Bansal, T, Haji, GS, Rossiter, HB orcid.org/0000-0002-7884-0726 et al. (2 more authors) (2018) Exercise Ventilatory Irregularity can be quantified by Approximate Entropy to detect Breathing Pattern Disorder. Respiratory Physiology and Neurobiology, 255. pp. 1-6. ISSN 1569-9048
Abstract
Background
Breathing pattern disorder (BPD) is a prevalent cause of exertional dyspnea and yet there is currently no reliable objective measure for its diagnosis. We propose that statistical analysis of ventilatory irregularity, quantified by approximate entropy (ApEn), could be used to detect BPD when applied to cardiopulmonary exercise test (CPET) data. We hypothesized that ApEn of ventilatory variables (tidal volume (VT), breathing frequency (Bf), minute ventilation (VE)) would be greater, i.e. more irregular, in patients with BPD than healthy controls.
Methods
We evaluated ventilatory ApEn in 20 adults (14 female) with exertional dyspnoea, undergoing CPET and independently diagnosed with BPD by a specialist respiratory physiotherapist. Data were compared with 15 age- gender- and BMI-matched controls. ApEn for VT, Bf and VE were calculated for an incremental cycle exercise test.
Results
Patients with BPD more frequently rated breathlessness as the reason for exercise limitation and had a lower mean (SD) peak oxygen uptake compared with controls: 80 (18) vs. 124 (27) % predicted (P < 0.001). ApEn was significantly greater for VT (p = 0.006) and VE (p = 0.002) in BPD than controls. ApEn VE was inversely related (r2 = 0.24, p = 0.03) to peak oxygen uptake in BPD but not controls. ROC analysis revealed that ApEn VE > 0.88, conferred a sensitivity and specificity of 70% and 87% respectively, for detection of BPD.
Conclusions
Non-linear statistical interrogation of CPET-acquired ventilatory data has utility in the detection of BPD. A simple calculation of approximate entropy of ventilation, during an incremental cardiopulmonary exercise test, provides a quantitative method to detect BPD.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Elsevier B.V. This is an author produced version of a paper published in Respiratory Physiology and Neurobiology. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Dyspnea; exercise; cardiopulmonary; entropy; breathing |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biomedical Sciences (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 May 2018 10:46 |
Last Modified: | 03 May 2019 00:42 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.resp.2018.05.002 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:130567 |