A predictive nomogram based on triglyceride glucose index to body mass index ratio for low appendicular skeletal muscle mass

Abstract The aim of this study was to investigate risk factors, develop, and assess the predictive nomogram for low appendicular skeletal muscle mass index (ASMI) in middle-aged and elderly populations. A total of 3,209 inpatients were divided into a Training Set (n = 2,407) and a Validation Set (n = 802). A nomogram was developed using R software for internal validation, and external validation was performed using the Validation Set. Gender (male), age, height, weight, triglyceride levels, alanine aminotransferase levels, alcohol consumption, and the triglyceride-glucose index to body-mass index ratio (TyG/BMI) were identified as predictors for the nomogram of low ASMI. In the Training Set, Q1-Q4 subgroups were performed for TyG/BMI, and logistic regression analysis showed that a TyG/BMI ratio greater than 0.37 was significantly associated with an increased risk of developing low ASMI (P