Construction of a prediction model for the risk of sarcopenia in community and hospitalized elderly patients with chronic diseases
10.3760/cma.j.issn.0254-9026.2024.11.008
- VernacularTitle:社区和住院老年慢病患者肌少症风险预测模型的构建
- Author:
Qiangwei TONG
1
;
Xiao WANG
;
Peiwen YU
;
Jing YU
;
Yunlu SHENG
;
Xin ZHAO
;
Juan LIU
Author Information
1. 南京医科大学第一附属医院/江苏省人民医院老年内分泌科，南京 210029
- Keywords:
Sarcopenia;
Chronic disease;
Community;
Inpatients;
Risk factor
- From:
Chinese Journal of Geriatrics
2024;43(11):1420-1425
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the factors influencing sarcopenia in older patients with chronic diseases, both in community settings and hospitals, and to develop a risk prediction model for sarcopenia.Methods:We recruited a total of 403 older adults with chronic diseases, consisting of 251 individuals from a community in Nanjing, Jiangsu Province, and 152 hospitalized patients from the Department of Geriatrics at Jiangsu Province Hospital.Assessments were conducted using a general information questionnaire, serum sample collection, the mini nutritional assessment-short form(MNA-SF), the mini-mental state examination(MMSE), and the geriatric depression scale(GDS).Binary Logistic regression analysis was employed to identify influencing factors and to construct a risk prediction model for sarcopenia, which was illustrated using a nomogram.The model's discrimination was evaluated using the receiver operating characteristic(ROC)curve and the area under the curve(AUC).Results:The prevalence of sarcopenia among community-dwelling older adults with chronic conditions was found to be 4.0%(10/251).In contrast, the prevalence in hospitalized older adults with chronic conditions was significantly higher at 36.2%(55/152).Binary Logistic regression analysis identified several independent risk factors for sarcopenia, including hospitalization( OR=14.391、95% CI: 6.284-32.955、 P<0.001), male gender( OR=3.321、95% CI: 1.587-6.950、 P=0.001), lower low-density lipoprotein cholesterol(LDL-C)levels( OR=2.542、95% CI: 1.160-5.572、 P=0.020), cognitive impairment( OR=2.654、95% CI: 1.269-5.550、 P=0.010), and the use of four or more types of medication( OR=2.328、95% CI: 1.952-5.689、 P=0.044).Based on these risk factors, a nomogram was developed as a predictive model for assessing sarcopenia risk.The AUC for this prediction model was 0.860(95% CI: 0.815-0.912), indicating a sensitivity of 0.831 and a specificity of 0.760. Conclusions:The incidence of sarcopenia is notably high among older patients with chronic diseases.A risk prediction model that incorporates factors such as hospitalization history, gender, LDL-C levels, cognitive function, and types of medication demonstrates significant potential for predicting sarcopenia.This model serves as a valuable foundation for the early screening and intervention of sarcopenia.
