Understanding patient outcomes after acute respiratory distress syndrome: identifying subtypes of physical, cognitive and mental health outcomes
- PMID: 28778920
- PMCID: PMC5690818
- DOI: 10.1136/thoraxjnl-2017-210337
Understanding patient outcomes after acute respiratory distress syndrome: identifying subtypes of physical, cognitive and mental health outcomes
Abstract
Purpose: With improving short-term mortality in acute respiratory distress syndrome (ARDS), understanding survivors' posthospitalisation outcomes is increasingly important. However, little is known regarding associations among physical, cognitive and mental health outcomes. Identification of outcome subtypes may advance understanding of post-ARDS morbidities.
Methods: We analysed baseline variables and 6-month health status for participants in the ARDS Network Long-Term Outcomes Study. After division into derivation and validation datasets, we used weighted network analysis to identify subtypes from predictors and outcomes in the derivation dataset. We then used recursive partitioning to develop a subtype classification rule and assessed adequacy of the classification rule using a kappa statistic with the validation dataset.
Results: Among 645 ARDS survivors, 430 were in the derivation and 215 in the validation datasets. Physical and mental health status, but not cognitive status, were closely associated. Four distinct subtypes were apparent (percentages in the derivation cohort): (1) mildly impaired physical and mental health (22% of patients), (2) moderately impaired physical and mental health (39%), (3) severely impaired physical health with moderately impaired mental health (15%) and (4) severely impaired physical and mental health (24%). The classification rule had high agreement (kappa=0.89 in validation dataset). Female Latino smokers had the poorest status, while male, non-Latino non-smokers had the best status.
Conclusions: We identified four post-ARDS outcome subtypes that were predicted by sex, ethnicity, pre-ARDS smoking status and other baseline factors. These subtypes may help develop tailored rehabilitation strategies, including investigation of combined physical and mental health interventions, and distinct interventions to improve cognitive outcomes.
Keywords: ARDS; health-related quality of life; mental health; outcomes; physical function; prediction.
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Conflict of interest statement
Competing interests: None declared.
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Comment in
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Prediction of long-term outcome subtypes in ARDS: first steps towards personalised medicine in critical care.Thorax. 2017 Dec;72(12):1067-1068. doi: 10.1136/thoraxjnl-2017-210775. Epub 2017 Oct 7. Thorax. 2017. PMID: 28988218 No abstract available.
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