0461 BEYOND THE INDEX: QUANTITATIVE PHENOTYPING OF APNEA

Abstract

Clinically, sleep apnea is characterized using metrics such as the Apnea-Hypopnea Index (AHI), a single rate averaged over the total sleep time. While clinically informative, it does not reflect either context or temporal distribution of the events. Thus, it is possible for patients with identical AHIs to present vastly different apnea phenotypes. Additionally, while descriptors relating factors such as sleep stage and position to apnea events can provide useful clinical information, current methods do not quantify the degree to which these factors contribute to the events. It is therefore crucial to develop phenotyping methods that can disambiguate differences in apnea event context, as well as in the relative contributions of different behavioral and physiological factors. We develop a point process approach for quantifying the contributions of different polysomnographic (PSG) observations to the instantaneous respiratory event probability. A point process is any system that can be represented as a series of stochastic momentary events, which is governed by time-varying instantaneous rate or probability. We use a generalized linear model (GLM) framework to estimate the degree to which sleep stage, body position, and previous event timing predicts the instantaneous probability of an event occurring. We applied our point process framework to technician-scored PSGs from a cohort of subjects with severe disease (AHI>30). Models including only position and sleep stage were poor predictors of sleep apnea (Kolmogorov-Smirnov test on time rescaled events). However, by adding the timing of past apnea events to the model, we observed a marked improvement to the model goodness-of-fit. Moreover, the degree to which past events influenced future apnea probability showed heterogeneity and clustering across subjects. These results indicate that past apnea history may be a major influencing factor on apnea probability. This suggests that a single apnea event, while mediated by other factors such as position and stage, may set off a cascade of subsequent respiratory events. Therefore, the structure of the history dependence may be a novel feature for apnea phenotyping and target for evaluating the effects of clinical intervention. NINDS R01 NS-096177 (M.J.P.).