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

Our plain-English summary of Entropy Analysis for the Evaluation of Respiratory Changes Due to Asbestos Exposure and Associated Smoking, by P.M. Sá, H.A. Castro, A.J. Lopes, et al (Entropy, 2019).

The study

• Authors: P.M. Sá, H.A. Castro, A.J. Lopes, P.L. Melo
• Journal: Entropy
• Published: 2019;21(3)
• Cited by: 3 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

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.

In plain English

This Brazilian study compared breathing signals of workers exposed to asbestos with those of healthy controls. It used 'entropy' measures, which describe how regular or irregular a signal is. The workers came from a public-health research center in Rio de Janeiro and had no clinical diagnosis of asbestosis. One analysis used 34 controls and 34 exposed workers, and another used 34 controls and 30 exposed workers. In each, 12 exposed workers were smokers. Entropy of respiratory impedance, measured with a forced oscillation device, did not differ significantly between groups. One airflow measure, recurrence period density entropy, was significantly lower than in controls among exposed workers overall, exposed non-smokers and exposed smokers. Another, sample entropy, was lower in exposed smokers than in controls and exposed non-smokers. To test how well the measures separated exposed workers from controls, the authors set 0.7 on a 0-to-1 score (area under the curve) as useful. After cross-validation, the airflow recurrence measure scored 0.72 across all exposed workers. The authors concluded that entropy analysis might be an early, sensitive indicator of future interstitial asbestosis. They noted their small sample.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Cross-sectional comparison of asbestos-exposed workers and controls, described by the authors as a validation study, with diagnostic-accuracy (ROC curve) analysis
• Who was studied: Workers exposed to asbestos but without a clinical diagnosis of asbestosis, from the Workers' Health and Human Ecology Study Center (CESTEH), Oswaldo Cruz Foundation, Rio de Janeiro, Brazil. Impedance analysis: 34 controls and 34 exposed workers (29 with radiographs categorized 0/0, 5 with 0/1 or 1/1; 12 smokers). Airflow analysis: 34 controls and 30 exposed workers (25 categorized 0/0, 5 categorized 0/1 or 1/1; 12 smokers). Controls had normal spirometry and no history of smoking or pulmonary disease. Study dates not given.
• Exposure: Occupational asbestos exposure, with smoking examined as an additional factor. Fiber types, jobs, products and exposure levels are not reported.
• Main results:
  • No significant differences in impedance entropy (SampEnZrs or RPDEnZrs) between controls and the general exposed group, exposed non-smokers or exposed smokers
  • Recurrence period density entropy of airflow (RPDEnV') was significantly lower in all asbestos-exposed groups than in controls
  • The RPDEnV' reduction compared with controls was p less than 0.0004 in exposed non-smokers and p less than 0.05 in exposed smokers
  • Sample entropy of airflow (SampEnV') was significantly lower in exposed smokers than in controls (p less than 0.04) and than in exposed non-smokers (p less than 0.02). It did not differ significantly from controls in the general exposed group or in non-smokers.
  • In the airflow analysis, exposed workers had lower FVC (2.84 vs 3.15 L in controls, p less than 0.03) and FEV1 (2.08 vs 2.51 L, p less than 0.004). The authors noted these changes were still within the normal range.
  • Diagnostic accuracy in all exposed workers: RPDEnV' had AUC 0.766 (sensitivity 70.0%, specificity 64.7%). After leave-one-out cross-validation it had AUC 0.72 (sensitivity 0.64, specificity 0.64). The authors treated an AUC of 0.7 as the threshold for clinical usefulness.
  • Diagnostic accuracy in exposed non-smokers: RPDEnV' had AUC 0.796 (sensitivity 88.9%, specificity 58.8%). After cross-validation it had AUC 0.79 (sensitivity 0.89, specificity 0.61).
  • Diagnostic accuracy in exposed smokers, after cross-validation: SampEnV' had AUC 0.71 (sensitivity 0.67, specificity 0.59) and RPDEnV' had AUC 0.70 (sensitivity 0.75, specificity 0.50)
  • Impedance entropy measures did not reach adequate diagnostic accuracy in any group
  • The authors described these entropy measures as regularity indexes. They cautioned that changes in them do not necessarily represent changes in complexity, though they argued a complexity interpretation was justified in this study.
• The authors' conclusion: The authors concluded that entropy analysis might be an early and sensitive functional indicator of future interstitial asbestosis, and that the findings should be confirmed in larger groups
• Limitations the authors state:
  • Relatively small sample size
  • Results are valid only within the studied groups
  • The evaluation of smoking effects was only preliminary
  • Sample entropy parameters were not optimized
  • Only two entropy measures were examined; others were not explored

Topics

Medical terms in this study, explained in our Lexicon: Asbestos Exposure, Interstitial.

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