Respiratory abnormalities in sarcoidosis: physiopathology and early diagnosis using oscillometry combined with respiratory modeling

Abstract Background Sarcoidosis is a multisystemic syndrome of uncertain etiology with abnormal respiratory findings in approximately 90% of cases. Spirometry is the most common lung function test used for assessing lung function in diagnosis and monitoring pulmonary health. Respiratory oscillometry...

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Main Authors: Bruno Falcão Oliveira, Caroline Oliveira Ribeiro, Cíntia Moraes de Sá Sousa, Mariana Carneiro Lopes, Agnaldo José Lopes, Pedro Lopes de Melo
Format: Article
Language:English
Published: BMC 2025-02-01
Series:BMC Pulmonary Medicine
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Online Access:https://doi.org/10.1186/s12890-025-03510-6
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author Bruno Falcão Oliveira
Caroline Oliveira Ribeiro
Cíntia Moraes de Sá Sousa
Mariana Carneiro Lopes
Agnaldo José Lopes
Pedro Lopes de Melo
author_facet Bruno Falcão Oliveira
Caroline Oliveira Ribeiro
Cíntia Moraes de Sá Sousa
Mariana Carneiro Lopes
Agnaldo José Lopes
Pedro Lopes de Melo
author_sort Bruno Falcão Oliveira
collection DOAJ
description Abstract Background Sarcoidosis is a multisystemic syndrome of uncertain etiology with abnormal respiratory findings in approximately 90% of cases. Spirometry is the most common lung function test used for assessing lung function in diagnosis and monitoring pulmonary health. Respiratory oscillometry allows a simple alternative for the analysis of respiratory abnormalities. Integer-order and fractional-order modeling have increasingly been used to interpret measurements obtained from oscillometry, offering a detailed description of the respiratory system. In this study, we aimed to enhance our understanding of the pathophysiological changes in sarcoidosis and assess the diagnostic accuracy of these models. Methods This observational study includes 25 controls and 50 individuals with sarcoidosis divided into normal to spirometry (SNS) and abnormal spirometry (SAS). The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). Results The integer-order model showed significant airway and total resistance increases in the SNS and SAS groups. There was a reduction in compliance and an increase in peripheral resistance in the SAS group (p < 0.001). The fractional-order model showed increased energy dissipation and hysteresivity in the SNS and SAS groups. Correlation analysis revealed significant associations among model and spirometric parameters, where the strongest associations were between total resistance and FEV1 (r: -0.600, p = 0.0001). The diagnostic accuracy analysis showed that total resistance and hysteresivity were the best parameters, reaching an AUC = 0.986 and 0.938 in the SNS and SAS groups, respectively. Conclusion The studied models provided a deeper understanding of pulmonary mechanical changes in sarcoidosis. The results suggest that parameters obtained through the studied models enhance evaluation and enable better management of these patients. Specifically, total resistance and hysteresivity parameters demonstrated diagnostic potential, which may be beneficial for the early identification of individuals with sarcoidosis, even when spirometry results are within normal ranges.
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spelling doaj-art-76e4611193e7427da8547e3c554d56ff2025-02-09T12:09:33ZengBMCBMC Pulmonary Medicine1471-24662025-02-0125111310.1186/s12890-025-03510-6Respiratory abnormalities in sarcoidosis: physiopathology and early diagnosis using oscillometry combined with respiratory modelingBruno Falcão Oliveira0Caroline Oliveira Ribeiro1Cíntia Moraes de Sá Sousa2Mariana Carneiro Lopes3Agnaldo José Lopes4Pedro Lopes de Melo5Department of Physiology, State University of Rio de JaneiroDepartment of Physiology, State University of Rio de JaneiroDepartment of Physiology, State University of Rio de JaneiroFaculty of Medical Sciences, State University of Rio de JaneiroPulmonary Function Laboratory, State University of Rio de JaneiroDepartment of Physiology, State University of Rio de JaneiroAbstract Background Sarcoidosis is a multisystemic syndrome of uncertain etiology with abnormal respiratory findings in approximately 90% of cases. Spirometry is the most common lung function test used for assessing lung function in diagnosis and monitoring pulmonary health. Respiratory oscillometry allows a simple alternative for the analysis of respiratory abnormalities. Integer-order and fractional-order modeling have increasingly been used to interpret measurements obtained from oscillometry, offering a detailed description of the respiratory system. In this study, we aimed to enhance our understanding of the pathophysiological changes in sarcoidosis and assess the diagnostic accuracy of these models. Methods This observational study includes 25 controls and 50 individuals with sarcoidosis divided into normal to spirometry (SNS) and abnormal spirometry (SAS). The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). Results The integer-order model showed significant airway and total resistance increases in the SNS and SAS groups. There was a reduction in compliance and an increase in peripheral resistance in the SAS group (p < 0.001). The fractional-order model showed increased energy dissipation and hysteresivity in the SNS and SAS groups. Correlation analysis revealed significant associations among model and spirometric parameters, where the strongest associations were between total resistance and FEV1 (r: -0.600, p = 0.0001). The diagnostic accuracy analysis showed that total resistance and hysteresivity were the best parameters, reaching an AUC = 0.986 and 0.938 in the SNS and SAS groups, respectively. Conclusion The studied models provided a deeper understanding of pulmonary mechanical changes in sarcoidosis. The results suggest that parameters obtained through the studied models enhance evaluation and enable better management of these patients. Specifically, total resistance and hysteresivity parameters demonstrated diagnostic potential, which may be beneficial for the early identification of individuals with sarcoidosis, even when spirometry results are within normal ranges.https://doi.org/10.1186/s12890-025-03510-6Fractional order modelingForced oscillation techniqueRespiratory mechanicsBiomedical instrumentationInteger respiratory modelingDiagnose of respiratory diseases
spellingShingle Bruno Falcão Oliveira
Caroline Oliveira Ribeiro
Cíntia Moraes de Sá Sousa
Mariana Carneiro Lopes
Agnaldo José Lopes
Pedro Lopes de Melo
Respiratory abnormalities in sarcoidosis: physiopathology and early diagnosis using oscillometry combined with respiratory modeling
BMC Pulmonary Medicine
Fractional order modeling
Forced oscillation technique
Respiratory mechanics
Biomedical instrumentation
Integer respiratory modeling
Diagnose of respiratory diseases
title Respiratory abnormalities in sarcoidosis: physiopathology and early diagnosis using oscillometry combined with respiratory modeling
title_full Respiratory abnormalities in sarcoidosis: physiopathology and early diagnosis using oscillometry combined with respiratory modeling
title_fullStr Respiratory abnormalities in sarcoidosis: physiopathology and early diagnosis using oscillometry combined with respiratory modeling
title_full_unstemmed Respiratory abnormalities in sarcoidosis: physiopathology and early diagnosis using oscillometry combined with respiratory modeling
title_short Respiratory abnormalities in sarcoidosis: physiopathology and early diagnosis using oscillometry combined with respiratory modeling
title_sort respiratory abnormalities in sarcoidosis physiopathology and early diagnosis using oscillometry combined with respiratory modeling
topic Fractional order modeling
Forced oscillation technique
Respiratory mechanics
Biomedical instrumentation
Integer respiratory modeling
Diagnose of respiratory diseases
url https://doi.org/10.1186/s12890-025-03510-6
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