Prediction of air trapping or pulmonary hyperinflation by forced spirometry in COPD patients: results from COSYCONET.


Journal

ERJ open research
ISSN: 2312-0541
Titre abrégé: ERJ Open Res
Pays: England
ID NLM: 101671641

Informations de publication

Date de publication:
Jul 2020
Historique:
received: 25 02 2020
accepted: 19 05 2020
entrez: 4 8 2020
pubmed: 4 8 2020
medline: 4 8 2020
Statut: epublish

Résumé

Air trapping and lung hyperinflation are major determinants of prognosis and response to therapy in chronic obstructive pulmonary disease (COPD). They are often determined by body plethysmography, which has limited availability, and so the question arises as to what extent they can be estimated We used data from visits 1-5 of the COPD cohort COSYCONET. Predictive parameters were derived from visit 1 data, while visit 2-5 data was used to assess reproducibility. Pooled data then yielded prediction models including sex, age, height, and body mass index as covariates. Hyperinflation was defined as ratio of residual volume (RV) to total lung capacity (TLC) above the upper limit of normal. (ClinicalTrials.gov identifier: NCT01245933). Visit 1 data from 1988 patients (Global Initiative for Chronic Obstructive Lung Disease grades 1-4, n=187, 847, 766, 188, respectively) were available for analysis (n=1231 males, 757 females; mean±sd age 65.1±8.4 years; forced expiratory volume in 1 s (FEV The degree of air trapping/hyperinflation in terms of RV/TLC can be estimated in a simple manner from forced spirometry, with an accuracy sufficient for inferring the presence of hyperinflation. This may be useful for clinical settings, where body plethysmography is not available.

Sections du résumé

BACKGROUND BACKGROUND
Air trapping and lung hyperinflation are major determinants of prognosis and response to therapy in chronic obstructive pulmonary disease (COPD). They are often determined by body plethysmography, which has limited availability, and so the question arises as to what extent they can be estimated
METHODS METHODS
We used data from visits 1-5 of the COPD cohort COSYCONET. Predictive parameters were derived from visit 1 data, while visit 2-5 data was used to assess reproducibility. Pooled data then yielded prediction models including sex, age, height, and body mass index as covariates. Hyperinflation was defined as ratio of residual volume (RV) to total lung capacity (TLC) above the upper limit of normal. (ClinicalTrials.gov identifier: NCT01245933).
RESULTS RESULTS
Visit 1 data from 1988 patients (Global Initiative for Chronic Obstructive Lung Disease grades 1-4, n=187, 847, 766, 188, respectively) were available for analysis (n=1231 males, 757 females; mean±sd age 65.1±8.4 years; forced expiratory volume in 1 s (FEV
CONCLUSIONS CONCLUSIONS
The degree of air trapping/hyperinflation in terms of RV/TLC can be estimated in a simple manner from forced spirometry, with an accuracy sufficient for inferring the presence of hyperinflation. This may be useful for clinical settings, where body plethysmography is not available.

Identifiants

pubmed: 32743009
doi: 10.1183/23120541.00092-2020
pii: 00092-2020
pmc: PMC7383055
pii:
doi:

Banques de données

ClinicalTrials.gov
['NCT01245933']

Types de publication

Journal Article

Langues

eng

Informations de copyright

Copyright ©ERS 2020.

