Journal of Diabetes Research最新文献

Aims: The aim of this study is to evaluate the real-world prescribing patterns of SGLT2 inhibitors and GLP-1 receptor agonists (GLP-1RA) in patients with newly diagnosed Type 2 diabetes (T2DM), particularly among those with high cardiovascular risks or chronic kidney disease, and to identify demographic, clinical, and system-level factors associated with receiving these medications.

Materials and methods: This cross-sectional study analyzed electronic medical records (EMRs) of patients with newly diagnosed T2DM from 60 primary care clinics in West Michigan between April 2021 and January 2023. We assessed the documented prescription rates of SGLT2 inhibitors and GLP-1RAs within 3 months of diagnosis based on EMRs, particularly in high-risk subgroups.

Results: Overall, 19.9% of n = 5783 patients with newly diagnosed T2DM had either an SGLT2 inhibitor or GLP-1RA prescribed. Prescription rates for these agents were 20.0% for patients with chronic ischemic heart disease and 19.3% for those with impaired kidney function. In adjusted analyses, higher BMI (aOR 2.92 for BMI > 40 kg/m², 95% CI 1.58-5.42, ref BMI < 24 kg/m²), hyperlipidemia (aOR 1.89, 95% CI 1.28-2.79), chronic ischemic heart disease (aOR 1.55, 95% CI 1.11-2.18), and higher HbA1c (aOR 1.32 per 1% increase, 95% CI 1.22-1.42) were associated with higher odds of receiving prescription of these medications.

Conclusions: Despite guideline recommendations, SGLT2 inhibitors and GLP-1RAs are prescribed to only a minority of patients with newly diagnosed T2DM, even among those with clear indications. Efforts to improve guideline-adherent care in primary care settings are needed.

Background and aims: In this study, we investigated whether high-intensity interval training (HIIT) and mixed probiotic consumption, either autonomously or synergistically, could regulate the expression of calcium-binding protein-1 (SMOC-1), insulin resistance (IR), and blood glucose (BG) in male rats with induced diabetes.

Methods: Thirty healthy male Wistar rats, aged about 8 weeks, were randomly divided into five groups of six rats each, including control group (C, 1G), diabetic control group (CD, 2G), probiotic supplement group (Pro, 3G), HIIT group (Ex, 4G), and HIIT and probiotic supplement group (Pro + Ex, 5G). Each strain of the mixed probiotic supplement, containing Lactobacillus rhamnosus GG (PTCC1637), Lactobacillus reuteri, and Lactococcus casei enriched with L-cysteine HCl, was administered at a concentration of 10¹⁰ colony-forming units (CFU) per milliliter to Groups 3G and 5G. Groups 4G and 5G underwent HIIT to evaluate the effect of supplementation and HIIT on SMOC-1, IR, and BG.

Results: Mixed probiotics and HIIT did not affect SMOC-1 expression in liver muscle (η ² = 0.00, p = 0.965, F _{(1, 15)} = 0.002); however, they synergistically lowered IR (η ² = 0.23, p = 0.048, F _{(1, 15)} = 4.65) and BG (η ² = 0.32, p = 0.013, F _{(1, 15)} = 7.79).

Conclusion: We found no significant effect of mixed probiotic supplementation or its combination with HIIT on SMOC-1. Notably, the HIIT and mixed probiotics reduced IR and BG. Future studies can help assess the accurate synergistic effects of HIIT and mixed probiotics.

