C22-20 A Novel Quiet-Breathing Flow Analyzer Enables Simple Classification of Ventilatory Impairment

Rationale Conventional spirometry requires forced breathing effort and is difficult to perform for older adults and for patients with neuromuscular disorders. Therefore, we developed a high-sensitivity flow-sensor analysis device, the Resting Respiratory Flow Analyzer (RRFA), that estimates ventilatory function from quiet-breathing flow waveforms by integrating flow to volume. The purpose of this study was to examine whether ventilatory impairment can be classified from resting-breathing flow patterns without forced effort. Methods RRFA consists of a high-sensitivity flow sensor and a flow-volume analysis module that converts flow to volume by integration. Quiet breathing for at least one minute was recorded in sitting and supine positions. Each breath was divided into eight phases (8-phase analysis). The analyzed indices were TE/TI, F_Mid_E, FE_T4/8, and Vd_E_4/8. Spirometric reference indices were VC, FEV1, FEV1/FVC, and VTE. Relationships between RRFA parameters and spirometric indices were examined using correlation analysis. Agreement of ventilatory-impairment classification, postural effects, and measurement repeatability were evaluated using Bland-Altman analysis and coefficients of variation (CV). Results Significant correlations were observed between RRFA indices and spirometric indices (r > 0.5, p < 0.01) in both sitting and supine positions. Absolute values differed due to differences in measurement principles, but agreement in classification accuracy and trend judgment was good. Postural changes were appropriately reflected, and classification results were consistent between positions. The coefficient of variation for each index was less than 0.5, indicating good repeatability. Eight-phase analysis also improved the stability of mid-expiratory indices compared with whole-breath analysis. In the respiratory waveform analysis obtained by RRFA, a decrease in flow rate was observed during the change to the supine position, reflecting elevation of the diaphragm and restriction of thoracic expansion. In particular, significant decreases in F_Mid_E and F_Mid_I suggested changes in peripheral airway resistance and inspiratory muscle activity, indicating that RRFA is a useful index for noninvasive detection of posture-dependent respiratory mechanical changes. Conclusions Integration-based analysis of quiet-breathing flow using a high-sensitivity sensor enabled evaluation of ventilatory function and classification of ventilatory impairment with high consistency to spirometry. RRFA thus enabled ventilatory impairment classification based on resting breathing, suggesting its potential applicability for bedside and home monitoring in patients unable to perform forced effort breathing. This approach provides a non-invasive and reproducible method for evaluating respiratory function without requiring forced effort breathing, and its clinical utility for bedside or home assessment of respiratory function can be expected.