关键词: 肌减少症, 年龄校正的 Charlson 合并症指数, 微型营养评估简化版量表, 小腿围, 预测, Logistic模型

Abstract: Background　Sarcopenia is prone to increase the risk of hospitalization and death in elderly people，and its incidence is often higher in patients with multiple chronic diseases. Detecting comorbidities can detect and treat sarcopenia as early as possible，but previous studies have not fully considered the severity and combination of chronic diseases. Objective　To analyze the association between age-adjusted charlson comorbidity index（aCCI）and the risk of sarcopenia in elderly patients，and explore a new predictive models for sarcopenia in the elderly. Methods　Select 218 elderly patients who were treated at the 925th Hospital of Joint Logistics Support Force from December 2023 to May 2024. According to the diagnosis results，the patients were divided into two groups：sarcopenia group（n=69）and non-sarcopenia group（n=149）. Collect basic patient information，blood biochemical indicators，muscle related indicators，Mini Nutritional Assessment Short-Form（MNA-SF），etc.，and use aCCI to assess comorbidities. Using multiple logistic regression analysis to investigate the association between aCCI and other factors with sarcopenia in elderly patients，and drawing receiver operating characteristic（ROC）curves to evaluate the predictive value of aCCI and scoring models for sarcopenia in elderly patients. Results　The results of multiple logistic regression analysis showed that elevated aCCI（OR=1.661，95%CI=1.165-2.368，P=0.005）was a risk factor for sarcopenia in elderly patients，while elevated MNA-SF score（OR=0.682，95%CI=0.506-0.920，P=0.012）and calf circumference（OR=0.543，95%CI=0.413-0.714，P<0.001）were protective factors for sarcopenia in elderly patients. Based on the multiple logistic regression model equation Logit（P）=20.174 - MNA-SF score × 0.382 calf circumference × 0.611+aCCI score × 0.507，a nomogram prediction model for the risk of sarcopenia in elderly patients was constructed. The ROC curve analysis of MNA-SF score，calf circumference，aCCI，and nomogram prediction models for predicting sarcopenia in elderly patients showed that the area under the ROC curve（AUC）of MNA-SF score，calf circumference，and aCCI for predicting sarcopenia in elderly patients was 0.733（95%CI=0.654~0.813），0.853（95%CI=0.797~0.908），and 0.739（95%CI=0.662~0.815），respectively. The AUC of the nomogram prediction model for sarcopenia in elderly patients was 0.919（95%CI=0.878~0.959，P<0.001），with an optimal cutoff value of 0.37，sensitivity of 0.831，and specificity of 0.821. Conclusion　Our findings suggest that elevated aCCI is a risk factor for sarcopenia in elderly patients，while elevated MNA-SF score and calf circumference are protective factors. And the nomogram prediction model based on MNA-SF score，calf circumference，and aCCI has high predictive value for sarcopenia in elderly patients，which can provide a basis for early screening and prevention of sarcopenia.

Key words: Sarcopenia, Age-adjusted charlson comorbidity index, Mini Nutritional Assessment Short-Form, Calf circumference, Predictive, Logistic models