Cross-Sectional Evaluation of Risk Factors and Preliminary Development of a Sarcopenia Risk Scoring Model in Patients...

This cross-sectional study aimed to identify clinical factors associated with sarcopenia in adults with type 2 diabetes mellitus (T2DM) aged ≤ 65 years and to develop a preliminary nomogram-based risk scoring model using routinely collected clinical indicators.

We enrolled 81 patients with T2DM aged ≤ 65 years who were admitted to Huzhou Central Hospital between July 2023 and September 2025. Demographic characteristics, anthropometric measurements, and laboratory parameters were collected. Appendicular skeletal muscle mass, handgrip strength, and gait speed were measured, and sarcopenia was diagnosed according to Asian Working Group for Sarcopenia criteria. Univariate analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariable logistic regression were used to identify independent risk factors and construct a nomogram-based prediction model. Model performance was evaluated using receiver operating characteristic (ROC) analysis, calibration plots, and decision curve analysis (DCA).

Compared with patients without sarcopenia, those with sarcopenia had lower HDL-C and albumin levels and higher HbA1c concentrations (all p < 0.05). LASSO regression identified HDL-C, HbA1c, height, and BMI as key predictors, and multivariable analysis confirmed low HDL-C, high HbA1c, shorter height, and lower BMI as independent risk factors. The nomogram demonstrated good discrimination (AUC = 0.844) and calibration, and decision curve analysis indicated favorable clinical net benefit.

Reduced height, lower BMI, elevated HbA1c, and decreased HDL-C are significant risk factors for sarcopenia in patients with T2DM. The developed risk scoring model demonstrated good discriminative ability within this single-center cohort and may serve as a preliminary tool for clinical risk stratification, but it requires validation in larger, independent samples.