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Long-term Weight Loss as a Predictor of Mortality in Hemodialysis Patients

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 participa...

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Autores principales: Moromizato, Takuhiro, Sakaniwa, Ryoto, Miyauchi, Takamasa, So, Ryuhei, Iso, Hiroyasu, Iseki, Kunitoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japan Epidemiological Association 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10319526/
https://www.ncbi.nlm.nih.gov/pubmed/35283398
http://dx.doi.org/10.2188/jea.JE20210389
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author Moromizato, Takuhiro
Sakaniwa, Ryoto
Miyauchi, Takamasa
So, Ryuhei
Iso, Hiroyasu
Iseki, Kunitoshi
author_facet Moromizato, Takuhiro
Sakaniwa, Ryoto
Miyauchi, Takamasa
So, Ryuhei
Iso, Hiroyasu
Iseki, Kunitoshi
author_sort Moromizato, Takuhiro
collection PubMed
description 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.
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spelling pubmed-103195262023-08-05 Long-term Weight Loss as a Predictor of Mortality in Hemodialysis Patients Moromizato, Takuhiro Sakaniwa, Ryoto Miyauchi, Takamasa So, Ryuhei Iso, Hiroyasu Iseki, Kunitoshi J Epidemiol Original Article 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. Japan Epidemiological Association 2023-08-05 /pmc/articles/PMC10319526/ /pubmed/35283398 http://dx.doi.org/10.2188/jea.JE20210389 Text en © 2022 Takuhiro Moromizato et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Original Article
Moromizato, Takuhiro
Sakaniwa, Ryoto
Miyauchi, Takamasa
So, Ryuhei
Iso, Hiroyasu
Iseki, Kunitoshi
Long-term Weight Loss as a Predictor of Mortality in Hemodialysis Patients
title Long-term Weight Loss as a Predictor of Mortality in Hemodialysis Patients
title_full Long-term Weight Loss as a Predictor of Mortality in Hemodialysis Patients
title_fullStr Long-term Weight Loss as a Predictor of Mortality in Hemodialysis Patients
title_full_unstemmed Long-term Weight Loss as a Predictor of Mortality in Hemodialysis Patients
title_short Long-term Weight Loss as a Predictor of Mortality in Hemodialysis Patients
title_sort long-term weight loss as a predictor of mortality in hemodialysis patients
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10319526/
https://www.ncbi.nlm.nih.gov/pubmed/35283398
http://dx.doi.org/10.2188/jea.JE20210389
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