Cargando…

Resilience in Incident Hemodialysis: Characterization and Outcome Prediction

The Resiliency in Dialysis Initiation (ReDI) Study aims to develop physical resilience signatures in older adults initiating hemodialysis. Study design—comprising a pilot, confirmatory study, and secondary data analyses—will be presented. So also will a method for characterizing resilience phenotype...

Descripción completa

Detalles Bibliográficos
Autores principales: Bandeen-Roche, Karen, Zhu, Jiafeng, Crews, Deidra, McAdams-DeMarco, Mara, Buta, Brian, Varadhan, Ravi, Walston, Jeremy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7742740/
http://dx.doi.org/10.1093/geroni/igaa057.2713
_version_ 1783624058970046464
author Bandeen-Roche, Karen
Zhu, Jiafeng
Crews, Deidra
McAdams-DeMarco, Mara
Buta, Brian
Varadhan, Ravi
Walston, Jeremy
author_facet Bandeen-Roche, Karen
Zhu, Jiafeng
Crews, Deidra
McAdams-DeMarco, Mara
Buta, Brian
Varadhan, Ravi
Walston, Jeremy
author_sort Bandeen-Roche, Karen
collection PubMed
description The Resiliency in Dialysis Initiation (ReDI) Study aims to develop physical resilience signatures in older adults initiating hemodialysis. Study design—comprising a pilot, confirmatory study, and secondary data analyses—will be presented. So also will a method for characterizing resilience phenotypes—using mixed-model analysis of SF-36 subscale trajectories—among participants of age 55 and older who had undergone hemodialysis in the Choices for Healthy Outcomes in Caring for ESRD study (n=485). Analyses revealed stable, improving, and declining phenotypes. In Cox models, both baseline phenotypic status and trajectory type predicted mortality after adjusting for age, CVD status, and CHF (global Wald test for trajectory type P-value=0.020 for vitality; 0.030 for general health). These analyses evidence usefulness of resilience phenotypes as markers of adverse outcome risk and foreshadow application to novel ReDI data.
format Online
Article
Text
id pubmed-7742740
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-77427402020-12-21 Resilience in Incident Hemodialysis: Characterization and Outcome Prediction Bandeen-Roche, Karen Zhu, Jiafeng Crews, Deidra McAdams-DeMarco, Mara Buta, Brian Varadhan, Ravi Walston, Jeremy Innov Aging Abstracts The Resiliency in Dialysis Initiation (ReDI) Study aims to develop physical resilience signatures in older adults initiating hemodialysis. Study design—comprising a pilot, confirmatory study, and secondary data analyses—will be presented. So also will a method for characterizing resilience phenotypes—using mixed-model analysis of SF-36 subscale trajectories—among participants of age 55 and older who had undergone hemodialysis in the Choices for Healthy Outcomes in Caring for ESRD study (n=485). Analyses revealed stable, improving, and declining phenotypes. In Cox models, both baseline phenotypic status and trajectory type predicted mortality after adjusting for age, CVD status, and CHF (global Wald test for trajectory type P-value=0.020 for vitality; 0.030 for general health). These analyses evidence usefulness of resilience phenotypes as markers of adverse outcome risk and foreshadow application to novel ReDI data. Oxford University Press 2020-12-16 /pmc/articles/PMC7742740/ http://dx.doi.org/10.1093/geroni/igaa057.2713 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstracts
Bandeen-Roche, Karen
Zhu, Jiafeng
Crews, Deidra
McAdams-DeMarco, Mara
Buta, Brian
Varadhan, Ravi
Walston, Jeremy
Resilience in Incident Hemodialysis: Characterization and Outcome Prediction
title Resilience in Incident Hemodialysis: Characterization and Outcome Prediction
title_full Resilience in Incident Hemodialysis: Characterization and Outcome Prediction
title_fullStr Resilience in Incident Hemodialysis: Characterization and Outcome Prediction
title_full_unstemmed Resilience in Incident Hemodialysis: Characterization and Outcome Prediction
title_short Resilience in Incident Hemodialysis: Characterization and Outcome Prediction
title_sort resilience in incident hemodialysis: characterization and outcome prediction
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7742740/
http://dx.doi.org/10.1093/geroni/igaa057.2713
work_keys_str_mv AT bandeenrochekaren resilienceinincidenthemodialysischaracterizationandoutcomeprediction
AT zhujiafeng resilienceinincidenthemodialysischaracterizationandoutcomeprediction
AT crewsdeidra resilienceinincidenthemodialysischaracterizationandoutcomeprediction
AT mcadamsdemarcomara resilienceinincidenthemodialysischaracterizationandoutcomeprediction
AT butabrian resilienceinincidenthemodialysischaracterizationandoutcomeprediction
AT varadhanravi resilienceinincidenthemodialysischaracterizationandoutcomeprediction
AT walstonjeremy resilienceinincidenthemodialysischaracterizationandoutcomeprediction