Risk factor analysis and prediction model development for the occurrence of sarcopenia in middle-aged and elderly men with newly diagnosed type 2 diabetes mellitus

Abstract

To develop a prediction model to forecast the onset of sarcopenia in middle-aged and elderly men with type 2 diabetes mellitus (T2DM), this study examined the risk factors contributing to sarcopenia in these individuals. Clinical data of 525 middle-aged and elderly men newly diagnosed with T2DM were retrospectively analyzed. After rigorous data filtering and preprocessing, eligible patients (n = 525) were randomized into the training cohort (n = 394) and validation cohort (n = 131) in a ratio of 3:1. Using sarcopenia in the training cohort as the outcome variable, multivariate logistic regression analysis was performed to identify independentpredictors. The nomogram prediction model was further constructed on theses basis. The constructed prediction model was externally validated using the validation cohort. The 525 newly diagnosed middle-aged and elderly men with T2DM included 451 patients without sarcopenia and 74 patients with sarcopenia, and the incidence of sarcopenia was 14.10%. In the training cohort, the occurrence of sarcopenia in male patients with T2DM was independently associated with age (60–74 years), age (≥75 years), body mass index (BMI) 7%), Albuminuria, non-alcoholic fatty liver disease (NAFLD) and Insulin use (p 7%), Albuminuria, and NAFLD remained independent predictors of sarcopenia in men with T2DM (p 0.05). In middle-aged and older men with T2DM, we successfully developed, and validated a high-precision nomogram model that may improve early identification and screening of individuals at high risk for sarcopenia.

Keywords

• newly diagnosed type 2 diabetes
• male
• sarcopenia
• age