BMC Pulmonary Medicine (Oct 2023)
Oscillometry of the respiratory system in Parkinson's disease: physiological changes and diagnostic use
Abstract
Abstract Background Lung function analysis in Parkinson's disease (PD) is often difficult due to the demand for adequate forced expiratory maneuvers. Respiratory oscillometry exams require onlyquiet tidal breathing and provide a detailed analysis of respiratory mechanics. We hypothesized that oscillometry would simplify the diagnosis of respiratory abnormalitiesin PD and improve our knowledge about the pathophysiological changes in these patients. Materials and methods This observational study includes 20 controls and 47 individuals with PD divided into three groups (Hoehn and Yahr Scale 1–1.5; H&Y scale 2–3 and PD smokers).The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). Results Initial stages are related to increased peripheral resistance (Rp; p = 0.001). In more advanced stages, a restrictive pattern is added, reflected by reductions in dynamic compliance (p < 0.05) and increase in resonance frequency (Fr; p < 0.001). Smoking PD patients presented increased Rp (p < 0.001) and Fr (p < 0.01). PD does not introduce changes in the central airways. Oscillometric changes were correlated with respiratory muscle weakness (R = 0.37, p = 0.02). Rp showed adequate accuracy in the detection of early respiratory abnormalities (AUC = 0.858), while in more advanced stages, Fr showed high diagnostic accuracy (AUC = 0.948). The best parameter to identify changes in smoking patients was Rp (AUC = 0.896). Conclusion The initial stages of PD are related to a reduction in ventilation homogeneity associated with changes in peripheral airways. More advanced stages also include a restrictive ventilatory pattern. These changes were correlated with respiratory muscle weakness and were observed in mild and moderate stages of PD in smokers and non-smokers. Oscillometry may adequately identify respiratory changes in the early stages of PD and obtain high diagnostic accuracy in more advanced stages of the disease.
Keywords