Diabetes, Obesity & Metabolism最新文献

Aims: Microvascular complications, such as diabetic retinopathy (DR), diabetic nephropathy (DN) and diabetic peripheral neuropathy (DPN), are common and serious outcomes of inadequately managed type 1 diabetes (T1D). Timely detection and intervention in these complications are crucial for improving patient outcomes. This study aimed to develop and externally validate machine learning (ML) models for self-identification of microvascular complication risks in T1D population.

Materials and methods: Utilizing data from the Chinese Type 1 Diabetes Comprehensive Care Pathway program, 911 T1D patients and 15 patient self-reported variables were included. Combined with XGBoost algorithm and cross-validation, self-identification models were constructed with 5 variables selected by feature importance ranking. For external validation, an online survey was conducted within a nationwide T1D online community (N = 157). The area under the receiver-operating-characteristic curve (AUROC) was adopted as the main metric to evaluate the model performance. The SHapley Additive exPlanation was utilized for model interpretation.

Results: The prevalence rates of microvascular complications in the development set and external validation set were as follows: DR 7.0% and 12.7% (p = 0.013), DN 5.9% and 3.2% (p = 0.162) and DPN 10.5% and 20.4% (p < 0.001). The models demonstrated the AUROC values of 0.889 for DR, 0.844 for DN and 0.839 for DPN during internal validation. For external validation, the AUROC values achieved 0.762 for DR, 0.718 for DN and 0.721 for DPN.

Conclusions: ML models, based on self-reported data, have the potential to serve as a self-identification tool, empowering T1D patients to understand their risks outside of hospital settings and encourage early engagement with healthcare services.

Aims: This study aimed to build a model-based predictive approach to evaluate the gastrointestinal side effects following an initial metformin medication.

Materials and methods: The model was developed from data from four randomised clinical cohorts. A prediction model was established using integrated or simplified indicators. Ten machine learning models were used for the construction of predictive models. The Shapley values were used to report the features' contribution.

Results: Four randomised clinical trial cohorts, including 1736 patients with type 2 diabetes, were first included in the analysis. Seventy percent of participants (1216) were allocated to the training set, 15% (260) were assigned to the internal validation set and 15% (260) were assigned to the test set. The Extra Tree model had the highest area under curve (AUC) (0.87) in the validation and test set. The top five crucial indicators were blood urea nitrogen (BUN), sex, triglyceride (TG), high-density lipoprotein-cholesterol (HDL-C) and total cholesterol (TC), and these five indicators were selected for constructing a simplified predictive model (AUC = 0.76). An online web-based tool was established based on the predictive model with integrated 17 features and top five indicators.

Conclusions: To predict gastrointestinal side effects in diabetic patients for initial use of metformin, a few easily obtained features are needed to establish the model. The model can be applied to the Chinese population in clinical practice.

Aims: Both pioglitazone and glucagon-like peptide 1 receptor agonists (GLP1RA) alone improve metabolic dysfunction-associated steatohepatitis (MASH) in randomized clinical trials, whereas preclinical studies suggested MASH benefits with sodium glucose co-transporter 2 inhibitors (SGLT2i). In the real world, patients with type 2 diabetes often require multiple agents for glycaemic control. Here, we investigated the benefits of combining these agents on risks of MASH.

Materials and methods: Longitudinal changes in FibroScan-aspartate aminotransferase (FAST) score were measured in 888 patients with type 2 diabetes. Use of pioglitazone, GLP1RA and/or SGLT2i was defined as continuous prescriptions of ≥180 days prior to their last reassessment FibroScan. Multivariable logistic regression analysis was conducted to evaluate the associations between use of these agents and FAST score changes.

Results: Over a median follow-up of 3.9 years, the increasing number of these agents used was significantly associated with more reductions in FAST score (p for trend <0.01). Dual combination was independently associated with a higher likelihood of achieving low FAST score at reassessment than single use of any of these agents (odds ratio [OR] 2.84, p = 0.01). Among the different drug combinations, using SGLT2i and pioglitazone (median dose 15 mg daily) together, as compared to not using any of these three agents, was associated with a higher likelihood of both low FAST score at reassessment (OR 6.51, p = 0.008) and FAST score regression (OR 12.52, p = 0.009), after adjusting for changes in glycaemic control and body weight during the study.

Conclusions: Combining SGLT2i and pioglitazone is a potentially useful strategy to ameliorate 'at-risk' MASH in patients with type 2 diabetes.

