Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy最新文献

Aim: We aimed to evaluate the efficacy and safety of roflumilast compared to alpha-lipoic acid (ALA) in type 2 diabetic patients with diabetic neuropathy.

Methods: In this randomized controlled parallel study, 58 type 2 diabetic patients with diabetic neuropathy were randomly allocated into (Roflumilast group; n=29), which received 500 mcg/day of oral roflumilast and (ALA group; n=29), which received 600 mg/day of oral ALA. At baseline and 12 weeks after intervention, blood samples were collected to assess fasting blood glucose (FBG), glycated hemoglobin (HbA1C), insulin, tumor necrosis factor-α (TNF-α), malondialdehyde (MDA), and neurotensin (NT) levels. Homeostatic Model Assessment of Beta Cell Function (HOMA-1β) and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) were calculated. Neuropathic symptoms and neuropathic pain were assessed using the Michigan Neuropathy Screening Instrument Questionnaire (MNSIQ), the Michigan Neuropathy Screening Instrument Examination (MNSIE), and the Douleur Neuropathique-4 (DN4) questionnaire.

Results: After intervention and as compared to baseline, both groups showed significant decreases in HbA1C, FBG, fasting insulin level, HOMA-IR, HOMA-1β, and serum levels of TNF-α, MDA, and neurotensin (P<0.001). The comparison between the two study groups post-treatment indicated that the roflumilast group showed a significant decrease in HbA1C by 0.7% (8.8% relative reduction) compared to 0.3% (3.8% relative reduction) in the ALA group (P<0.001), FBG (P<0.001), fasting insulin level (P=0.012), and HOMA-IR (P<0.001). Similarly, serum MDA level was declined by 0.80 nmol/mL (37.0% reduction) with the roflumilast group versus 0.56 nmol/mL (25.1% reduction) with the ALA group (P=0.003). Post-intervention and compared to baseline data, both groups exhibited significant reductions in neuropathy scores (P<0.001). The comparison between the two study groups after treatment revealed non-significant variations between both groups regarding MNSIQ, MNSIE, and DN4 scores (P>0.05).

Conclusion: Roflumilast may offer superior glycemic and oxidative stress control benefits, though neuropathy symptoms control was comparable to ALA.

Clinicaltrialsgov id: (NCT05369793).

Background: Heart failure (HF) is a severe and common complication of type 2 diabetes mellitus (T2DM), associated with increased morbidity and mortality. Although the biomarker NT-proBNP, at a cut-off value of 125 pg/mL, has demonstrated satisfactory discriminatory power for predicting HF risk in T2DM patients, its measurement remains inaccessible in most primary healthcare settings in China. This study aimed to develop and externally validate a machine learning-based nomogram for predicting the risk of elevated NT-proBNP (≥125 pg/mL) as a surrogate for HF risk in patients with T2DM.

Methods: We retrospectively enrolled 564 T2DM patients as the development cohort and 302 from two external centers as the validation cohort. After feature selection via least absolute shrinkage and selection operator regression, five machine learning models were constructed and evaluated using 10-fold cross-validation. The optimal model was presented as a static nomogram and further deployed as an online web application for clinical use.

Results: Six key predictors were identified: estimated glomerular filtration rate, age, serum albumin, hemoglobin, urine albumin-to-creatinine ratio, and the binary indicator of age ≥ 65 years. Interpretability analysis using SHapley Additive exPlanations revealed estimated glomerular filtration rate as the most influential feature. The final machine learning-based nomogram achieved AUCs of 0.806 (95% CI: 0.767-0.845) in training and 0.861 (95% CI: 0.813-0.908) in external validation, with good calibration and clinical utility. Furthermore, the nomogram scores showed a significant positive correlation with established TRS-HF_DM risk strata, supporting its clinical relevance.

Conclusion: We developed and validated an interpretable machine learning-based nomogram that effectively predicts the risk of elevated NT-proBNP in T2DM patients using six routine clinical variables. This tool demonstrates robust performance and generalizability, offering a practical and accessible solution for HF risk stratification in resource-limited primary care settings in China.

Background and objectives: Childhood obesity is associated with both short-term and long-term health complications, yet a new obesity phenotype called metabolically healthy obesity (MHO) has emerged. While MHO is often perceived as a "benign" form of obesity, research specifically examining health disorders risks in children with MHO remains limited. This systematic review and meta-analysis aimed to evaluate health disorders in children with MHO.

Methods: Following PRISMA 2020 guidelines, we systematically searched five databases (PubMed, Scopus, Google Scholar, EBSCO, and ScienceDirect) for observational studies examining MHO children aged 0-18 years. The studies were analyzed using R and R Studio software, with study quality assessed using the Newcastle Ottawa Scale.