Type 2 diabetes, mainly driven by insulin resistance (IR), represents 90% of diabetic cases and has been related to bone fragility and fractures. However, it is unclear how hyperglycaemia, IR and oxidative stress interplay to induce bone fragility. This study was then undertaken to examine the contribution and the interconnection of hyperglycaemia, insulinopenia, IR and oxidative stress to bone fragility, as well as the time- and severity-dependent effects of insulin impairment on bone fragility and its reversibility. IR was induced by dexamethasone in three different protocols: 1 mg/kg/day/im for 7 consecutive days; 500 μg/kg/day/im for 7 consecutive days, the dose was changed to 100 μg/kg/day/im for the following 14 days; and 200 μg/kg/day/im for 21 consecutive days. Fasting glycaemia, glucose tolerance test (GTT) and insulin tolerance test (ITT) were performed at the end of each treatment period while body mass was recorded daily. A control group receiving DMSO 4% was constituted for each protocol. Following euthanasia, the serum was collected for lipid profile, calcium, phosphate and alkaline phosphatase. The pancreas and liver were collected for the assessment of oxidative stress markers. Tibia and femur were collected to assess calcium phosphate and histological modifications. Dexamethasone induced an increase in baseline blood glucose and insulin intolerance while promoting glucose tolerance. A decrease in animal body weight as well as disturbances in oxidative stress, calcium and lipid profiles were observed in dexamethasone-treated animals. Bone histopathology showed loss of bone matrix, decreased collagen and an increase in Trap expression in dexamethasone-treated rats. Bone alterations were positively correlated with oxidative stress and IR. These results show that the phosphocalcic metabolism disruption and bone structure alterations induced by glucocorticoids are related to IR (time and severity) and oxidative stress status. Surprisingly, the relation is more effective on the tibia than the femur.

Objectives: This study examines the association between the Geriatric Nutritional Risk Index (GNRI) and all-cause and cardiovascular disease (CVD) mortality in elderly diabetic nephropathy (DN) patients in the United States.

Methods: Participants were categorized into three GNRI-based groups: (1) moderate to severe malnutrition (M/S) risk (< 92), (2) low risk (92-98), and (3) no risk (> 98). The primary outcomes were all-cause and CVD mortality. Cox proportional hazards regression and competing risk analysis were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).

Results: Among 1790 DN patients (mean age 71.24 ± 7.17 years; weighted 55.0% male, 45.0% female), over 11,724 person-years (mean follow-up 6.56 ± 4.59 years), 274 (15.3%) died from CVD and 914 (51.1%) from all causes. The M/S risk group had a 143% increased all-cause mortality risk (HR 2.43; 95% CI, 1.25-5.80), while the low risk group had a 56% increased risk (HR 1.56; 95% CI, 1.19-2.38), compared to the no risk group. No significant correlation was observed between GNRI and CVD mortality. In gender-specific analysis, the M/S risk group had a higher all-cause mortality risk in males (HR 2.50; 95% CI, 1.04-5.99) than in females (HR 1.62; 95% CI, 0.83-3.15).

Conclusions and implications: A lower GNRI is associated with higher all-cause mortality in elderly DN patients, particularly in males, but not with CVD mortality. GNRI may be a useful prognostic tool for mortality risk assessment in this population.

[This corrects the article DOI: 10.1155/2020/2817972.].

Background: Diabetes significantly increases the risk of cognitive impairment, particularly mild cognitive impairment (MCI). Early identification of individuals at risk for MCI is crucial for timely intervention. This study was aimed at developing and validating a machine learning-based model to predict MCI in patients with Type 2 diabetes (T2DM).

Methods: Participants with T2DM and completed cognitive assessments were included. Feature selection was done using statistical methods and genetic programming to reduce collinearity. Six classification models were trained and evaluated using cross-validation and hyperparameter tuning. External validation was performed with cohorts from the Jiangsu DiabEtes COgnitive Dysfunction Early Diagnosis and Intervention (DECODE) study and the Third National Health and Nutrition Examination Survey (NHANES III). SHAP analysis identified key predictors, and a web interface was developed for practical application.

Results: A total of 2074 participants were included. Significant predictors were education, age, GCA index (glycolipid metabolism), systolic blood pressure, eGFR, BMI, and diabetes duration. The support vector classifier (SVC) model achieved the highest performance, with an AUC of 0.74 ± 0.04, an F1 score of 0.62 ± 0.06, and a recall of 0.74 ± 0.09 in internal validation. External validation with the DECODE cohort yielded an AUC of 0.80, an F1 score of 0.80, and a recall of 0.89. NHANES III validation confirmed the model's reliability in predicting MCI risk.

