학술논문
Analyzing key elements of breathing patterns, deriving remaining variables, and identifying cutoff values in individuals with chronic respiratory disease and healthy subjects.
Document Type
Academic Journal
Author
Chuang ML; Division of Pulmonary Medicine and Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung 40201, Taiwan, ROC; School of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan, ROC. Electronic address: yuan1007@ms36.hinet.net.
Source
Publisher: Elsevier Science Country of Publication: Netherlands NLM ID: 101140022 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1878-1519 (Electronic) Linking ISSN: 15699048 NLM ISO Abbreviation: Respir Physiol Neurobiol Subsets: MEDLINE
Subject
Language
English
Abstract
Background: Pulmonary physiology encompasses intricate breathing patterns (BPs), characterized by breathing frequency (Bf), volumes, and flows. The complexities intensify in the presence of interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD), especially during exercise. This study seeks to identify pivotal factors driving changes among these variables and establish cutoff values, comparing their efficacy in differentiating BPs to traditional methods, specifically a breathing reserve (BR) of 30% and a Bf of 50 bpm.
Methods: Screening 267 subjects revealed 23 with ILD, 126 with COPD, 33 healthy individuals, and the exclusion of 85 subjects. Lung function tests and ramp-pattern cardiopulmonary exercise testing (CPET) were conducted, identifying crucial BP elements. Changes were compared between groups at peak exercise. The area under the receiver operating characteristic curve (AUC) analysis determined cutoff values.
Results: Inspiratory time (TI) remained constant at peak exercise for all subjects (two-group comparisons, all p=NS). Given known differences in expiratory time (TE) and tidal volume (VT) among ILD, COPD, and healthy states, constant TI could infer patterns for Bf, total breathing cycle time (TTOT=60/Bf), I:E ratio, inspiratory duty cycle (IDC, TI/TTOT), rapid shallow breathing index (Bf/VT), tidal inspiratory and expiratory flows (VT/TI and VT/TE), and minute ventilation (V̇E=Bf×VT) across conditions. These inferences aligned with measurements, with potential type II errors causing inconsistencies. RSBI of 23 bpm/L and VT/TI of 104 L/min may differentiate ILD from control, while V̇E of 54 L/min, BR of 30%, and VT/TE of 108 may differentiate COPD from control. BR of 21%, TE of 0.99 s, and IDC of .45 may differentiate ILD from COPD. The algorithm outperformed traditional methods (AUC 0.84-0.91 versus 0.59-0.90).
Conclusion: The quasi-fixed TI, in conjunction with TE and VT, proves effective in inferring time-related variables of BPs. The findings have the potential to significantly enhance medical education in interpreting cardiopulmonary exercise testing. Moreover, the study introduces a novel algorithm for distinguishing BPs among individuals with ILD, COPD, and those who are healthy.
Competing Interests: Declaration of Competing Interest The authors declare no competing interests.
(Copyright © 2024. Published by Elsevier B.V.)
Methods: Screening 267 subjects revealed 23 with ILD, 126 with COPD, 33 healthy individuals, and the exclusion of 85 subjects. Lung function tests and ramp-pattern cardiopulmonary exercise testing (CPET) were conducted, identifying crucial BP elements. Changes were compared between groups at peak exercise. The area under the receiver operating characteristic curve (AUC) analysis determined cutoff values.
Results: Inspiratory time (TI) remained constant at peak exercise for all subjects (two-group comparisons, all p=NS). Given known differences in expiratory time (TE) and tidal volume (VT) among ILD, COPD, and healthy states, constant TI could infer patterns for Bf, total breathing cycle time (TTOT=60/Bf), I:E ratio, inspiratory duty cycle (IDC, TI/TTOT), rapid shallow breathing index (Bf/VT), tidal inspiratory and expiratory flows (VT/TI and VT/TE), and minute ventilation (V̇E=Bf×VT) across conditions. These inferences aligned with measurements, with potential type II errors causing inconsistencies. RSBI of 23 bpm/L and VT/TI of 104 L/min may differentiate ILD from control, while V̇E of 54 L/min, BR of 30%, and VT/TE of 108 may differentiate COPD from control. BR of 21%, TE of 0.99 s, and IDC of .45 may differentiate ILD from COPD. The algorithm outperformed traditional methods (AUC 0.84-0.91 versus 0.59-0.90).
Conclusion: The quasi-fixed TI, in conjunction with TE and VT, proves effective in inferring time-related variables of BPs. The findings have the potential to significantly enhance medical education in interpreting cardiopulmonary exercise testing. Moreover, the study introduces a novel algorithm for distinguishing BPs among individuals with ILD, COPD, and those who are healthy.
Competing Interests: Declaration of Competing Interest The authors declare no competing interests.
(Copyright © 2024. Published by Elsevier B.V.)