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

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.