Results: Ten studies with a total of 19,119 children were included in this review. Children with MHO demonstrated significantly higher overall health disorders risk compared to MHNW children (pooled OR 2.88, 95% CI [1.64; 5.06]). This trend aligns with the subgroups analysis of left ventricle hypertrophy, hypertension, and kidney damage. However, some of the subgroup analyses showed insignificant results. Additionally, MHO children showed lower risks of experiencing health disorders compared to MUO children (pooled OR 0.56, 95% CI [0.23; 1.34]). The underlying mechanism of the increased health risk is excess adipokines causing systemic inflammation and leading to increased various health risks.

Conclusion: Despite metabolically "healthy" status, children with MHO remain at increased risk for health disorders compared to normal-weight peers. This systematic review and meta-analysis is the first one discussing the health disorders in children with MHO. More studies are required in the future to reinforce these findings in order to produce much more comprehensive insights.

Objective: Tsukushi (TSK) is a recently identified hepatic factor that has gained prominence for its distinctive function in glycolipid metabolism and energy homeostasis. However, the role of TSK in gestational diabetes mellitus (GDM) remains largely unexplored. In this study, we conducted a pioneering investigation by determining serum TSK levels in patients with GDM and examining the correlation between these levels and various metabolic parameters in gestational diabetes patients.

Methods: A total of 176 pregnant women (mean age 29.5 ± 3.2 years) were recruited from September 2023 to December 2024. Serum TSK levels and clinical markers related to glycolipid metabolism were measured at 24-28 weeks of gestation. All subjects underwent an oral glucose tolerance test (OGTT).

Results: Serum TSK was significantly higher in patients with GDM than in the normal glucose tolerance group [0.60(0.47,0.73 vs 0.52(0.42,0.67) ng/mL; P <0.05]. Correlation analysis showed that TSK was significantly and positively correlated with diastolic blood pressure (DBP), alanine aminotransferase (ALT), direct bilirubin (Dbil), free triiodothyronine (FT3), 1-h post-OGTT glucose (1hPG), low-density lipoprotein cholesterol (LDL-C), and total cholesterol (TC). Logistic regression analysis showed that Logistic regression analysis showed that higher TSK levels were independently associated with increased odds of GDM.

Conclusion: TSK levels were higher in GDM than in NGT (P=0.013), and higher TSK tertiles were independently associated with increased odds of GDM (Model 3 OR=2.883, 95% CI 1.173-7.084; P=0.021). After FDR correction, only the association with total cholesterol remained significant (FDR-adjusted P=0.023).

Purpose: To investigate how lifestyle interventions alter fat distribution and organ-specific iron deposition in individuals with obesity, and whether these changes can serve as indicators of glycemic remission in obese patients with dysglycemia.

Methods: This prospective study included individuals with obesity who participated in a 6-month lifestyle intervention, which comprised a caloric-restricted balanced diet and an exercise regimen. Ultimately, 104 participants completed the follow-up phase. Magnetic resonance imaging (MRI) was utilized to monitor the dynamics of fat mobilization and organ iron deposition at baseline and 6-month follow-up. Correlation analysis, logistic regression, and receiver operating characteristic (ROC) curve analysis were employed to examine the relationships between regional fat distribution, organ iron deposition, and glycemic improvement.

Results: Initially, the 104 participants were divided into three categories: normal glucose regulation (NGR, n=41), prediabetes (n=23), and type 2 diabetes mellitus (T2DM, n=40). After a 6-month lifestyle change, the number of patients with T2DM and prediabetes decreased, and those with NGR increased. There were also notable decreases in liver and pancreatic fat, as well as visceral and subcutaneous fat, with the largest decrease in liver fat (-43.2%) among obese participants. There were also reductions in liver and pancreatic iron deposition after intervention. ROC curve analysis revealed that the change in liver fat was the best indicator of diabetes remission among obese participants, with an area under the curve of 0.819 (95% confidence interval [CI]: 0.681-0.957). Notably, liver fat reduction ≥38.8% predicted diabetes remission (OR=2.5, 95% CI:1.59-5.60) in individuals with obesity.

Conclusion: Lifestyle intervention can effectively reduce ectopic fat and iron overload in individuals with obesity. The extent of hepatic fat mobilization has emerged as the most significant indicator of diabetes remission in individuals with obesity, potentially serving as a pivotal focus for future therapeutic interventions.

[This corrects the article DOI: 10.2147/DMSO.S525774.].

Objective: In this study, we aimed to investigate the association between skeletal muscle area (SMA), subcutaneous fat area (SFA), and visceral fat area (VFA), quantified using computed tomography (CT), and the risk of type 2 diabetes mellitus (T2DM). We also evaluated the predictive performance of these parameters for assessing T2DM risk.