Conclusions: This study compared machine learning models for diagnosing MCI in T2DM patients. The SVC model demonstrated strong efficacy and accuracy, highlighting the potential of machine learning in diagnosing MCI in this population.

Porcine neonatal pancreatic cell clusters (NPCCs) are a promising and abundant source for islet transplantation owing to their ability to secrete insulin and proliferative potential. However, a significant limitation is the delayed normalization of blood glucose following transplantation, largely attributed to incomplete β-cell differentiation. Exendin-4, a glucagon-like peptide-1 receptor agonist, has been shown to enhance β-cell differentiation, proliferation, and function in various models. This study was aimed at investigating whether posttransplant treatment with exendin-4 could accelerate NPCC differentiation and improve long-term glycemic outcomes in diabetic nude mice. NPCCs were isolated from 1- to 3-day-old piglets and transplanted under the kidney capsule of streptozotocin-induced diabetic nude mice. Recipients received subcutaneous injection of either exendin-4 (3 μg/kg) or saline (as control) twice daily. Graft differentiation was assessed at Days 6, 9, and 16 via immunostaining for insulin, glucagon, PDX1, and SOX9. Blood glucose levels, body weight, and graft histology were monitored over time. Exendin-4 treatment significantly increased the proportion of mature insulin⁺ cells at Day 9 (p < 0.05) and both PDX1⁺/insulin^- and SOX9⁺ progenitor cells at Day 6 (p < 0.01). By Week 10, hyperglycemia persisted in both groups; however, exendin-4-treated recipients exhibited a significant reduction in blood glucose from Week 6 onward. At this time point, grafts from hyperglycemic mice displayed both insulin^-/PDX1⁺ (progenitor cells) and insulin⁺/PDX1⁺ (mature) β-cells, indicating ongoing differentiation. Among mice maintained beyond 10 weeks, euglycemia was achieved between Days 119 and 308, with grafts exhibiting mature insulin⁺/PDX1⁺ cells-evidence of morphological and functional maturation. Our results indicate that exendin-4 transiently enhances NPCC differentiation and expands the progenitor population in early posttransplantation phases. Furthermore, it contributes to improved graft performance and glycemic control, likely through its well-established metabolic effects.

Background: People with diabetes are at increased risk of infections. Emerging evidence suggests sodium-glucose cotransporter 2 (SGLT2) inhibitors have pleiotropic effects that may protect against certain infections. We systematically reviewed real-world evidence on the association between SGLT2 inhibitors and infections among adults with Type 2 diabetes.

Methods: We searched Medline, Embase, Scopus, and Google Scholar from January 1, 2012 to March 18, 2024 for observational studies conducted in adults with Type 2 diabetes published in English. The exposure was SGLT2 inhibitors, and comparators were nonusers or users of other glucose-lowering medications. Studies reporting outcome estimates for specific non-genitourinary infections were included. The study was prospectively registered with PROSPERO (CRD42023492265).

Results: From 6827 records, 28 studies were included in qualitative synthesis and 14 in meta-analyses. There was no association with COVID-19-related mortality in seven studies (OR 0.91; 95% CI: 0.57-1.46) or COVID-19-related hospitalisation in three studies (OR 0.90; 95% CI: 0.67-1.20). A reduced risk of pneumonia was observed in three studies (HR: 0.61; 95% CI: 0.57-0.66), a reduced risk of pneumonia-related mortality in two studies (HR: 0.49; 95% CI: 0.35-0.67), and a reduced risk of sepsis in three studies (HR: 0.45; 95% CI: 0.30-0.68).

Conclusion: Real-world evidence suggests SGLT2 inhibitors are associated with lower risk of pneumonia, pneumonia-related mortality and sepsis. Given the high burden of infection in this population, these associations deserve further research.

Aims: Reporting of impaired fasting glucose (IFG) prevalence and risk factors for progression to diabetes differs between studies, in part, due to the use of multiple definitions of the condition. We aimed to determine the prevalence of diabetes and IFG in men and identify risk factors for the progression to diabetes and regression to normoglycaemia.