Déclaration de conflit d'intérêts

Conflict of interest: P. Alter reports grants from German Federal Ministry of Education and Research (BMBF) Competence Network Asthma and COPD (ASCONET); grants from AstraZeneca GmbH; grants and nonfinancial support from Bayer Schering Pharma AG; grants, personal fees and nonfinancial support from Boehringer Ingelheim Pharma GmbH & Co. KG; grants and nonfinancial support from Chiesi GmbH; grants from GlaxoSmithKline; grants from Grifols Deutschland GmbH; grants from MSD Sharp & Dohme GmbH; grants and personal fees from Mundipharma GmbH; grants, personal fees and nonfinancial support from Novartis Deutschland GmbH; and grants from Pfizer Pharma GmbH; grants from Takeda Pharma Vertrieb GmbH & Co. KG, all outside the submitted work. Conflict of interest: J. Orszag has nothing to disclose. Conflict of interest: C. Kellerer has nothing to disclose. Conflict of interest: K. Kahnert has nothing to disclose Conflict of interest: T. Speicher has nothing to disclose. Conflict of interest: H. Watz has nothing to disclose. Conflict of interest: R. Bals reports grants and personal fees from AstraZeneca; grants and personal fees from Boehringer Ingelheim; personal fees from GlaxoSmithKline; personal fees from Grifols; grants and personal fees from Novartis; personal fees from CSL Behring; grants from German Federal Ministry of Education and Research (BMBF) Competence Network Asthma and COPD (ASCONET); grants from Sander Stiftung; grants from Schwiete Stiftung; grants from Krebshilfe; and grants from Mukoviszidose eV, all outside the submitted work. Conflict of interest: T. Welte reports grants from the German Ministry of Research and Education during the conduct of the study, and personal fees from Novartis and Boehringer Ingelheim outside the submitted work. Conflict of interest: C.F. Vogelmeier reports grants and personal fees from AstraZeneca; grants and personal fees from Boehringer Ingelheim; personal fees from CSL Behring; personal fees from Chiesi; grants and personal fees from GlaxoSmithKline; grants and personal fees from Grifols; personal fees from Menarini; personal fees from Mundipharma; grants and personal fees from Novartis; personal fees from Nuvaira; personal fees from OmniaMed; and personal fees from MedUpdate, all outside the submitted work. Conflict of interest: R.A. Jörres reports grants from German Federal Ministry of Education and Research (BMBF) Competence Network Asthma and COPD (ASCONET); grants from AstraZeneca GmbH; grants from Bayer Schering Pharma AG; grants and personal fees from Boehringer Ingelheim Pharma GmbH & Co. KG; grants from Chiesi GmbH; grants and personal fees from GlaxoSmithKline; grants from Grifols Deutschland GmbH; grants from MSD Sharp & Dohme GmbH; grants and personal fees from Mundipharma GmbH; grants and personal fees from Novartis Deutschland GmbH; grants from Pfizer Pharma GmbH; grants from Takeda Pharma Vertrieb GmbH & Co. KG; personal fees from Custo Med GmbH; personal fees from Bosch; personal fees from Siemens; and grants and personal fees from Lufthansa, all outside the submitted work.

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Auteurs

Peter Alter (P)

Dept of Medicine, Pulmonary and Critical Care Medicine, Philipps University of Marburg (UMR), member of the German Center for Lung Research (DZL), Marburg, Germany.

Jan Orszag (J)

Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Comprehensive Pneumology Center Munich (CPC-M), member of the DZL, Munich, Germany.

Christina Kellerer (C)

School of Medicine, Institute of General Practice and Health Services Research, Technical University of Munich, Munich, Germany.

Kathrin Kahnert (K)

Dept of Internal Medicine V, University Hospital, LMU Munich, CPC-M, member of the DZL, Munich, Germany.

Tim Speicher (T)

Dept of Medicine, Pulmonary and Critical Care Medicine, Philipps University of Marburg (UMR), member of the German Center for Lung Research (DZL), Marburg, Germany.

Henrik Watz (H)

Pulmonary Research Institute at LungenClinic Grosshansdorf, Airway Research Center North, member of the DZL, Grosshansdorf, Germany.

Robert Bals (R)

Dept of Internal Medicine V - Pulmonology, Allergology, Intensive Care Medicine, Saarland University Hospital, Homburg, Germany.

Tobias Welte (T)

Clinic for Pneumology, Hannover Medical School, member of the DZL, Hannover, Germany.

Claus F Vogelmeier (CF)

Dept of Medicine, Pulmonary and Critical Care Medicine, Philipps University of Marburg (UMR), member of the German Center for Lung Research (DZL), Marburg, Germany.

Rudolf A Jörres (RA)

Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Comprehensive Pneumology Center Munich (CPC-M), member of the DZL, Munich, Germany.

Classifications MeSH