Development and validation of a nomogram model for accurately predicting severe fatigue in maintenance hemodialysis patients: A multicenter cross‐sectional study in China

Abstract Introduction This study aims to analyze the risk factors for severe fatigue in maintenance hemodialysis (MHD) patients and develop a clinical prediction model to help doctors and patients prevent severe fatigue. Methods Multicentre MHD patients were included in this study. The objective was to investigate the risk factors for severe fatigue in MHD patients and develop a prediction model. Results A total of 243 MHD patients were included in the study, and the incidence of severe fatigue was found to be 20.99%. Using age, body mass index, total cholesterol, and albumin levels, a predictive nomogram for fatigue was constructed. In the training set, the nomogram had an area under the curve of 0.851, sensitivity of 82.86%, specificity of 81.76%, and c‐index of 0.851. The nomogram was accurate in calibration and proved to be clinically useful. Conclusion The nomogram developed in this study is a practical and reliable tool for quickly identifying severe fatigue in MHD patients.