0698 A Comparison Of Two Visual Hypopnea Classification Methods

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Abstract Introduction The rules for classifying apneas as either obstructive or central using usual polysomnography (PSG) channels are well established, but classification of hypopneas is less straightforward without special sensors. Visual scoring methods have been proposed by the American Academy of Sleep Medicine (AASM) and by Randerath, et al. These two scoring methods have never been compared. We evaluated these two scoring methods for clinical use. Methods We selected 50 hypopnea segments from patient’s PSGs with very clear obstructive physiology (average total AHI 48.6, central AI 0), assumed to be obstructive hypopneas, and from patient’s PSGs with very clear central physiologies (average total AHI 34.3, obstructive AI 0.3), assumed to be central hypopneas. These 100 hypopnea-containing PSG segments (HCPS) were deidentified, placed in randomized order, and sent to two groups of 6 PSG scorers (2 RPSGTs, 2 sleep medicine fellows, 2 sleep medicine specialists). One group scored using the AASM criteria and the other used the Randerath algorithm. After a washout period, re-randomized HCPS were sent to be scored using the alternative method. We used Fleiss’ kappa to determine inter-rater reliability—i.e., how consistently multiple scorers came to the same conclusion about a given hypopnea segment using each method, and accuracy—how often the scorers rated the HCPS in a manner consistent with the assumed physiology. We also recorded the time it took to score. Results Overall accuracy of both methods was 68%. Among 12 scorers, Fleiss’ Kappa coefficient was 0.32 and 0.27 for the AASM and Randerath scoring methods, respectively. Average scoring time (24.3 minutes for AASM and 26.2 minutes for Randerath) was similar (p=0.79). Conclusion Inter-rater agreement was only fair using these methods, and accuracy was only 68%. More work is needed to discover a convenient, non-invasive way to reproducibly and accurately characterize hypopneas. Support This project does not have any funding support.