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Entropy 2019, 21(3), 225; https://doi.org/10.3390/e21030225

Entropy Analysis for the Evaluation of Respiratory Changes Due to Asbestos Exposure and Associated Smoking

1
Institute of Biology and Faculty of Engineering, Biomedical Instrumentation Laboratory, State University of Rio de Janeiro, Rio de Janeiro 20550-900, Brazil
2
Oswaldo Cruz Foundation, National School of Public Health, Rio de Janeiro 21040-900, Brazil
3
Pedro Ernesto University Hospital, State University of Rio de Janeiro, Rio de Janeiro 20550-900, Brazil
4
Rehabilitation Sciences Post-Graduate Programme, Augusto Motta University Centre, Rio de Janeiro 21041-020, Brazil
5
Laboratory of Clinical and Experimental Research in Vascular Biology, State University of Rio de Janeiro, Rio de Janeiro 20550-900, Brazil
*
Author to whom correspondence should be addressed.
Received: 10 December 2018 / Revised: 21 February 2019 / Accepted: 22 February 2019 / Published: 27 February 2019
(This article belongs to the Special Issue The 20th Anniversary of Entropy - Approximate and Sample Entropy)
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Abstract

Breathing is a complex rhythmic motor act, which is created by integrating different inputs to the respiratory centres. Analysing nonlinear fluctuations in breathing may provide clinically relevant information in patients with complex illnesses, such as asbestosis. We evaluated the effect of exposition to asbestos on the complexity of the respiratory system by investigating the respiratory impedance sample entropy (SampEnZrs) and recurrence period density entropy (RPDEnZrs). Similar analyses were performed by evaluating the airflow pattern sample entropy (SampEnV’) and recurrence period density entropy (RPDEnV’). Groups of 34 controls and 34 asbestos-exposed patients were evaluated in the respiratory impedance entropy analysis, while groups of 34 controls and 30 asbestos-exposed patients were investigated in the analysis of airflow entropy. Asbestos exposition introduced a significant reduction of RPDEnV’ in non-smoker patients (p < 0.0004), which suggests that the airflow pattern becomes less complex in these patients. Smoker patients also presented a reduction in RPDEnV’ (p < 0.05). These finding are consistent with the reduction in respiratory system adaptability to daily life activities observed in these patients. It was observed a significant reduction in SampEnV’ in smoker patients in comparison with non-smokers (p < 0.02). Diagnostic accuracy evaluations in the whole group of patients (including non-smokers and smokers) indicated that RPDEnV’ might be useful in the diagnosis of respiratory abnormalities in asbestos-exposed patients, showing an accuracy of 72.0%. In specific groups of non-smokers, RPDEnV’ also presented adequate accuracy (79.0%), while in smoker patients, SampEnV’ and RPDEnV’ presented adequate accuracy (70.7% and 70.2%, respectively). Taken together, these results suggest that entropy analysis may provide an early and sensitive functional indicator of interstitial asbestosis. View Full-Text
Keywords: sample entropy; recurrence period density entropy; respiratory system complexity; asbestos-exposed workers; smoking; diagnostic; early diagnosis; respiratory diseases; forced oscillation technique; respiratory impedance sample entropy; recurrence period density entropy; respiratory system complexity; asbestos-exposed workers; smoking; diagnostic; early diagnosis; respiratory diseases; forced oscillation technique; respiratory impedance
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Sá, P.M.; Castro, H.A.; Lopes, A.J.; Melo, P.L. Entropy Analysis for the Evaluation of Respiratory Changes Due to Asbestos Exposure and Associated Smoking. Entropy 2019, 21, 225.

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