correlate with indices of glucose and lipid metabolism early in pregnancy in women developing GDM. Cellular markers reflecting attenuated defence against oxidative stress and senescence decrease throughout pregnancy and at 5‐year follow‐up and correlate with aortic stiffness in women with previous GDM.


Changes in HbA1c and weight from enrollment to 2 years in key subgroups. (A) Mean HbA1c (%) at enrollment and 2 years for the full cohort and by baseline HbA1c category (<8% vs ≥8%). (B) Mean body weight (lbs) at enrollment and 2 years for the full cohort and by ketone adherence group, defined by average blood ketone levels during the first 6 months of care. Value labels at each time point indicate the mean for each group. Values displayed to the right of each line represent the absolute change in HbA1c (panel A) or the percent change in body weight (panel B) from enrollment to 2 years. The full set of subgroup analyses is provided in Data S2. HbA1c indicates hemoglobin A1c.
Sustained metabolic improvements in a remotely delivered ketogenic nutrition programme for veterans with type 2 diabetes: A 3‐year observational study

June 2025

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3 Reads

Aim To evaluate the long‐term effectiveness and safety of a remote, medically supervised ketogenic nutrition therapy intervention for Veterans with type 2 diabetes (T2D). Materials and Methods This retrospective observational analysis examined de‐identified medical records of Veterans with T2D who engaged in a remote continuous care intervention. Outcomes were HbA1c, weight, diabetes medication use and cardiometabolic markers (lipids, liver enzymes, kidney function) among those who remained enrolled for 2 or 3 years. Separately, we assessed weight, glucose and medication changes at programme departure among Veterans who discontinued before 2 years. Outcomes were analysed across subgroups. Linear mixed‐effects models and paired t‐tests evaluated changes over time. Results Among 640 enrolled Veterans (mean age: 59 years, BMI: 35 kg/m², HbA1c: 8.4%), 310 (49%) remained engaged at 2 years and 197 (33%) at 3 years. At both time points, HbA1c was reduced by approximately 0.8%, alongside decreases in diabetes medication use. Weight decreased by approximately 9% at both 2 and 3 years. Overall, reductions in HbA1c and weight were seen across subgroups. Veterans who discontinued before 2 years experienced metabolic improvements, with greater benefits among those enrolled at least 6 months. Conclusions For US Veterans, long‐term participation in a remote ketogenic nutrition therapy intervention was associated with sustained improvements in glycaemic control, weight, medication use and select cardiometabolic markers. A 0.8% HbA1c reduction is associated with meaningful reductions in diabetes‐related complications, highlighting the potential clinical relevance of these findings.


OGTT curve of (A) glucagon‐like peptide‐1 (GLP‐1), (B) GIP, (C) PYY, (D) glucagon, before (black) and after (white) intervention with obesity surgery (circles) and low‐energy diet (LED) (squares). Statistical comparisons of the AUCs are reported in Table 1.
Centroid shift and mean vectors by treatment for (A) glucagon‐like peptide‐1 (GLP‐1), (B) PYY, (C) GIP, (D) glucagon. The arrows show the shift of the centroid coordinates after intervention. Circles represent the OS group; squares represent the LED group. Black dots represent the visit before intervention, white dots represent the visit after intervention. The error lines represent the standard error for Cx and Cy. †p < 0.05 for difference between interventions in the shift of the Cx of the vector; ‡p < 0.05 for difference between interventions in the shift of the Cy of the vector.
Hormonal levels of (A) adrenocorticotropin (ACTH), (B) cortisol, (C) growth hormone (GH), (D) thyrotropin (TSH), (E) parathyroid hormone (PTH), (F) prolactin during fasting and the OGTT, before (black) and after (white) intervention with obesity surgery (OS, circles) and low‐energy diet (LED, squares). *p < 0.05, **p < 0.01, ***p < 0.001 for difference after weight‐loss intervention. Interaction term for intervention × visit.
Fasting levels of (A) IGF‐1, (B) fT3, (C) fT4, (D) copeptin, (E) sex hormone‐binding globulin (SHBG) before (white) and after (grey) obesity surgery (OS) and low‐energy diet (LED). *p < 0.05, **p < 0.01, ***p < 0.001 for difference after weight‐loss intervention.
Hormonal adaptations to weight loss: Responses to an oral glucose load 4 weeks after obesity surgery and low‐energy diet

