Background: We aimed to determine the predictors of regression to normoglycemia and progression to diabetes among subjects with pre-diabetes in a single model concurrently.
Methods: The present study included 1329 participants aged 20 to 70 years with prediabetes from the population-based cohort of the Tehran Lipid and Glucose Study, with a 10-year follow-up. Glycemic status at follow-up was categorized as regression to normoglycemia: fasting plasma glucose [FPG] of <5.55 and 2h-plasma glucose [PG] of <7.77 mmol/L, and not taking antidiabetic medications. Glycemic status at follow-up was categorized as progression to diabetes: FPG ≥7 or 2h-PG of ≥11.1 mmol/L, or taking antidiabetic medications. Glycemic status determined whether the patients remained in prediabetes category (isolated impaired fasting glycaemia [iIFG] [(5.55≤FPG<7 and 2h-PG<7.77 mmol/L); isolated impared glucose tolarence [iIGT] (7.77 ≤ 2h-PG<11.1 and FGP<5.55 mmol/L)]. With prediabetes as a reference, multinomial logistic regression was utilized to identify the determinants of glycemic changes.
Results: Approximately 40% of participants returned to normoglycemia (n = 578), and similar percentage of participants progressed to diabetes (n = 518). Based on the multivariable multinomial model, regression to normoglycemia was associated with age (relative risk ratio [RRR] = 0.97; 95% CI, 0.95-0.99), female sex (RRR = 1.72; 95% CI, 1.18-2.50), high education level of ≥12 years (RRR = 2.10; 95% CI, 1.19-3.70), and combined IFG/impaired glucose tolerance (IGT) versus IFG (RRR = 0.45; 95% CI, 0.29-0.70). The risk of progression to diabetes increased with body mass index (RRR = 1.10; 95% CI, 1.05-1.15), waist circumference (RRR = 0.97; 95% CI, 0.96-0.99), positive familial history of diabetes (RRR = 1.62; 95% CI, 1.07-2.45), and combined IFG/IGT versus IFG (RRR = 2.54; 95% CI, 1.71-3.77).
Conclusion: A small percentage of patients with prediabetes remain in this condition, but the majority go on to develop diabetes or regress to normoglycemia. Both directions had distinct predictors.
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http://dx.doi.org/10.3389/fendo.2022.1041808 | DOI Listing |
JTCVS Open
December 2024
Division of Cardiac Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Md.
Objective: Previous retrospective studies have established a relationship between postoperative hypoglycemia and adverse outcomes after cardiac surgery, but none have accounted for the cause of hypoglycemia.
Methods: A retrospective review was performed of patients who underwent cardiac surgery at a single institution between 2016 and 2021. Patients were categorized as hypoglycemic if they had 1 or more postoperative blood glucose measurement less than 70 mg/dL and normoglycemic otherwise.
J Clin Med
December 2024
The Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel.
Ethnocultural differences between Jewish and Arab communities in Northern Israel may contribute to disparities in type 2 diabetes prevalence. Widespread screening strategies, including hospital-based initiatives, are crucial for early detection of hyperglycemia. This study aimed to determine the prevalence of postprandial hyperglycemia and identify its associated factors in a diverse population of non-diabetic adults visiting the Galilee Medical Center, a tertiary care hospital in Northern Israel.
View Article and Find Full Text PDFEur Stroke J
January 2025
Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.
Introduction: The progression of diabetes status in post-stroke patients remains under-investigated, particularly regarding new treatments for type II diabetes mellitus (DM II), like glucagon-like peptide 1 receptor agonists (GLP-1-RA) and sodium-glucose co-transporter-2 (SGLT-2) inhibitors, which have not been studied in the post-stroke setting.
Patients And Methods: Eight hundred eighty-four consecutive ischemic stroke patients recruited to our prospective STROKE-CARD Registry were assessed concerning their glycemic status at baseline (normoglycemia, prediabetes, DM II) and change over time within 1 year follow-up. Multivariate logistic regression was performed to identify factors associated with transitioning from normoglycemia to prediabetes or DM II.
Front Endocrinol (Lausanne)
December 2024
Department of Nephrology, Shenzhen Second People's Hospital, Shenzhen, Guangdong, China.
Objective: Previous studies have identified a positive link between the visceral adiposity index (VAI) and diabetes in specific populations. Our investigation focused on examining this association in normoglycemic adults in Japan.
Methods: A cohort study of NAGALA (NAfld in the Gifu Area Longitudinal Analysis) was undertaken from 2004 to 2015 in Japan.
Acta Diabetol
December 2024
Department of General Practice, Zhongda Hospital, Institute of Diabetes, School of Medicine, Southeast University, No.87 Dingjiaqiao Street, 210009, Nanjing, China.
Background: Cluster analysis provides an effective approach in stratifying prediabetes into different subgroups; however, the association of the cluster-based subgroups with prediabetes progression and regression has not been investigated. We aimed to address this issue in a Chinese population.
Methods: A total of 4,128 participants with prediabetes were included to generate cluster-based subgroups of prediabetes based on age, body mass index (BMI), triglyceride-and-glucose (TyG) index, and hemoglobin A1c (HbA1c), using a k-means clustering model.
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