[Development and validation of a prediction model for sarcopenia in male patients with liver cirrhosis].

Objective

To develop and validate a predictive model for muscle atrophy (referred to as sarcopenia) in male patients with liver cirrhosis.

Methods

A retrospective analysis was conducted on clinical data from male patients with liver cirrhosis admitted to the First Affiliated Hospital of Nanjing Medical University between January 1, 2023 and May 31, 2024. The patients were divided into a modeling cohort and a validation cohort at a 7:3 ratio using a random number table method. Based on the skeletal muscle index derived from CT images at the third lumbar vertebra (L3-SMI), the patients were divided into sarcopenia group (L3-SMI<44.77 cm²/m²) and non-sarcopenia group. The logistic regression model was used to analyze and screen the predictors of sarcopenia in the modeling cohort, and verify the interaction, and finally a nomogram model was constructed. The effectiveness and clinical applicability of the model were evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA).

Results

A total of 278 male patients with liver cirrhosis, aged (58±13) years, were enrolled in this study. There were 195 patients in the modeling cohort (88 cases in sarcopenia group, 107 cases in non-sarcopenia group) and 83 patients in the validation cohort. Based on the data of the modeling group, age (OR=1.061, 95%CI: 1.027-1.097, P<0.001), dry body mass index (dBMI, OR= 0.695, 95%CI:0.614-0.787, P<0.001), and platelet count (OR=1.009, 95%CI: 1.003-1.015, P=0.004) were predictors of sarcopenia in male patients with liver cirrhosis. No statistically significant interaction effects were observed among these variables (all P>0.05). The constructed column chart shows that the AUC, sensitivity, and specificity of the modeling group are 0.848 (95%CI: 0.795-0.900), 65.9%, and 86.9%, respectively. The AUC, sensitivity, and specificity of the validation group are 0.841 (95%CI: 0.755-0.928), 78.0%, and 83.3%, respectively. Calibration curves indicated column chart has good calibration ability. DCA curves confirmed the model's decision-making has good clinical applicability.

Conclusions

Age, dBMI, and platelet count served as predictors of sarcopenia in male patients with liver cirrhosis, and the column chart model constructed based on the above indicators can effectively predict the risk of sarcopenia in male patients with liver cirrhosis.