Acta Diabetologica最新文献

Aims: Diabetes patients are at a higher risk of fractures, and glucagon-like peptide-1 receptor agonists (GLP-1RAs) have been suggested to positively impact on bone metabolism. We aim to provide a comprehensive assessment of fracture events associated with GLP-1RAs based on pharmacovigilance data.

Methods: In this study, fracture-related adverse events (AEs) associated with GLP-1RAs and other commonly used glucose-lowering drugs were identified from Food and Drug Administration Adverse Event Reporting System (FAERS) database (2004-2022). The reporting odds ratio (ROR) and adjusted ROR (adj. ROR) were used to compare the reporting of fracture-related AEs associated with insulin, GLP-1RAs, and Non GLP-1RAs, in patients with diabetes through two scenarios. This involved separately comparing each glucose-lowering drug to all other medications used in diabetic patients and reiterating after excluding insulin cases.

Results: A total of 490,107 AE reports for patients with diabetes were identified and 98, 625 of them were for GLP-1RAs. Among all diabetes drugs, GLP-1RAs had the lowest reporting of any fracture-related AEs [adj. ROR = 0.44 (0.40-0.47)], consistent across osteoporotic fracture [adj. ROR = 0.39 (0.34-0.45)] and hip fracture [adj. ROR = 0.34 (0.28-0.41)]. Among GLP-1RA agents, albiglutide was associated with the lowest adj. ROR [0.11 (0.05-0.21)] for any fracture-related AEs. After excluded all insulin reports, GLP-1RAs retained a significantly lower adj. ROR towards any fracture [adj. ROR = 0.45 (0.40-0.50)], osteoporotic fracture [adj. ROR = 0.44 (0.37-0.52)], and hip fracture [adj. ROR = 0.43 (0.33-0.54)].

Conclusion: In a real-world pharmacovigilance setting, GLP-1RAs were associated with lower reporting of fracture-related AEs, indicating the protective effect of GLP-1RAs against fractures.

Background: The triglyceride glucose (TyG) index serves as a dependable surrogate biomarker for evaluating insulin resistance. However, the role of the TyG index in patients with diabetes mellitus who also suffer from acute renal failure warrants further investigation. This study sought to investigate the association between the TyG index and the incidence of acute renal failure in individuals with diabetes.

Methods: This study utilized data from the MIMIC-IV database, categorizing patients into tertiles according to their TyG index. Employing multivariate logistic regression models, we analyzed the relationship between the TyG index and the occurrence of acute renal failure among diabetic patients. To assess non-linear relationships, restricted cubic splines were utilized, and upon detection of non-linearity, a recursive algorithm was implemented to determine inflection points.

Results: The study comprised a total of 1074 participants diagnosed with diabetes mellitus. In the model adjusted for all covariates, the odds ratio (OR) for the association between the TyG index and acute renal failure, accompanied by a 95% confidence interval (CI), was 1.22 (0.82, 1.82), which did not reach statistical significance. However, analysis using restricted cubic splines revealed a U-shaped relationship between the TyG index and acute renal failure, with an inflection point at 9.26. The relationship between the TyG index and acute renal failure was inverse before reaching the inflection point and became directly proportional thereafter, with an OR (95% CI) of 1.86 (1.12, 3.09) after the point.

Conclusion: In individuals diagnosed with diabetes mellitus, our analysis revealed a non-linear relationship between the TyG index and the incidence of acute renal failure. Beyond the inflection point, elevated TyG index levels were markedly linked to a higher prevalence of acute renal failure.

Background: Although the MODY12 subtype, caused by ABCC8 mutations, is rare, it is highly sensitive to sulfonylureas. The identification of ABCC8 mutations in patients clinically diagnosed with MODY has the ability to contribute to the precise management of diabetes.

Methods: Genetic analysis of two families with MODY were conducted using whole-exome sequencing (WES) and Sanger sequencing. The spatial structures of the mutant proteins were constructed using MODELLER and PyMOL software to provide further evidence of pathogenicity.

Results: The heterozygous missense mutations V357I and R1393H in ABCC8 were found in probands of two unrelated MODY pedigrees, which co-segregated with the hyperglycemic phenotypes in these two pedigrees. Detection of the V357I mutation enabled the proband of family A to successfully transfer from insulin to sulfonylurea (SU). After 3 months of follow-up for the SU trial, the HbA1c level of proband A improved from 12.4% at the initial diagnosis to 7.20%. Proband B was treated with insulin because of pregnancy and poor islet function. In silico analysis indicated that the R1393H mutation resulted in a longer hydrogen bond distance to L1389 and cleavage of carbon-hydrogen bonds to V1395, A1390, and L1389.

Conclusions: We have described two pathogenic missense mutations in ABCC8 in Chinese families with MODY. Our findings support the heterogeneity in the clinical features of MODY12 caused by ABCC8 mutations.

Aim: To assess the efficacy and safety of autologous cell therapy (ACT) in patients with ischemic diabetic foot ulcers (DFU). The present meta-analysis was designed to support the development of the Italian Guidelines for the Treatment of Diabetic Foot Syndrome (DFS).

Methods: A Medline and Embase search were performed up to Feb 1st, 2024 collecting all RCTs including diabetic patients or reporting subgroup analyses on diabetic patients with ischemic foot ulcers comparing ACT with placebo/no therapy/standard of care (SoC), with a duration of at least 26 weeks. Prespecified endpoints were: major amputation (principal) and minor amputation, ulcer healing, time-to-healing, transcutaneous oxygen pressure (TcPO2), ankle-brachial index (ABI), pain, and all-cause mortality (secondary). Any ACT was allowed, irrespective of cell product type and route of administration (intra-arterial and intramuscular).