June 2025

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5 Reads

Aims In addition to weight loss, obesity surgery (OS) leads to metabolic improvements that seem at least partly independent of weight loss and are also mediated by various endocrine pathways and the brain. For the first time, we compared the short‐term effects of weight loss achieved by either OS or a low‐energy diet (LED) on several hormonal systems, at fasting and upon an oral glucose challenge. Materials and Methods This study presents sub‐analyses from a randomized controlled trial including 24 participants with obesity but without diabetes (BMI 35–45 kg/m²), randomized 2:1 to either OS or 4‐week LED leading to comparable weight loss. Circulating levels of gut, pituitary, adrenal, thyroid hormones, glucagon, insulin‐like growth factor‐1 and sex hormone‐binding globulin were measured at baseline and 4 weeks after either intervention, both at fasting and during an oral glucose tolerance test (OGTT). Results At 4 weeks, similar weight loss was achieved for the two interventions (7.7 for OS vs. 7.4% for LED). glucagon‐like peptide‐1 and peptide YY secretion during the OGTT increased after OS (p < 0.001 for OGTTAUC for both hormones), but not LED, while glucagon secretion remained unaffected. Adrenocorticotropin, cortisol and prolactin levels during OGTT were increased after OS (p = 0.04, p < 0.001, p = 0.002, respectively), while parathyroid hormone levels were decreased (p = 0.007). Fasting triiodothyronine levels were reduced after OS (p = 0.01). Fasting sex hormone‐binding globulin levels decreased after both interventions (p < 0.01). Conclusion Rapid and extensive hormonal changes occur after OS, but not LED, despite similar weight loss. Of note, few differences were seen in the fasting state, whereas multiple endocrine pathways were affected during the oral glucose challenge. The findings suggest altered responses to oral glucose after OS in several hypothalamus‐pituitary endocrine axes and peripheral endocrine glands.


Overview of normal sarcomere and release of cardiac troponin following acute myocardial injury.
Cardiac troponin at the point of care in acute and chronic coronary syndromes

June 2025

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6 Reads

High‐sensitivity cardiac troponin (hs‐cTn) assays are integral to the assessment of patients with acute chest pain where prompt and accurate diagnosis of myocardial infarction enables timely delivery of potentially life‐saving treatment. In the Emergency Department, implementation of central laboratory hs‐cTn assays has reduced length of stay and unnecessary hospital admission. Recently hs‐cTn assays have become available on point‐of‐care (POC) platforms that have equivalent analytical and diagnostic performance to central laboratory platforms but can deliver results more rapidly to guide decisions in real‐time. These assays have the potential to further accelerate care in the Emergency Department and to facilitate the assessment of patients with suspected acute coronary syndromes in pre‐hospital settings, primary care and the out‐patient clinic. Greater accessibility to testing could broaden the role of hs‐cTn to improve the risk stratification of patients with new onset exertional angina and chronic coronary syndromes. Whilst hs‐cTn assays are already available for use at the point‐of‐care, prospective studies are required to determine the clinical and cost‐effectiveness of testing in patients with acute and chronic coronary syndromes.


Flowchart of criteria for selecting study participants. CGM, continuous glucose monitoring; HDHCC, hyogo diabetes hypoglycemia cognition complications; MMSE, mini‐mental state examination; T2DM, type 2 diabetes mellitus.
Continuous glucose monitoring‐derived time in range is associated with changes in cognitive function test scores in Japanese patients with type 2 diabetes mellitus

June 2025

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6 Reads

Aims Type 2 diabetes mellitus (T2DM) is known to be a risk factor for cognitive dysfunction and dementia. Time in range (TIR), which is derived from continuous glucose monitoring (CGM), has been widely used as an indicator of the quality of glycemic control. While cross‐sectional studies have reported an association between CGM‐derived TIR and cognitive function scores, few studies have longitudinally investigated the relationship between the two. This study aimed to prospectively investigate the association between CGM‐derived TIR and changes in multiple cognitive function scores. Materials and Methods The present study used baseline and 2‐year data from an ongoing multicenter cohort study. This study included 197 T2DM patients aged ≥60 years with undiagnosed dementia. Participants were examined with the mini‐mental state examination (MMSE), the Japanese version of the Montreal cognitive assessment (MoCA‐J) and the digit symbol substitution test (DSST) at both baseline and 2 years. Multiple regression analyses were performed to investigate the association between TIR and changes in cognitive function test scores over 2 years. Results Multivariate regression analysis showed that there was a significant association between TIR and changes in MMSE (ΔMMSE) over 2 years (standard partial regression coefficient [β] = 0.187, p = 0.005). Similarly, multivariate regression models showed a significant association between TIR and ΔMoCA‐J (β = 0.218, p = 0.001) and ΔDSST (β = 0.164, p = 0.036). Conclusions In patients with T2DM with undiagnosed dementia, CGM‐derived TIR might be associated with overall cognitive decline and reduced processing speed.