Introduction: We aimed to characterise and compare individuals diagnosed with type 1 diabetes (T1D), latent autoimmune diabetes in adults (LADA) and type 2 diabetes (T2D), in a real-world setting.

Methods: Anthropometric and clinical data from 36 959 people with diabetes diagnosed at age 30-70 years enrolled in the prospective diabetes patients follow-up (DPV) registry from 1995 to 2022 were analysed cross-sectionally at diagnosis and follow-up (≥6 months after diagnosis). LADA was defined as clinical diagnosis of T2D, positivity of ≥1 islet autoantibody and an insulin-free interval of ≥6 months upon diabetes diagnosis.

Results: At diagnosis, age, body mass index, waist circumference, C-peptide and HbA1c in people with LADA (n = 747) fell in between individuals with T1D (n = 940) and T2D (n = 35 272) (all p-values < 0.01). At follow-up, after adjusting for age, sex and diabetes duration, the prevalence of dyslipidemia and hypertension was the highest in people with LADA (90.6%, 77.7%) compared to people with T2D (81.8%, 60.4%) and T1D (75.7%, 39.7%) (p < 0.01). The prevalence of diabetic kidney disease (DKD) was higher in LADA (44.2%), than in T1D (19.9%) (p < 0.01). The prevalence of peripheral neuropathy was higher in individuals with LADA (55.1%) than in T2D (43.9%) and T1D (42.1%) (p < 0.05). Coverage of treatment for hypertension and dyslipidemia were 22.4% and 15.0% in T1D, 63.0% and 36.6% in LADA and 29.4% and 18.2% in T2D.

Conclusion: People with LADA had a higher prevalence of cardiovascular risk factors (dyslipidemia, hypertension) and cardiovascular complications (DKD and peripheral neuropathy), suggesting that people with LADA are at need for improved recognition and care.

Aims: There is conflicting evidence regarding whether excess adiposity without metabolic abnormalities reflects a truly benign phenotype. This study evaluated the independent and joint associations of the presence of excess adiposity and metabolic abnormalities on arterial stiffness.

Materials and methods: Participants in UK Biobank with body mass index (BMI) and arterial stiffness index (ASI) recorded between 2006 and 2010, free from cardiovascular diseases and not underweight (BMI <18.5 kg/m²) were included. The primary outcome was severity of ASI analysed using multivariate-adjusted linear regression.

Results: Of 162 590 participants, 42.5% were overweight and 24.4% were obese. Within the normal BMI strata, 50.7% had ≥1 metabolic abnormality. Compared to individuals with normal BMI and no metabolic abnormality (reference group), increased BMI or metabolic abnormalities were similarly associated with higher ASI: normal BMI with metabolic abnormalities (adjusted β-coefficient and 95% CI, 0.35; 0.30-0.40); overweight without metabolic abnormalities (0.32; 0.26-0.37). Individuals with obesity and no metabolic abnormality had higher ASI (0.65; 0.57-0.74) but was lower than individuals with overweight and metabolic abnormalities (0.80; 0.75-0.84). Individuals with obesity and metabolic abnormalities had the highest ASI (1.07; 1.02-1.12) among all six metabolic combinations, p < 0.001 for each versus reference group. Sensitivity analysis suggested higher ASI with increasing number of metabolic abnormalities within BMI categories and higher ASI in the presence of abdominal obesity within metabolic categories.

Conclusions: Excess adiposity and metabolic abnormalities are independently associated with increased arterial stiffness to a similar degree, suggesting that metabolically healthy individuals with overweight and obesity are not benign groups. This reinforces the need to prevent excess adiposity and consider primary prevention strategies even before metabolic abnormalities emerge.

Aim: Gestational diabetes mellitus (GDM) has been associated with reduced postprandial glucagon-like peptide 1 (GLP-1) responses. As pregnancy induces changes in gallbladder motility and bile acids stimulate GLP-1 secretion, we investigated postprandial gallbladder emptying and GLP-1 responses in women with GDM.

Methods: Women with and without GDM underwent two 240-min mixed meal tests; one during third trimester of pregnancy and one 3-6 months postpartum. We evaluated ultrasonography-assessed gallbladder emptying, plasma concentrations of glucometabolic hormones including GLP-1, paracetamol absorption (proxy for gastric emptying) and circulating factors known to affect gallbladder dynamics.