Methods: We used a retrospective case-control design, including 207 hospitalized patients who underwent abdominal quantitative CT (QCT) scans at Fushun Central Hospital from July 2021 to July 2022. Using QCT technology, SMA, SFA, and VFA were measured at the level of the third lumbar vertebra. Additionally, the skeletal muscle index (SMI=SMA/height²) and the visceral-to-subcutaneous fat ratio (VFA/SFA) were calculated. Univariate and multivariate logistic regression analyses were used to examine the association between skeletal muscle and abdominal fat parameters with T2DM, and receiver operating characteristic (ROC) curves evaluated the predictive performance of each indicator.

Results: Body mass index, systolic blood pressure, diastolic blood pressure, fasting blood glucose, VFA, and SFA were significantly higher in the T2DM group compared with the control group, and SMA and SMI were significantly lower (all P<0.05). Multivariate logistic regression analysis showed that lower SMI (odds ratio [OR]=0.906, 95% confidence interval [CI]: 0.847-0.970, P=0.004) and greater VFA (OR=1.008, 95% CI: 1.004-1.012, P<0.001) were independent risk factors for T2DM. ROC curve analysis showed that SMI (area under the ROC curve [AUC]=0.634) and VFA (AUC=0.697) had moderate predictive performance for T2DM whereas the combined model (SMI+VFA) significantly improved predictive efficacy (AUC=0.816).

Conclusion: Visceral fat accumulation was an independent risk factor for T2DM, and increased skeletal muscle mass showed a protective effect. The combined SMI and VFA model showed significantly enhanced predictive ability for T2DM risk, suggesting its potential as a clinical biomarker.

Purpose: Although body mass index (BMI) is an established risk factor for cardiovascular diseases (CVD), many studies found that obese patients with established CVD had better prognosis than their lean counterparts. The study aimed to investigate whether this inverse association between BMI and arterial stiffness can be explained by body composition analysis.

Patients and methods: Participants, aged from 26 to 86 years, were included in the cross-sectional study from October 2016 to January 2020. The brachial-ankle PWV (baPWV) was measured to assess arterial stiffness. Body composition was measured using bioelectrical impedance analysis (BIA). Lean Mass Index (LMI) and Fat Mass Index (FMI), calculated as lean mass and fat mass divided by squared height (kg/m²) respectively, are complementary indices that quantitatively assess individual's non-fat and fat compartments. Multiple linear regression analysis was conducted to investigate the associations between BMI, LMI and arterial stiffness. Mediation analysis was performed to examine the effect of bone mineral density (BMD) on the association between LMI and baPWV.

Results: A total of 744 participants were included. The median age was 61.00 (55.00, 67.00) years, and 502 (67.47%) of them were men. The median BMI, FMI and LMI were 25.56 (23.35, 28.01) kg/m², 7.18 (5.81, 8.68) kg/m² and 18.45 (17.10, 19.73) kg/m² respectively. The median baPWV was 1514.50 (1358.00, 1689.00) cm/s. Among all the anthropometric parameters, only BMI (r=-0.150, p<0.001) and LMI (r=-0.206, p<0.001) were significantly correlated with baPWV. Although BMI was inversely associated with baPWV [β=-5.99, 95% CI (-11.10, -0.89), p=0.022], the association became insignificant after LMI [β=-25.85, 95% CI (-44.73, -6.96), p=0.007] was included in the model. Furthermore, 19.68% of the association between LMI and baPWV was mediated by BMD.

Conclusion: Lean mass is the essential body component that determines the inverse association between BMI and arterial stiffness. Body composition analysis may provide important information for subclinical atherosclerosis beyond BMI.

Objective: Negative pressure wound therapy (NPWT) is a key intervention for diabetic foot ulcers (DFUs). However, the body of meta-analytic evidence is fraught with conflicting findings, creating significant clinical uncertainty. This study was designed to harmonize the discordant evidence, identify the most methodologically robust meta-analysis, and formulate a clear, evidence-based recommendation for the clinical use of NPWT.

Methods: We conducted a comprehensive search of the PubMed, Embase, and Cochrane Library databases to identify all pertinent meta-analyses. The methodological quality of each included review was rigorously assessed using the Assessment of Multiple Systematic Reviews (AMSTAR) instrument. The Jadad decision algorithm was then employed to systematically select the most reliable and robust evidence.

Results: Eight meta-analyses met the inclusion criteria, with AMSTAR scores ranging from 6 to 9. The formal application of the Jadad decision algorithm identified the meta-analysis by Deng et al as the definitive source of best available evidence. This meta-analysis demonstrated that NPWT significantly improved wound healing rates (risk ratio = 1.46) and decreased amputation rates (risk ratio = 0.69) relative to conventional therapy, while also shortening granulation tissue formation time without increasing adverse events.

Conclusion: The highest-quality evidence, harmonized through this appraisal, confirms that NPWT is a safe and effective adjunctive therapy for DFUs. Its demonstrated ability to accelerate healing while reducing amputations provides a strong evidence base for consideration as a key component of standard clinical practice.