Long-term Weight Loss as a Predictor of Mortality in Hemodialysis Patients.
body mass index
follow-up study
haemodialysis
mortality
Journal
Journal of epidemiology
ISSN: 1349-9092
Titre abrégé: J Epidemiol
Pays: Japan
ID NLM: 9607688
Informations de publication
Date de publication:
05 08 2023
05 08 2023
Historique:
medline:
8
8
2023
pubmed:
15
3
2022
entrez:
14
3
2022
Statut:
ppublish
Résumé
Serial weight decrease can be a prognostic predictor in chronic hemodialysis (HD) patients. We investigated the impact of long-term post-HD body weight (BW) changes on all-cause mortality among HD patients. This longitudinal cohort study and post-hoc analysis evaluated participants of a previous randomized controlled trial conducted between 2006 and 2011 who were followed up until 2018. Weight change slopes were generated with repeated measurements every 6 months during the trial for patients having ≥5 BW measurements. Participants were categorized into four groups based on quartiles of weight change slopes; the median weight changes per 6 months were -1.02 kg, -0.25 kg, +0.26 kg, and +0.86 kg for first, second, third, and fourth quartile, respectively. Cox proportional hazard regression was used to evaluate differences in subsequent survival among the four groups. BW trajectories were plotted with a backward time-scale and multilevel regression analysis to visualize the difference in BW trajectories between survivors and non-survivors. Among the 461 patients, 404 were evaluated, and 168 (41.6%) died within a median follow-up period of 10.2 years. The Cox proportional hazard regression adjusted for covariates and baseline BW showed that a higher rate of weight loss was associated with higher mortality. The hazard ratios were 2.02 (95% confidence interval [CI], 1.28-3.20), 1.77 (95% CI, 1.10-2.85), 1.00 (reference), and 1.11 (95% CI, 0.67-1.83) for the first, second, third (reference), and fourth quartiles, respectively. BW trajectories revealed a significant decrease in BW in non-survivors. Weight loss elucidated via serial BW measurements every 6 months is significantly associated with higher mortality among HD patients.
Sections du résumé
BACKGROUND
Serial weight decrease can be a prognostic predictor in chronic hemodialysis (HD) patients. We investigated the impact of long-term post-HD body weight (BW) changes on all-cause mortality among HD patients.
METHODS
This longitudinal cohort study and post-hoc analysis evaluated participants of a previous randomized controlled trial conducted between 2006 and 2011 who were followed up until 2018. Weight change slopes were generated with repeated measurements every 6 months during the trial for patients having ≥5 BW measurements. Participants were categorized into four groups based on quartiles of weight change slopes; the median weight changes per 6 months were -1.02 kg, -0.25 kg, +0.26 kg, and +0.86 kg for first, second, third, and fourth quartile, respectively. Cox proportional hazard regression was used to evaluate differences in subsequent survival among the four groups. BW trajectories were plotted with a backward time-scale and multilevel regression analysis to visualize the difference in BW trajectories between survivors and non-survivors.
RESULTS
Among the 461 patients, 404 were evaluated, and 168 (41.6%) died within a median follow-up period of 10.2 years. The Cox proportional hazard regression adjusted for covariates and baseline BW showed that a higher rate of weight loss was associated with higher mortality. The hazard ratios were 2.02 (95% confidence interval [CI], 1.28-3.20), 1.77 (95% CI, 1.10-2.85), 1.00 (reference), and 1.11 (95% CI, 0.67-1.83) for the first, second, third (reference), and fourth quartiles, respectively. BW trajectories revealed a significant decrease in BW in non-survivors.
CONCLUSION
Weight loss elucidated via serial BW measurements every 6 months is significantly associated with higher mortality among HD patients.
Identifiants
pubmed: 35283398
doi: 10.2188/jea.JE20210389
pmc: PMC10319526
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM