Study on the Predictive Value of Different Insulin Resistance Replacement Indices for Hyperuricemia in Middle-aged and Elderly Patients with Type 2 Diabetes

Background In China, there is a significant prevalence of type 2 diabetes patients (T2DM) , who also have an increased risk of developing secondary hyperuricemia (HUA) . Patients with T2DM who develops HUA are at increased risk of developing further problems, which could have detrimental effects on their health. Consequently, it is crucial to promptly identify individuals who have a high risk of developing secondary HUA and to begin early prevention and therapy. Objective Exploring the predictive value of common insulin resistance (IR) surrogates for the HUA in middle-aged and elderly T2DM patients. And employ a subset of these metrics as predictive metrics for the occurrence and progression of HUA. Methods Using stratified random sampling, 479 individuals with type 2 diabetes mellitus (T2DM) and 1 528 patients with non-hyperuricemia (NHUA) were chosen from seven community health service centers in Shenzhen between January and March 2023. Multivariate Logistic regression analysis was used to evaluate the effects of various insulin resistance (IR) metrics and their quartiles on the incidence of HUA in middle-aged and older type 2 diabetic patients. Triglyceride-high density lipoprotein cholesterol (TG/HDL-C) index, non-high density lipoprotein cholesterol ratio (Non-HDL-C/HDL-C) index, triglyceride glucose (TyG) index, triglyceride glucose body mass (TyG-BMI) index, triglyceride glucose waist circumference (TyG-WC) index, and insulin resistance metabolism (METS-IR) index are some of these metrics. The predictive efficacy of several IR substitution measures for HUA in middle-aged and older T2DM patients was assessed using the ROC curve. The CHARLS database's cohort data from 2011 and 2015 were filtered in order to create a nested case-control that would validate the predictive power of different IR alternative indicators for the likelihood of HUA. Results Multivariate Logistic regression study revealed that the METS-IR index, TG/HDL-C index, Non HDL-C/HDL-C index, TyG index, TyG-BMI index, TyG-WC index, and TG/HDL-C index were independent influencing factors for the occurrence of HUA (P