Objective: To develop a new, alternative sarcopenia risk score to screen for sarcopenia in type 2 diabetes patients in China and to demonstrate its validity.

Research Design and Methods: The data for this study came from a multicenter, cross-sectional study that had been designed to estimate the prevalence of sarcopenia among adults with type 2 diabetes and had been conducted in several hospitals in Beijing, China. A total of 1125 participants were randomly divided into two groups: an exploratory population and a validation population. A multivariable logistic regression model using the backward stepwise likelihood ratio method to estimate the probability of sarcopenia was fitted with candidate variables in the exploratory population. A new, alternative sarcopenia risk score was developed based on the multivariable model. The internal and external validations were performed in the exploratory and validation populations.

Results: The new, alternative sarcopenia risk score included seven variables: age, sex, BMI, glycosylated hemoglobin, insulin treatment or not, total caloric intake per day, and the proportion of calorie supplied by protein. The score ranged from -9 to 23. The area under the receiver operating characteristic (ROC) curve of the risk score for the prediction of sarcopenia in type 2 diabetes patients was 0.812 (95% CI 0.748-0.877) and 0.841 (95% CI 0.785-0.897) in the exploratory and validation populations, respectively. At the optimal cutoff value of 11, the sensitivity and specificity of the score for the prediction of sarcopenia were 74.5% and 78.0% in the exploratory population and 80.5% and 72.2% in the validation population, respectively. The Hosmer-Lemeshow goodness-of-fit test showed a good calibration with the risk score in external validation (χ2=1.687, P=0.989).

Conclusions: The new, alternative sarcopenia risk score appears to be an effective screening tool for the identification of sarcopenia in Chinese patients with type 2 diabetes in clinical practice.

Disclosure

Q. He: None. L. Guo: None.

Funding

Science and Technology Commission

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