Results: Seven studies fulfilled all inclusion criteria, all using intramuscular transplantation as route of administration, but only 2 had a follow-up greater than 26 weeks. Participants treated with ACT had a significantly lower risk of major amputations in comparison with SoC/placebo (MH-OR 0.47 [0.24, 0.92], p = 0.03). ACT was also associated with a significantly higher rate of ulcer healing (MH-OR: 10.1 [3.5, 29.6], p < 0.001), greater increase of TcPO₂ and ABI values (WMD: 17.57 [13.02, 22.12], p < 0.001), and reduction of pain (WMD: -1.83 [-2.32, -1.34], p = 0.003).

Conclusions: ACT must be considered as a potential therapy for patients with ischemic diabetic foot ulcers. Further studies are needed to better clarify their role in the treatment and management of DFS.

Background: Current studies have identified severe lipid metabolism diseases in diabetic microangiopathy patients, especially in diabetic kidney disease (DKD), diabetic retinopathy (DR) and diabetic neuropathy (DN), with unclear causal relationships.

Methods: We employed a large-scale dataset containing 179 lipid species as the exposure and large-scale public summary-level datasets of DKD, DR and DN as the outcome. We applied Mendelian randomization (MR) approach to explore causal associations between circulating liposomes and diabetic microangiopathy. A sequence of sensitivity tests was conducted to verify the stability of the MR analysis.

Results: We manifest that diacylglycerol (18:1_18:3) (OR = 0.716, 95%CI = 0.559-0.917, P = 0.008), triacylglycerol (OR:0.741-0.763, P < 0.05) and phosphatidylcholine (OR:0.620-1.247, P < 0.05) have a potential association with DKD. And there is a nominal causal effect of phosphatidylinositol (16:0_18:2) (OR = 0.617, 95%CI = 0.401-0.948, P = 0.028), phosphatidylcholine (OR:0.499-0.672, P < 0.05) and sphingomyelin (OR:0.652-1.850, P < 0.05) to DR. In addition, phosphatidylethanolamine (18:1_0:0) (OR = 0.616, 95%CI = 0.405-0.935, P = 0.023), diacylglycerol (16:0_18:1) (OR = 0.675, 95%CI = 0.463-0.984, P = 0.041) and phosphatidylcholine (OR = 0.720-1.619, P < 0.05) nominally associate with DN. It is noteworthy that plasma lipidome of different structures show different effects.

Conclusion: We establish a possible causal connection between certain plasma lipidome and major diabetic microangiopathies. Implementing intervention strategies targeting different lipid molecules may provide novel approaches for preventing and treating diabetic microangiopathies.

Aims: The association of serum uric acid (SUA) with mortality remains unclear in patients with diabetic kidney disease (DKD). Thus, this prospective cohort study aimed to explore the association of SUA with all-cause and cardiovascular disease (CVD) mortality among patients with DKD in a large, nationally representative sample.

Methods: This cohort study included data from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 and the National Death Index mortality data until 31 December 2019. The restricted cubic spline and the Cox proportional hazards regression were conducted to describe the association of SUA with all-cause and CVD mortality and evaluate potential nonlinear associations.

Results: The analysis included 3470 patients with DKD from NHANES 1999-2018. During the follow-up time of 24,633 person-years, we recorded 1489 all-cause deaths, including 542 CVD deaths. We identified a J-shaped association of SUA with all-cause and CVD mortality. The corresponding inflection points were observed at 5.1 and 5.7 mg/dL. When SUA were higher than inflection points, each 1 mg/dL increase in SUA was linked to a 13% and 22% higher risk of all-cause (HR: 1.13; 95% CI: 1.07-1.20;P < 0.001) and CVD (HR: 1.22; 95% CI: 1.06-1.41;P = 0.006) mortality, respectively.

Conclusions: This study indicated the J-shaped association of SUA with all-cause and CVD mortality in patients with DKD. The corresponding inflection points were 5.1 mg/dL for all causes and 5.7 mg/dL for CVD, respectively. More clinical randomized trials are needed to confirm the optimal uric acid-lowering target.

Aims: Studies on machine learning (ML) for the prediction of diabetic nephropathy (DN) in type 1 diabetes mellitus (T1DM) patients are rare. This study focused on the development and external validation of an explainable ML model to predict the risk of DN among individuals with T1DM.

Methods: This was a retrospective, multicenter study conducted across 19 hospitals in Gansu Province, China (No: 2022-473). In total, 1368 patients were eligible for analysis among 1633 collected T1DM patients from January 2016 to December 2023. Recursive feature elimination using random forest and fivefold cross-validation was conducted to identify key features. Among the 12 initial ML algorithms, the optimal ML model was developed and validated externally in a distinct population, and its predictive outcomes were explained via the SHapley additive exPlanations method, which offered personalized decision insights.

Results: Among the 1368 T1DM patients, 324 had DN. The extreme gradient boosting (XGBoost) model, which achieved optimal performance with an AUC of 83% (95% confidence interval [CI]: 76‒89), was selected to predict the risk of DN among T1DM patients. The DN predictive model included variables such as T1DM duration, postprandial glucose (PPG), systolic blood pressure (SBP), glycated hemoglobin (HbA1c), serum creatinine (Scr) and low-density lipoprotein cholesterol (LDL-C). External validation confirmed the reliability of the model, with an AUC of 76% (95% CI: 70‒82).

Conclusions: The ML prediction tool has potential for advancing early and precise identification of the risk of DN among T1DM patients. Although successful external validation indicated that the developed model can provide a promising strategy for clinical adoption and help improve patient outcomes through timely and accurate risk assessment, additional prospective data and further validation in diverse populations are necessary.