Results: Fifteen women with GDM and 15 pregnant women with normal glucose tolerance (NGT) (baseline median age 31 (interquartile range 29;33) versus 32 (28;33) years, body mass index (BMI) 27.2 (24.7;30.7) versus 28.4 (26.2;31.0) kg/m², HbA_1c 30 (29;32) versus 30 (28;31) mmol/mol) were included. No differences in postprandial gallbladder emptying or GLP-1 responses were observed between women with and without GDM, neither during pregnancy nor postpartum. Pregnancy increased fasting gallbladder volumes by 69 (30;122)% and 103 (59;156)% and postprandial gallbladder emptying by 77 (28;236)% and 99 (37;190)% compared with postpartum in women with and without GDM, respectively. Postprandial GLP-1 responses were reduced by 60 (3;82)% and 81 (11;90)% during pregnancy compared with postpartum in women with and without GDM, respectively.

Conclusion: Pregnancy-induced changes in gallbladder motility seem to play no or a limited role in previously reported GDM-associated reduced postprandial GLP-1 responses as gallbladder emptying was greater and postprandial GLP-1 response was lower in pregnancy than postpartum regardless of GDM status.

Aims: Type 2 diabetes (T2D) patients with a clinical phenotype characterized by a high degree of insulin resistance are at increased risk of chronic kidney disease (CKD). We previously demonstrated that the endothelin receptor antagonist (ERA) atrasentan reduced insulin resistance in T2D. In this study, we compared the effect of atrasentan on insulin resistance across different phenotypic clusters of patients with T2D.

Materials and methods: We performed a post hoc analysis of the SONAR trial, a randomized, placebo-controlled trial of the ERA atrasentan in patients with T2D and CKD. Patients were stratified into four previously identified phenotypic clusters: severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD) and mild age-related diabetes (MARD). Changes in insulin resistance, assessed by HOMA-IR, were compared between the phenotypic clusters using a mixed effects model.

Results: In total, 931 patients were included in the analysis. In the overall population, atrasentan compared to placebo reduced HOMA-IR by 12.9% [95%CI 3.5,21.4]. This effect of atrasentan was more pronounced in clusters characterized by insulin resistance or deficiency: (SIRD cluster 26.2% [95% CI 3.8,43.3] and SIDD cluster 18.5% [95%CI -3.8,35.9]), although the latter did not reach statistical significance. The effect of atrasentan compared to placebo was less pronounced in the other two clusters (MARD 12.2% [95% CI -1.7,24.12] and MOD -5.3% [95% CI -28.9,13.9]).

Conclusions: Atrasentan significantly improved insulin sensitivity in patients with T2D and CKD, especially in those characterized by high insulin resistance (SIRD cluster). Further studies are warranted to investigate the long-term clinical outcomes of atrasentan treatment in these distinct phenotypic clusters.

Aim: Over recent years, therapy options and strategies for type 2 diabetes mellitus (T2DM) have developed substantially. This study investigated glucose-lowering treatment in patients with high cardiovascular risk over three decades.

Materials and methods: A total of 2158 patients undergoing elective coronary angiography at a tertiary care hospital in Europe were included in three sequential observational studies (OS): OS1 (1999-2000; n = 672), OS2 (2005-2008; n = 1005) and OS3 (2022-2023; n = 481). Sociodemographic data, patient-reported medication, medical histories and blood samples were analysed.

Results: A clear trend towards more complex glucose-lowering therapies was found. A wider array of glucose-lowering drugs was used over time (OS1: 11; OS2: 21; OS3: 25) and the number of different drugs used in combination therapy in a single patient increased to a maximum of five in OS3. Furthermore, substantial differences in applied medication regimens were observed: Sodium-glucose cotransporter-2 inhibitors were the most frequently reported substance class (34.0% of total reported glucose-lowering drugs) in OS3, whilst metformin remained a key component (OS1: 33.9%; OS2: 41.8%; OS3: 32.0%). Other drug classes like sulfonylureas were largely replaced. A total of 69.2% of patients in OS3 achieved an HbA1c level of < 7% (vs. OS1: 51.9%, OS2: 54.7%; p_trend < 0.001). Over 25% of patients with T2DM were newly diagnosed at admission (OS1: 43.8%, OS2: 29.7%, OS3: 27.2%; p_trend < 0.001) and had therefore no diabetes-related medication.

Conclusion: These real-world data emphasize a marked shift in T2DM treatment towards novel substance classes. However, the use of incretin mimetics remained low. Significantly more patients reached HbA1c targets in the most recent cohort.