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Predicting outcomes following holistic breathlessness services: A pooled analysis of individual patient data

BACKGROUND: Holistic breathlessness services have been developed for people with advanced disease and chronic breathlessness, leading to improved psychological aspects of breathlessness and health. The extent to which patient characteristics influence outcomes is unclear. AIM: To identify patient ch...

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Autores principales: Brighton, Lisa Jane, Gao, Wei, Farquhar, Morag, Booth, Sara, Bajwah, Sabrina, Man, William D-C, Reilly, Charles C, Yi, Deokhee, Higginson, Irene J, Maddocks, Matthew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6439935/
https://www.ncbi.nlm.nih.gov/pubmed/30764714
http://dx.doi.org/10.1177/0269216319830299
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author Brighton, Lisa Jane
Gao, Wei
Farquhar, Morag
Booth, Sara
Bajwah, Sabrina
Man, William D-C
Reilly, Charles C
Yi, Deokhee
Higginson, Irene J
Maddocks, Matthew
author_facet Brighton, Lisa Jane
Gao, Wei
Farquhar, Morag
Booth, Sara
Bajwah, Sabrina
Man, William D-C
Reilly, Charles C
Yi, Deokhee
Higginson, Irene J
Maddocks, Matthew
author_sort Brighton, Lisa Jane
collection PubMed
description BACKGROUND: Holistic breathlessness services have been developed for people with advanced disease and chronic breathlessness, leading to improved psychological aspects of breathlessness and health. The extent to which patient characteristics influence outcomes is unclear. AIM: To identify patient characteristics predicting outcomes of mastery and distress due to breathlessness following holistic breathlessness services. DESIGN: Secondary analysis of pooled individual patient data from three clinical trials. Our primary analysis assessed predictors of clinically important improvements in Chronic Respiratory Questionnaire mastery scores (+0.5 point), and our secondary analysis predictors of improvements in Numerical Rating Scale distress due to breathlessness (−1 point). Variables significantly related to improvement in univariate models were considered in separate backwards stepwise logistic regression models. PARTICIPANTS: The dataset comprised 259 participants (118 female; mean (standard deviation) age 69.2 (10.6) years) with primary diagnoses of chronic obstructive pulmonary disease (49.8%), cancer (34.7%) and interstitial lung disease (10.4%). RESULTS: Controlling for age, sex and trial, baseline mastery remained the only significant independent predictor of improvement in mastery (odds ratio 0.57, 95% confidence intervals 0.43–0.74; p < 0.001), and baseline distress remained the only significant predictor of improvement in distress (odds ratio 1.64; 95% confidence intervals 1.35–2.03; p < 0.001). Baseline lung function, breathlessness severity, health status, mild anxiety and depression, and diagnosis did not predict outcomes. CONCLUSIONS: Outcomes of mastery and distress following holistic breathlessness services are influenced by baseline scores for these variables, and not by diagnosis, lung function or health status. Stratifying patients by levels of mastery and/or distress due to breathlessness appears appropriate for clinical trials and services.
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spelling pubmed-64399352019-04-29 Predicting outcomes following holistic breathlessness services: A pooled analysis of individual patient data Brighton, Lisa Jane Gao, Wei Farquhar, Morag Booth, Sara Bajwah, Sabrina Man, William D-C Reilly, Charles C Yi, Deokhee Higginson, Irene J Maddocks, Matthew Palliat Med Short Reports BACKGROUND: Holistic breathlessness services have been developed for people with advanced disease and chronic breathlessness, leading to improved psychological aspects of breathlessness and health. The extent to which patient characteristics influence outcomes is unclear. AIM: To identify patient characteristics predicting outcomes of mastery and distress due to breathlessness following holistic breathlessness services. DESIGN: Secondary analysis of pooled individual patient data from three clinical trials. Our primary analysis assessed predictors of clinically important improvements in Chronic Respiratory Questionnaire mastery scores (+0.5 point), and our secondary analysis predictors of improvements in Numerical Rating Scale distress due to breathlessness (−1 point). Variables significantly related to improvement in univariate models were considered in separate backwards stepwise logistic regression models. PARTICIPANTS: The dataset comprised 259 participants (118 female; mean (standard deviation) age 69.2 (10.6) years) with primary diagnoses of chronic obstructive pulmonary disease (49.8%), cancer (34.7%) and interstitial lung disease (10.4%). RESULTS: Controlling for age, sex and trial, baseline mastery remained the only significant independent predictor of improvement in mastery (odds ratio 0.57, 95% confidence intervals 0.43–0.74; p < 0.001), and baseline distress remained the only significant predictor of improvement in distress (odds ratio 1.64; 95% confidence intervals 1.35–2.03; p < 0.001). Baseline lung function, breathlessness severity, health status, mild anxiety and depression, and diagnosis did not predict outcomes. CONCLUSIONS: Outcomes of mastery and distress following holistic breathlessness services are influenced by baseline scores for these variables, and not by diagnosis, lung function or health status. Stratifying patients by levels of mastery and/or distress due to breathlessness appears appropriate for clinical trials and services. SAGE Publications 2019-02-15 2019-04 /pmc/articles/PMC6439935/ /pubmed/30764714 http://dx.doi.org/10.1177/0269216319830299 Text en © The Author(s) 2019 http://www.creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Short Reports
Brighton, Lisa Jane
Gao, Wei
Farquhar, Morag
Booth, Sara
Bajwah, Sabrina
Man, William D-C
Reilly, Charles C
Yi, Deokhee
Higginson, Irene J
Maddocks, Matthew
Predicting outcomes following holistic breathlessness services: A pooled analysis of individual patient data
title Predicting outcomes following holistic breathlessness services: A pooled analysis of individual patient data
title_full Predicting outcomes following holistic breathlessness services: A pooled analysis of individual patient data
title_fullStr Predicting outcomes following holistic breathlessness services: A pooled analysis of individual patient data
title_full_unstemmed Predicting outcomes following holistic breathlessness services: A pooled analysis of individual patient data
title_short Predicting outcomes following holistic breathlessness services: A pooled analysis of individual patient data
title_sort predicting outcomes following holistic breathlessness services: a pooled analysis of individual patient data
topic Short Reports
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6439935/
https://www.ncbi.nlm.nih.gov/pubmed/30764714
http://dx.doi.org/10.1177/0269216319830299
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