Association of changes in body composition with all-cause mortality in patients undergoing hemodialysis: A prospective cohort study

Le résumé fourni par la source

• Death risk in patients undergoing hemodialysis is predicted by LTI loss and FTI gain. • Longitudinal changes in LTI and FTI were more strongly associated with mortality than single-point values. • LTI loss is significantly associated with FTI gain, and they worsened the prognosis. • This study offers patients undergoing hemodialysis effective prognostic information and guidance for clinical care. This study aimed to explore the effect of longitudinal body composition changes on mortality risk in patients undergoing hemodialysis and identify whether changes in body composition can more accurately predict mortality than baseline status. A prospective cohort study was conducted on 340 patients undergoing hemodialysis. Lean mass and body fat were determined using a bioimpedance spectroscopy (BIS) device and expressed as the lean tissue index (LTI) or fat tissue index (FTI), respectively. The patients were subjected to BIS at baseline and after 1 year. The hazard ratio (HR) for death was calculated using Cox regression analysis. Among 340 patients, 289 were tested with a repeat BIS. LTI loss and FTI gain were observed in 51.2% and 47.1% of the patients, respectively. Low baseline LTI was a significant predictor of all-cause mortality after adjusting for demographic and biochemical parameters (HR, 2.41; P = 0.047), but not when comorbidities were included in the multivariate analysis. However, after adjusting for various confounding factors, LTI loss (HR, 3.40; P = 0.039) and FTI gain (HR, 4.06; P = 0.024) were independent risk factors for all-cause mortality, and the adjusted HR for LTI loss and FTI gain vs. no LTI loss and no FTI gain was 5.34 ( P = 0.016). LTI loss and FTI gain, particularly their combination, are important predictors of survival in patients undergoing hemodialysis. Our results emphasize that longitudinal changes in LTI and FTI are more strongly associated with all-cause mortality than single-point values. Therefore, it is important to dynamically assess the muscle and fat tissues and develop potential targeted treatment strategies for this population.

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