Background: Glycemic variability (GV) is developing as a marker of glycemic control, which can be utilized as a promising predictor of complications. To determine whether long-term GV is associated with incident eGFR decline in two cohorts of Tehran Lipid and Glucose Study (TLGS) and Multi-Ethnic Study of Atherosclerosis (MESA) during a median follow-up of 12.2 years.
Methods: Study participants included 4422 Iranian adults (including 528 patients with T2D) aged ≥ 20 years from TLGS and 4290 American adults (including 521 patients with T2D) aged ≥ 45 years from MESA. The Multivariate Cox proportional hazard models were used to assess the risk of incident eGFR decline for each of the fasting plasma glucose (FPG) variability measures including standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of the mean (VIM) both as continuous and categorical variables. The time of start for eGFR decline and FPG variability assessment was the same, but the event cases were excluded during the exposure period.
Results: In TLGS participants without T2D, for each unit change in FPG variability measures, the hazards (HRs) and 95% confidence intervals (CI) for eGFR decline ≥ 40% of SD, CV, and VIM were 1.07(1.01-1.13), 1.06(1.01-1.11), and 1.07(1.01-1.13), respectively. Moreover, the third tertile of FPG-SD and FPG-VIM parameters was significantly associated with a 60 and 69% higher risk for eGFR decline ≥ 40%, respectively. In MESA participants with T2D, each unit change in FPG variability measures was significantly associated with a higher risk for eGFR decline ≥ 40%.Regarding eGFR decline ≥ 30% as the outcome, in the TLGS, regardless of diabetes status, no association was shown between FPG variability measures and risk of eGFR decline in any of the models; however, in the MESA the results were in line with those of GFR decline ≥ 40%.Using pooled data from the two cohorts we found that generally FPG variability were associated with higher risk of eGFR decline ≥ 40% only among non-T2D individuals.
Conclusions: Higher FPG variability was associated with an increased risk of eGFR decline in the diabetic American population; however, this unfavorable impact was found only among the non-diabetic Iranian population.
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http://dx.doi.org/10.1186/s12889-023-15463-8 | DOI Listing |
Am J Transl Res
December 2024
Department of Anesthesiology, Perioperative and Pain Medicine, Nanjing First Hospital, Nanjing Medical University Nanjing, Jiangsu, China.
Objectives: To retrospectively investigate the effect of a mobile app-based self-care diary, a nursing management method, on post-heart transplantation diabetes.
Methods: A retrospective analysis was conducted on the general data of 87 patients who underwent heart transplantation in the Cardiac and Thoracic Vascular Surgery Department of Nanjing First Hospital between January 2018 and December 2023. Based on the nursing method, the patients were divided into a control group that received routine nursing measures (n=47 cases) and an observation group that implemented a mobile APP-based self-care diary combined with nursing (n=40 cases).
Antioxidants (Basel)
December 2024
Immunogenomics and Metabolic Diseases Laboratory, Instituto Nacional de Medicina Genómica, SS, Mexico City 14610, Mexico.
Endoplasmic reticulum stress (ERS) is activated in all cells by stressors such as hyperglycemia. However, it remains unclear which specific serum biomarkers of ERS are consistently altered in type 2 diabetes (T2D). We aimed to identify serum ERS biomarkers that are consistently altered in T2D and its complications, and their correlation with metabolic and anthropometric variables.
View Article and Find Full Text PDFFront Endocrinol (Lausanne)
December 2024
Department of Endocrinology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China.
Objective: Diabetic peripheral neuropathy (DPN) is a chronic complication of diabetes that can potentially escalate into ulceration, amputation and other severe consequences. The aim of this study was to construct and validate a predictive nomogram model for assessing the risk of DPN development among diabetic patients, thereby facilitating the early identification of high-risk DPN individuals and mitigating the incidence of severe outcomes.
Methods: 1185 patients were included in this study from June 2020 to June 2023.
BMC Med Res Methodol
December 2024
Department of Military Health Statistics, Faculty of Preventive Medicine, Air Force Medical University/Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, Shaanxi, China.
Background: Accurate fasting plasma glucose (FPG) trend prediction is important for management and treatment of patients with type 2 diabetes mellitus (T2DM), a globally prevalent chronic disease. (Generalised) linear mixed-effects (LME) models and machine learning (ML) are commonly used to analyse longitudinal data; however, the former is insufficient for dealing with complex, nonlinear data, whereas with the latter, random effects are ignored. The aim of this study was to develop LME, back propagation neural network (BPNN), and mixed-effects NN models that combine the 2 to predict FPG levels.
View Article and Find Full Text PDFDiabetol Metab Syndr
December 2024
Department of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
Objective: This research primarily focuses on exploring the changes in intrapulmonary vascular volume (IPVV) in radiological patterns of usual interstitial pneumonia (UIP) associated with Type 2 Diabetes Mellitus (T2DM), thereby inferring the possible mechanisms of the co-occurrence of diabetes and UIP patterns.
Methods: Thin-layer data were post-processed on the basis of high-resolution computed tomography (HRCT) and quantitatively assessed for IPVV. Changes in IPVV were compared between T2DM combined with UIP modality and T2DM non-UIP modality.
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