A Novel Quantitative Arousal-Associated EEG-Metric to Predict Severity of Respiratory Distress in Obstructive Sleep Apnea Patients

Abstract

Respiratory arousals (RA) on polysomnography (PSG) are an important predictor of obstructive sleep apnea (OSA) disease severity. Additionally, recent reports suggest that more global indices of desaturation such as the hypoxic burden, namely the area under the curve (AUC) of the oxygen saturation (SaO2) PSG trace may better depict the desaturation burden in OSA. Here we investigated possible associations between a new metric, namely the AUC of the respiratory arousal electroencephalographic (EEG) recording, and already established parameters as the apnea/hypopnea index (AHI), arousal index and hypoxic burden in patients with OSA. In this data-driven study, polysomnographic data from 102 patients with OSAS were assessed (32 female; 70 male; mean value of age: 52 years; mean value of Body-Mass-Index-BMI: 31 kg/m2). The marked arousals from the pooled EEG signal (C3 and C4) were smoothed and the AUC was estimated. We used a support vector regressor (SVR) analysis to predict AHI, arousal index and hypoxic burden as captured by the PSG. The SVR with the arousal-AUC metric could quite reliably predict the AHI with a high correlation coefficient (0,58 in the training set, 0,65 in the testing set and 0,64 overall), as well as the hypoxic burden (0,62 in the training set, 0,58 in the testing set and 0,59 overall) and the arousal index (0,58 in the training set, 0,67 in the testing set and 0,66 overall). This novel arousal-AUC metric may predict AHI, hypoxic burden and arousal index with a quite high correlation coefficient and therefore could be used as an additional quantitative surrogate marker in the description of obstructive sleep apnea disease severity.

Multi‐centre arousal scoring agreement in the Sleep Revolution

“…As arousals are required to score hypopneas without a ≥3% blood oxygen desaturation and to calculate the ArI, both of which only regard the presence or number of arousals, some scorers may consider scoring the duration of the arousals irrelevant in the current clinical practice. However, it would be beneficial to acquire information on the arousal durations when estimating the magnitude of sleep fragmentation more accurately and in developing alternative metrics to describe arousals and sleep fragmentation, for example, arousal intensity (Amatoury et al, 2016; Azarbarzin et al, 2014), arousal burden (Shahrbabaki et al, 2021), and arousal‐AUC (area under the curve) (Malatantis‐Ewert et al, 2022). In addition, information on the arousal duration is crucial for linking arousals to other events, especially in a PLM series, where the arousal should be associated with a limb movement if they overlap or have <0.5 s in between, regardless of which one occurs first (Troester et al, 2023).…”

Heart Rate Variability as a Surrogate Marker of Severe Chronic Coronary Syndrome in Patients with Obstructive Sleep Apnea

“…A data-driven regression model was implemented, without the explicit stating of a functional form, indicating a nonparametric technique. The procedure was quite similar to the one used by Malatantis-Ewert et al [24]. The algorithm looks for an optimal separating threshold between the two data sets by maximizing the margin between the classes' closest points.…”