Analysis of factors associated with sarcopenia in maintenance hemodialysis patients: Development and validation of predictive models

Background: Sarcopenia is prevalent among maintenance hemodialysis (MHD) patients, contributing to increased mortality risk and reduced quality of life. However, research on predictive factors for sarcopenia in this population, particularly involving body mass index (BMI) and serum phosphorus levels, remains limited. Objectives: This study aimed to evaluate BMI and serum phosphorus as independent risk factors for sarcopenia in MHD patients and to develop and validate a nomogram prediction model for early clinical detection. Methods: A cohort of 186 MHD patients from the Second Affiliated Hospital of Hebei North University (June 2023 to January 2024) was randomly divided into a modeling group (n = 117) and a validation group (n = 69). Sarcopenia was diagnosed using the 2019 Asian Working Group for Sarcopenia (AWGS) criteria, with assessments conducted through bioelectrical impedance analysis and laboratory tests. A nomogram model incorporating BMI and serum phosphorus was developed using multivariate logistic regression. Results: Univariate and multivariate analyses identified BMI and serum phosphorus as independent risk factors for sarcopenia in MHD patients (P<0.05). In the validation cohort, the nomogram model demonstrated an area under the receiver operating characteristic curve (AUC) of 0.787, with a sensitivity of 80.8% and specificity of 72.1%. Decision curve analysis (DCA) confirmed clinical utility within a risk threshold range of 11% to 72%. In the modeling cohort, the model achieved a sensitivity of 60.7%, specificity of 97.0%, and AUC of 0.870. Conclusions: BMI and serum phosphorus are significant independent risk factors for sarcopenia in MHD patients. The developed nomogram model exhibits robust predictive performance (AUC = 0.787) and high clinical applicability, enabling early detection and personalized interventions for sarcopenia in this population.