ArticlePloS one2016
Early Diagnosis of Respiratory Abnormalities in Asbestos-Exposed Workers by the Forced Oscillation Technique.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 21 citations in OpenAlex.
- Interpretable machine learning methods based on oscillometry and electric modeling for the diagnostic of respiratory dysfunction in silicosis.BMC medical informatics and decision making · 2026Article
- Respiratory abnormalities in sarcoidosis: physiopathology and early diagnosis using oscillometry combined with respiratory modeling.BMC pulmonary medicine · 2025Observational
- Prediction of Abnormal Functional Performance in Chronic Obstructive Pulmonary Disease Using Respiratory Models: A Pilot Study.International journal of chronic obstructive pulmonary disease · 2025Article
- Combined forced oscillation and fractional-order modeling in patients with work-related asthma: a case-control study analyzing respiratory biomechanics and diagnostic accuracy.Biomedical engineering online · 2020Article
- Evaluation of forced oscilometry technique's parameters in severe obstructive sleep apnea patients without breathing disorder.Journal of family medicine and primary care · 2020Article
- Lung Function Assessment by Impulse Oscillometry in Adults.Therapeutics and clinical risk management · 2020Review
- Oscillation Mechanics, Integer and Fractional Respiratory Modeling in COPD: Effect of Obstruction Severity.International journal of chronic obstructive pulmonary disease · 2020Article
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- Forced oscillation technique for early detection of the effects of smoking and COPD: contribution of fractional-order modeling.International journal of chronic obstructive pulmonary diseaseArticle
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Authors and funding
4 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe current reference test for the detection of respiratory abnormalities in asbestos-exposed workers is spirometry. However, spirometry has several shortcomings that greatly affect the efficacy of current asbestos control programs. The forced oscillation technique (FOT) represents the current state-of-the-art technique in the assessment of lung function. This method provides a detailed analysis of respiratory resistance and reactance at different oscillatory frequencies during tidal breathing. Here, we evaluate the FOT as an alternative method to standard spirometry for the early detection and quantification of respiratory abnormalities in asbestos-exposed workers. METHODOLOGY/PRINCIPAL
findingsSeventy-two subjects were analyzed. The control group was composed of 33 subjects with a normal spirometric exam who had no history of smoking or pulmonary disease. Thirty-nine subjects exposed to asbestos were also studied, including 32 volunteers in radiological category 0/0 and 7 volunteers with radiological categories of 0/1 or 1/1. FOT data were interpreted using classical parameters as well as integer (InOr) and fractional-order (FrOr) modeling. The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). Exposed workers presented increased obstruction (resistance p<0.001) and a reduced compliance (p<0.001), with a predominance of obstructive changes. The FOT parameter changes were correlated with the standard pulmonary function analysis methods (R = -0.52, p<0.001). Early respiratory abnormalities were identified with a high diagnostic accuracy (AUC = 0.987) using parameters obtained from the FrOr modeling. This accuracy was significantly better than those obtained with classical (p<0.001) and InOr (p<0.001) model parameters.
conclusionsThe FOT improved our knowledge about the biomechanical abnormalities in workers exposed to asbestos. Additionally, a high diagnostic accuracy in the diagnosis of early respiratory abnormalities in asbestos-exposed workers was obtained. This makes the FOT particularly useful as a screening tool in the context of asbestos control and elimination. Moreover, it can facilitate epidemiological research and the longitudinal follow-up of asbestos exposure and asbestos-related diseases.
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