Background: The forced oscillation technique (FOT) allows analysis of the upper airway impedance and, hence, detection of obstructive sleep apnea. Objective: To evaluate FOT with respect to sensitivity and to specificity in online detection of sleep-disordered breathing patterns and to compare algorithmic onset detection time with manual onset time markers of staff physicians. Methods: We compared the absolute value ∣Z∣ of the impedance with three routinely obtained polysomnographic signals – nasal airflow v̇nasal, thoracic excursion Thox and esophageal pressure Pes – by retrospective analysis of the diagnostic polysomnograms of 51 patients. For each signal we evaluated algorithms for online detection of respiratory events. For each out of five apnea classes, 50 respiratory events marked by staff physicians were drawn randomly from the 51 polysomnograms to optimize the online detection algorithms (learning set). The algorithm analyzes relative changes of signal baseline and amplitude. Again 50 respiratory events were drawn randomly for each apnea class to examine to what extent it is possible to detect event onsets with the algorithms (test set). Results: The sensitivity of the signals varied between 56 and 94% and was on average 74%. The specificity was 96 ± 1.5% on average. The onset was detected 4–6 s after the initially evaluated onset of the staff physicians. Conclusion: We conclude that nasal airflow and FOT are equivalent sensitive measurands for detection of respiratory events.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.