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: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-02-01
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| Series: | BMC Pulmonary Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12890-025-03510-6 |
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| Summary: | 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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| ISSN: | 1471-2466 |