COPD profiles and treatable traits using minimal resources: identification, decision tree and stability over time.


Journal

Respiratory research
ISSN: 1465-993X
Titre abrégé: Respir Res
Pays: England
ID NLM: 101090633

Informations de publication

Date de publication:
14 Feb 2022
Historique:
received: 19 10 2021
accepted: 08 02 2022
entrez: 15 2 2022
pubmed: 16 2 2022
medline: 22 3 2022
Statut: epublish

Résumé

Profiles of people with chronic obstructive pulmonary disease (COPD) often do not describe treatable traits, lack validation and/or their stability over time is unknown. We aimed to identify COPD profiles and their treatable traits based on simple and meaningful measures; to develop and validate a decision tree and to explore profile stability over time. An observational, prospective study was conducted. Clinical characteristics, lung function, symptoms, impact of the disease (COPD Assessment Test-CAT), health-related quality of life, physical activity, lower-limb muscle strength and functional status were collected cross-sectionally and a subsample was followed-up monthly over six months. A principal component analysis and a clustering procedure with k-medoids were applied to identify profiles. A decision tree was developed and validated cross-sectionally. Stability was explored over time with the ratio between the number of timepoints that a participant was classified in the same profile and the total number of timepoints (i.e., 6). 352 people with COPD (67.4 ± 9.9 years; 78.1% male; FEV Four profiles and treatable traits were identified with simple and meaningful measures possibly available in low-resource settings. A decision tree with three commonly used variables in the routine assessment of people with COPD is now available for quick allocation to the identified profiles in clinical practice. Profiles and treatable traits may change over time in people with COPD hence, regular assessments to deliver goal-targeted personalised treatments are needed.

Sections du résumé

BACKGROUND AND OBJECTIVE OBJECTIVE
Profiles of people with chronic obstructive pulmonary disease (COPD) often do not describe treatable traits, lack validation and/or their stability over time is unknown. We aimed to identify COPD profiles and their treatable traits based on simple and meaningful measures; to develop and validate a decision tree and to explore profile stability over time.
METHODS METHODS
An observational, prospective study was conducted. Clinical characteristics, lung function, symptoms, impact of the disease (COPD Assessment Test-CAT), health-related quality of life, physical activity, lower-limb muscle strength and functional status were collected cross-sectionally and a subsample was followed-up monthly over six months. A principal component analysis and a clustering procedure with k-medoids were applied to identify profiles. A decision tree was developed and validated cross-sectionally. Stability was explored over time with the ratio between the number of timepoints that a participant was classified in the same profile and the total number of timepoints (i.e., 6).
RESULTS RESULTS
352 people with COPD (67.4 ± 9.9 years; 78.1% male; FEV
CONCLUSION CONCLUSIONS
Four profiles and treatable traits were identified with simple and meaningful measures possibly available in low-resource settings. A decision tree with three commonly used variables in the routine assessment of people with COPD is now available for quick allocation to the identified profiles in clinical practice. Profiles and treatable traits may change over time in people with COPD hence, regular assessments to deliver goal-targeted personalised treatments are needed.

Identifiants

pubmed: 35164762
doi: 10.1186/s12931-022-01954-6
pii: 10.1186/s12931-022-01954-6
pmc: PMC8842856
doi:

Types de publication

Journal Article Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

30

Subventions

Organisme : Fundação para a Ciência e a Tecnologia
ID : PTDC/SAU-SER/28806/2017
Organisme : Fundação para a Ciência e Tecnologia
ID : PTDC/DTP-PIC/2284/2014

Informations de copyright

© 2022. The Author(s).

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Auteurs

Alda Marques (A)

Lab3R - Respiratory Research and Rehabilitation Laboratory, School of Health Sciences, University of Aveiro (ESSUA), Agras do Crasto - Campus Universitário de Santiago, Edifício 30, 3810-193, Aveiro, Portugal. amarques@ua.pt.
iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Agras do Crasto - Campus Universitário de Santiago, Edifício 30, 3810-193, Aveiro, Portugal. amarques@ua.pt.

Sara Souto-Miranda (S)

Lab3R - Respiratory Research and Rehabilitation Laboratory, School of Health Sciences, University of Aveiro (ESSUA), Agras do Crasto - Campus Universitário de Santiago, Edifício 30, 3810-193, Aveiro, Portugal.
iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Agras do Crasto - Campus Universitário de Santiago, Edifício 30, 3810-193, Aveiro, Portugal.

Ana Machado (A)

Lab3R - Respiratory Research and Rehabilitation Laboratory, School of Health Sciences, University of Aveiro (ESSUA), Agras do Crasto - Campus Universitário de Santiago, Edifício 30, 3810-193, Aveiro, Portugal.
iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Agras do Crasto - Campus Universitário de Santiago, Edifício 30, 3810-193, Aveiro, Portugal.

Ana Oliveira (A)

Lab3R - Respiratory Research and Rehabilitation Laboratory, School of Health Sciences, University of Aveiro (ESSUA), Agras do Crasto - Campus Universitário de Santiago, Edifício 30, 3810-193, Aveiro, Portugal.
School of Rehabilitation Science, McMaster University, Hamilton, Canada.
West Park Healthcare Centre, Toronto, Canada.

Cristina Jácome (C)

Center for Health Technology and Services Research (CINTESIS) and Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal.

Joana Cruz (J)

Centre for Innovative Care and Health Technology (ciTechCare), Polytechnic of Leiria, Leiria, Portugal.

Vera Enes (V)

iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Agras do Crasto - Campus Universitário de Santiago, Edifício 30, 3810-193, Aveiro, Portugal.
Center for Research & Development in Mathematics and Applications (CIDMA), University of Aveiro, Aveiro, Portugal.

Vera Afreixo (V)

Center for Research & Development in Mathematics and Applications (CIDMA), University of Aveiro, Aveiro, Portugal.

Vitória Martins (V)

Pulmonology Department, Hospital Distrital Figueira Foz, Figueira da Foz, Portugal.

Lília Andrade (L)

Pulmonology Department, Centro Hospitalar do Baixo Vouga, Aveiro, Portugal.

Carla Valente (C)

Pulmonology Department, Centro Hospitalar do Baixo Vouga, Aveiro, Portugal.

Diva Ferreira (D)

Pulmonology Department, Centro Hospitalar do Médio Ave, Famalicão, Portugal.

Paula Simão (P)

Pulmonology Department, Unidade Local de Saúde de Matosinhos, Matosinhos, Portugal.

Dina Brooks (D)

School of Rehabilitation Science, McMaster University, Hamilton, Canada.
West Park Healthcare Centre, Toronto, Canada.

Ana Helena Tavares (AH)

Lab3R - Respiratory Research and Rehabilitation Laboratory, School of Health Sciences, University of Aveiro (ESSUA), Agras do Crasto - Campus Universitário de Santiago, Edifício 30, 3810-193, Aveiro, Portugal.
iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Agras do Crasto - Campus Universitário de Santiago, Edifício 30, 3810-193, Aveiro, Portugal.
Center for Research & Development in Mathematics and Applications (CIDMA), University of Aveiro, Aveiro, Portugal.

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