Construction and validation of a nomogramdiagnostic model for osteosarcopenia in maintenance hemodialysis patients
10.3760/cma.j.cn115682-20240327-01627
- VernacularTitle:维持性血液透析患者肌少-骨质疏松症列线图诊断模型的构建与验证
- Author:
Haoyong ZHANG
1
;
Kun ZHANG
;
Xin LI
;
Xiaojing WANG
;
Chen YU
;
Keqin ZHANG
;
Fanglei XU
Author Information
1. 同济大学医学院，上海 200092
- Keywords:
Hemodialysis;
Osteosarcopenia;
Risk factor;
Nomogram
- From:
Chinese Journal of Modern Nursing
2024;30(24):3242-3249
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the risk factors of osteosarcopenia in maintenance hemodialysis patients, construct a diagnostic nomogram model and verify the effect.Methods:Usingthe convenient sampling method, a total of 697 patients who underwent regular hemodialysis in six hospitals in Shanghai from July 2020 to April 2021 were selected as the modeling set, and 132 patients who underwent regular hemodialysis in Tongji Hospital in Shanghai in November 2020 were selected as the validation set. General information, laboratory indicators, human parameters, physical functions, nutritional status, physical activity, cognitive function, and depression were collected. Logistic regression was used to analyze the risk factors of osteosarcopenia in maintenance hemodialysis patients and to construct a nomogram model. The effect of the model was evaluated by the area under the receiver operating characteristic curve, calibration curve, and decision curve.Results:A total of 697 maintenance hemodialysis patients were included in the modeling set, including 171 patients with osteosarcopenia, with an incidence rate of 24.53% (171/697). The results of the binomial logistic regression analysis showed that age, body mass index, physical activity intensity, and Charlson Comorbidity Index (CCI) were the influencing factors for the occurrence of osteosarcopenia in maintenance hemodialysis patients ( P<0.05). The area under the receiver operating characteristic curve in the modeling set, ten-fold cross-validation, and validation set were 0.835, 0.827, and 0.851, respectively. The calibration curves of the modeling and validation sets fitted well. The decision curve showed that the clinical utility of the nomogram was good. Conclusions:Maintenance hemodialysis patients are prone to osteosarcopenia. Old age, low body mass index, high Charlson Comorbidity Index, and low-intensity physical activity are risk factors for osteosarcopenia in maintenance hemodialysis patients. A nomogramdiagnostic model based on the above-mentioned influencing factors can help medical staff identify high-risk populations early and develop prevention and treatment measures.
