Respiratory Inductance Plethysmography to Quantify Changes in Ventilation in Obstructive Sleep Apnea.
prospective_cohort · Level II
Where this comes from
- Record sourced from PubMed, PMID 41056175.
- Also identified by DOI 10.1109/TBME.2025.3618403 and PMC identifier 12989205.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
The study aims to determine whether respiratory inductance plethysmography (RIP) signals can be used to quantify changes in ventilation and provide advanced obstructive sleep apnea (OSA) severity metrics. This approach seeks to address limitations in current airflow-based OSA measures, particularly those relying on nasal pressure, which may be compromised by oral breathing. Adult patients with OSA (N = 89, 68Male:21Female) completed in-laboratory polysomnography (PSG) allowing for RIP-based ventilation estimates to be compared against a gold standard oronasal-pneumotach (normalized ventilation %<sub>eupnea</sub>). Concordance was assessed on three levels: 1) individual breath ventilation, 2) individual respiratory event depth (percentage reduction in ventilation from local average), and 3) patient-specific OSA severity in terms of average event depth and ventilatory burden (average event depth x average event duration x event rate). To address overestimation of RIP ventilation during obstruction, we developed and applied a calibration and linearization method ("RIP correction"). Concordance analysis evaluated median bias for both small (<70%<sub>eupnea</sub>) and large breaths (>130%<sub>eupnea</sub>), along with bias and intraclass correlation coefficient (ICC) calculation for events and patient-specific measures. For individual breaths (N = 495,631), RIP correction reduced overestimation bias for small breaths from 12 to 2%<sub>eupnea</sub>. For individual events (N = 34,497), RIP correction reduced mean bias for event depth estimates from 9 to 1%<sub>eupnea</sub>. For patient-specific analysis underestimation of average event depth was attenuated from 9 to 4%<sub>eupnea</sub> and for ventilatory burden, from 275 to 117%<sub>eupnea</sub> min/hr. Additionally, RIP correction improved ICC for event depth and patient-level traits. RIP signals, with appropriate processing, enable quantification of advanced ventilation-based OSA metrics, addressing concerns that airflow-based measures may be affected by breathing route.
Medical subject headings
- Sleep Apnea, Obstructive
- Plethysmography
- Signal Processing, Computer-Assisted