Materials and methods: Participants were from the Geelong Osteoporosis Study. Diabetes was defined as fasting plasma glucose (FPG) ≥ 7.0 mmol/L, self-report of diabetes and/or use of antihyperglycaemic medication. IFG was defined using both American Diabetes Association (IFG-ADA: FPG 5.6-6.9 mmol/L) and World Health Organisation (IFG-WHO: FPG 6.1-6.9 mmol/L) criteria. Prevalence of hyperglycaemia at baseline (2001-2006, 1170 men, 20-97 years) was age-standardised to the 2006 Australian population. Multivariable logistic regression models (n = 416) were used to identify risk factors for the progression to diabetes and regression to normoglycaemia over 15 years.

Results: Age-standardised prevalence of IFG-ADA was 18.2% (95% CI 15.7-20.7), 6.2% for IFG-WHO (95% CI 4.8-7.6) and 7.3% for diabetes (95% CI 5.8-8.8). Higher FPG, glycated haemoglobin, age, body fat percent and lower HDL cholesterol were associated with progression to diabetes, whereas younger age and higher HDL cholesterol were associated with regression. A 1.0 mmol/L increase in FPG resulted in a sixfold greater chance of progression to diabetes over follow-up (OR 6.44, 95% CI 2.97-13.94; p < 0.001). A prediction model containing age, FPG, HDL cholesterol and HbA1c predicted an optimal FPG cut point for progression of 5.3 mmol/L.

Conclusion: This study reports cut points for predicting progression to diabetes that align with the ADA classification of IFG. These data may support future work investigating diabetes prevention strategies.

Objective: This randomized controlled trial evaluated the differential effects of aerobic training (AT), resistance training (RT), and combined training (CT) on biphasic insulin secretion and glucose effectiveness (GE) in patients with Type 2 diabetes mellitus (T2DM).

Methods: Forty-five male T2DM patients (mean age: 55.24 ± 8.17 years; disease duration: 12.51 ± 6.46 years; baseline HbA1c: 7.1% ± 1.0%) were randomized to 12-week AT (n = 11), RT (n = 11), CT (n = 11), or control (n = 12) groups. AT involved progressive aerobic exercise (25-45 min at 70%-75% maximum heart rate, thrice weekly). RT comprised nine multijoint exercises (2-3 sets, 8-12 repetitions, thrice weekly). CT combined the full AT protocol with a modified RT regimen (one set, twice weekly). First-phase insulin secretion (FPIS), second-phase insulin secretion (SPIS), and GE were quantified using validated models pre- and postintervention.

Results: Adjusting for baseline values, age, and diabetes duration, ANCOVA revealed significant between-group differences in FPIS (F[3, 38] = 8.64, p < 0.001, η ² = 0.406), SPIS (F[3, 38] = 6.93, p < 0.001, η ² = 0.354), and GE (F[3, 38] = 5.57, p = 0.003, η ² = 0.305). CT elicited the greatest improvements: FPIS (53.4% ± 12.7%, p < 0.001), SPIS (38.9% ± 11.2%, p < 0.001), and GE (12.8% ± 4.6%, p = 0.001) versus control. AT enhanced FPIS (32.6% ± 10.3%, p = 0.001) and SPIS (21.7% ± 8.9%, p = 0.042), while RT improved FPIS (28.5% ± 9.8%, p = 0.006), SPIS (27.5% ± 9.4%, p = 0.012), and GE (10.7% ± 4.3%, p = 0.004). Regression analysis identified baseline β-cell function (β = -0.31, p = 0.020), adiposity reduction (β = -0.36, p = 0.008), and glycemic improvement (β = -0.42, p = 0.003) as predictors of FPIS gains (R ² = 0.537).

Conclusions: CT outperforms single-modality training in enhancing biphasic insulin secretion and GE in T2DM, supporting multimodal exercise as a cornerstone of diabetes management to improve β-cell function and glycemic control.

Trial registration: ClinicalTrials.gov identifier: IRCT2016042227529N1.