Flow chart of the number of studies selected for meta‐analysis.
Risk of bias assessment of the included studies in the meta‐analysis.
Forest plot displaying weighted mean difference and 95% confidence intervals for the effect of saroglitazar on fasting glucose, postprandial glucose, HbA1c, insulin, C‐peptide and HOMA‐IR.
Forest plot displaying weighted mean difference and 95% confidence intervals for the effect of saroglitazar on fasting glucose and HbA1c in clinical trials with treatment durations of ≤12 weeks and >12 weeks.
Funnel plots showing publication bias for the effect of saroglitazar on fasting glucose and HbA1c.
Effect of saroglitazar on glycaemic parameters: A systematic review and meta‐analysis of randomized controlled trials

Aims Saroglitazar is a dual peroxisome proliferator‐activated receptor (PPAR), predominantly a PPAR‐α agonist and a moderate PPAR‐γ agonist activity, which has shown positive effects in diabetic dyslipidaemia. However, its potential anti‐diabetic effect has not been thoroughly investigated, and the data have been inconsistent. Thus, we conducted a meta‐analysis to examine the impact of saroglitazar on glycaemic markers in patients with dyslipidaemia, type 2 diabetes and non‐alcoholic fatty liver disease. Materials and Methods The search strategy was conducted in PubMed, Web of Science, Scopus, ClinicalTrials.gov and Google Scholar databases. Randomized controlled trials reporting changes in glycaemic parameters after saroglitazar therapy were selected. The Cochrane risk‐of‐bias tool for randomized trials version 2 was used to assess the quality of the included studies. For meta‐analysis, a random‐effects model and the generic inverse variance method were conducted. Also, the leave‐one‐out method was applied for the sensitivity analysis. Results A total of 10 clinical trials (N = 2077; mean age: 49.7 years; 40% female) were included. Regarding the quality of the included studies, two trials had a low risk of bias, seven trials showed some concerns and one study exhibited a high risk of bias. The meta‐analysis of 10 randomized controlled trials showed that saroglitazar significantly reduces fasting glucose (weighted mean difference [WMD]: −12.11 mg/dL, 95% CI: −14.79, −9.43, p < 0.0001, I² = 40%), postprandial glucose (WMD: −16.17 mg/dL, 95% CI: −22.29, −10.04, p < 0.0001, I² = 0%) and HbA1c (WMD: −0.39%, 95% CI: −0.57, −0.22, p < 0.0001, I² = 72%) compared to active control or placebo. However, there was no significant effect on insulin levels (WMD: −1.03 μU/mL, 95% CI: −4.12, 2.06, p = 0.51, I² = 37%), HOMA‐IR (WMD: –0.41, 95% CI: −0.86, 0.04, p = 0.07, I² = 41%) and C‐peptide (WMD: −0.30 ng/mL, 95% CI: −0.76, 0.15, p = 0.19, I² = 0%) after saroglitazar therapy. Conclusions Our results revealed that saroglitazar therapy improves glycaemic parameters through the reduction of fasting glucose, postprandial glucose and HbA1c.




Distribution of HVS 3 years post‐treatment in patients initiating SGLT2 inhibitors vs DPP‐4 inhibitors after 1:1 PSM. SGLT2, sodium‐glucose transporter‐2; DPP‐4, dipeptidyl peptidase 4; HVS, HbA1c variability score.
Cardiovascular and renal outcomes in patients initiating SGLT2 inhibitors vs DPP‐4 inhibitors after 1:1 PSM. SGLT2, sodium‐glucose transporter‐2; DPP‐4, dipeptidyl peptidase 4; MACE, major adverse cardiovascular events; SRE, serious renal events; AMI, acute myocardial infarction; HHF, hospitalization for heart failure; HR, hazard ratio; CI, confidence interval.
The effect of sodium‐glucose cotransporter 2 inhibitors on HbA1c variability and cardiovascular and renal adverse outcome in patients with T2DM

