年龄校正的Charlson合并症指数对老年患者肌少症的预测价值研究

BackgroundSarcopenia is prone to increase the risk of hospitalization and death in elderly peopleand its incidence is often higher in patients with multiple chronic diseases. Detecting comorbidities can detect and treat sarcopenia as early as possiblebut previous studies have not fully considered the severity and combination of chronic diseases. ObjectiveTo analyze the association between age-adjusted charlson comorbidity indexaCCIand the risk of sarcopenia in elderly patientsand explore a new predictive models for sarcopenia in the elderly. MethodsSelect 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 resultsthe patients were divided into two groupssarcopenia groupn=69and non-sarcopenia groupn=149. Collect basic patient informationblood biochemical indicatorsmuscle related indicatorsMini Nutritional Assessment Short-FormMNA-SFetc.and use aCCI to assess comorbidities. Using multiple logistic regression analysis to investigate the association between aCCI and other factors with sarcopenia in elderly patientsand drawing receiver operating characteristicROCcurves to evaluate the predictive value of aCCI and scoring models for sarcopenia in elderly patients. ResultsThe results of multiple logistic regression analysis showed that elevated aCCIOR=1.66195%CI=1.165-2.368P=0.005was a risk factor for sarcopenia in elderly patientswhile elevated MNA-SF scoreOR=0.68295%CI=0.506-0.920P=0.012and calf circumferenceOR=0.54395%CI=0.413-0.714P<0.001were protective factors for sarcopenia in elderly patients. Based on the multiple logistic regression model equation LogitP=20.174 - MNA-SF score 0.382 calf circumference 0.611+aCCI score 0.507a nomogram prediction model for the risk of sarcopenia in elderly patients was constructed. The ROC curve analysis of MNA-SF scorecalf circumferenceaCCIand nomogram prediction models for predicting sarcopenia in elderly patients showed that the area under the ROC curveAUCof MNA-SF scorecalf circumferenceand aCCI for predicting sarcopenia in elderly patients was 0.73395%CI=0.654~0.8130.85395%CI=0.797~0.908and 0.73995%CI=0.662~0.815respectively. The AUC of the nomogram prediction model for sarcopenia in elderly patients was 0.91995%CI=0.878~0.959P<0.001with an optimal cutoff value of 0.37sensitivity of 0.831and specificity of 0.821. ConclusionOur findings suggest that elevated aCCI is a risk factor for sarcopenia in elderly patientswhile elevated MNA-SF score and calf circumference are protective factors. And the nomogram prediction model based on MNA-SF scorecalf circumferenceand aCCI has high predictive value for sarcopenia in elderly patientswhich can provide a basis for early screening and prevention of sarcopenia.