Objective  To analyze the risk factors of sarcopenia in young and middle-aged patients with maintenance hemodialysis (MHD), and to establish and verify the risk prediction model.

  Methods  A total of 339 young and middle-aged MHD patients in the First People's Hospital of Lianyungang City from September to December 2020 were selected, and were divided into modeling group (n=237) and verification group (n=102) in a ratio of 7:3 by the simple random method. Multivariate Logistic regression model was used to analyze the data of the modeling group, the independent risk factors of sarcopenia in young and middle-aged MHD patients were screened, and a risk prediction model was established. The Hosmer-Lemeshow test was used to evaluate the fitting degree of the model, and the receiver operating characteristics (ROC) curve was used to evaluate the identification ability of the model. The data of the patients in the validation group were selected, and the ROC curve was used to test the prediction effect of the model.

  Results  In this study, the body mass index (BMI) (OR=0.742, 95%CI, 0.612~0.899), upper arm muscle circumference (OR=0.767, 95%CI, 0.595~0.988) and hemoglobin (OR=0.975, 95%CI, 0.951~0.999) were included to construct a risk prediction model finally, and the model equation was: Z=-0.298×BMI -0.265×upper arm muscle circumference-0.025×hemoglobin. The Hosmer-Lemeshow chi square test result of the modeling group showed that the model had a good fitting degree (χ²=14.954, P=0.060), and the area under the curve of ROC curve was 0.862 (95%CI, 0.792~0.932). The area under the curve of ROC curve in the verification group was 0.866 (95%CI, 0.788~0.943), the sensitivity and specificity were 89.5% and 74.7% respectively, and the Youden index was 0.642.

  Conclusion  In this study, the prediction model of sarcopenia for young and middle-aged MHD patients based on BMI, upper arm muscle circumference and hemoglobin has high prediction value, and the required indicators are easy and convenient to obtain, which can provide a reliable basis for clinical evaluation.