June 2025

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7 Reads

Aims To compare the effectiveness of sodium‐glucose cotransporter 2 (SGLT2) inhibitors and dipeptidyl peptidase 4 (DPP‐4) inhibitors in reducing haemoglobin A1c (HbA1c) variability and improving cardiovascular and renal outcomes in patients with type 2 diabetes mellitus (T2DM) and high HbA1c variability. Methods This territory‐wide cohort study involved patients with T2DM and an HbA1c variability score (HVS) >60% who initiated SGLT2 inhibitors or DPP‐4 inhibitors in Hong Kong between 2015 and 2022. Propensity score (PS) matching was used to adjust for confounders. The primary outcome was post‐treatment HVS within 3 years. Secondary outcomes included major adverse cardiovascular events (MACE) and serious renal events (SRE). Results Among 20,205 T2DM patients with a baseline HVS >60%, 4,612 SGLT2 inhibitor users were 1:1 matched with DPP‐4 inhibitor users. When referencing the 0%–20% quintile, patients initiating SGLT2 inhibitors versus DPP‐4 inhibitors exhibited a reduced likelihood of being in higher HVS quintiles [21%–40%: odds ratio (OR) 0.76, 95% confidence interval (CI) 0.66–0.88; 41%–60%: OR 0.57, 95% CI 0.50–0.65; 61%–80%: OR 0.49, 95% CI 0.42–0.56; and 81%–100%: OR 0.40, 95% CI 0.34–0.47]. SGLT2 inhibitors were associated with a reduced risk of MACE [hazard ratio (HR) 0.69; 95% CI 0.60–0.79] and SRE (HR 0.71; 95% CI 0.63–0.80) compared to DPP‐4 inhibitors. Conclusion In patients with high HbA1c variability, SGLT2 inhibitor initiation was associated with superior effectiveness in reducing HbA1c variability compared to DPP‐4 inhibitors. The initiation of SGLT2 inhibitors versus DPP‐4 inhibitors was linked to significantly reduced cardiovascular and renal adverse events.



IR per 1000 PY with 95% CI for the main analysis population per country and aHR for all UTC, per country and all countries pooled.
Cumulative dose of empagliflozin‐– IR per 1000 PY with 95% CI for the main analysis population per country and aHR for all UTC, per country and all countries pooled. The quartiles were calculated based on the patient‐level total dosages of empagliflozin use from index date to the end of follow‐up. The UK: Q1 = 3010 mg, Q2 = 6300 mg, Q3 = 12283.8 mg; Sweden: Q1 = 3040 mg, Q2 = 5400 mg, Q3 = 9750 mg; Finland: Q1 = 3290 mg, Q2 = 6300 mg, Q3 = 12 050 mg. NA, not available due to local data regulations for <5 frequencies; Q1, first quartile; Q2, second quartile; Q3, third quartile.
Cumulative exposure duration of empagliflozin‐– IR per 1000 PY with 95% CI for the main analysis population per country and aHR for all UTC, per country and all countries pooled. The quartiles were calculated based on the patient‐level total durations of empagliflozin use from the index date to the end of follow‐up. The UK: Q1 = 264 days, Q2 = 478 days, Q3 = 873 days; Sweden: Q1 = 270 days, Q2 = 451 days, Q3 = 793 days; Finland: Q1 = 279 days, Q2 = 486 days, Q3 = 890 days. NA, not available due to local data regulations for <5 frequencies; Q1, first quartile; Q2, second quartile; Q3, third quartile.
Post‐authorisation safety study to assess the risk of urinary tract cancer in people with type 2 diabetes initiating empagliflozin: A multi‐country European study

June 2025

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3 Reads

Aims This study aimed to assess the risk of urinary tract cancers (UTCs), including bladder and renal cancers, in people with type 2 diabetes (T2D) initiating empagliflozin compared with people initiating any dipeptidyl peptidase‐4 inhibitor (DPP‐4i) in the United Kingdom (UK), Sweden, and Finland. Materials and Methods This was a non‐interventional, multi‐country cohort study based on secondary data in Sweden, Finland, and the UK. The study used an active comparator, new user design and included propensity score‐matched adults with T2D initiating empagliflozin or a DPP‐4i between 2014 and 2020 (2021 for the UK). Follow‐up started at the index date (first prescription or dispensation for empagliflozin or a DPP‐4i) and 180 days were considered as the latency period. Incidence rates (IRs) and hazard ratios (HRs) were estimated under an as‐treated approach in each country. HRs were then entered into a random‐effects meta‐analysis. Results The main analyses included 151 055 matched people. The mean age for empagliflozin initiators was 57.0–63.2 years across the countries, and most were female (59.6%–67.8%). A meta‐analysis of country‐level HR showed no evidence of an increased risk of UTC (adjusted HR = 0.88, 95% confidence intervals [CIs]: 0.66–1.17), bladder cancer (adjusted HR = 0.91, 95% CI: 0.63–1.33) or renal cancer (adjusted HR = 0.89, 95% CI: 0.57–1.38) for empagliflozin initiators compared with DPP‐4i initiators. Various sensitivity analyses also validated the robustness of the main findings. Conclusions No increased risk of UTC, bladder, and renal cancer was observed when empagliflozin initiators were compared with DPP‐4i initiators in this non‐interventional cohort study.


Journal metrics


5.4 (2023)

Journal Impact Factor™


22%

Acceptance rate


10.9 (2023)

CiteScore™


3 days

Submission to first decision


1.361 (2023)

SNIP


$5,380.00 / £3,810.00 / €4,650.00

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