Established risk prediction models for the incidence of a low lean tissue index in patients with peritoneal dialysis

OBJECTIVE: The objective of this study is to investigate the incidence of low lean tissue index (LTI) and the risk factors for low LTI in peritoneal dialysis (PD) patients, including to establish risk prediction models. METHODS: A total of 104 PD patients were enrolled from October 2019 to 2021. LTI was measured by bioimpedance spectroscopy. Multivariate logistic regression and machine learning were used to analyze the risk factors for low LTI in PD patients. Kaplan–Meier analysis was used to analyze the survival rate of patients with low LTI. RESULTS: The interleukin-6 (IL-6) level, red cell distribution width (RDW), overhydration, body mass index (BMI), and the subjective global assessment (SGA) rating significantly differed between the low LTI and normal LTI groups (all p < 0.05). Multivariate logistic regression showed that IL-6 (1.10 [95% CI: 1.02–1.18]), RDW (1.87 [95% CI: 1.18–2.97]), BMI (0.97 [95% CI: 0.68–0.91]), and the SGA rating (6.33 [95% CI: 1.59–25.30]) were independent risk factors for LTI. Cox regression analysis showed that low LTI (HR 3.14, [95% CI: 1.12–8.80]) was the only significant risk factor for all-cause death in peritoneal dialysis patients. The decision process to predict the incidence of low LTI in PD patients was established by machine learning, and the area under the curve of internal validation was 0.6349. CONCLUSIONS: Low LTI is closely related to mortality in PD patients. Microinflammatory status, high RDW, low BMI and low SGA rating are risk factors for low LTI in PD patients. The developed prediction model may serve as a useful tool for assessing low LTI in PD patients.