• Physiology & behavior · Feb 2017

    Apnea-hypopnea index prediction through an assessment of autonomic influence on heart rate in wakefulness.

    • Da Woon Jung, Yu Jin Lee, Do-Un Jeong, and Kwang Suk Park.
    • Interdisciplinary Program for Biomedical Engineering, Seoul National University Graduate School, Seoul, Republic of Korea.
    • Physiol. Behav. 2017 Feb 1; 169: 9-15.

    AbstractWith the high prevalence of obstructive sleep apnea, the issue of developing a practical tool for obstructive sleep apnea screening has been raised. Conventional obstructive sleep apnea screening tools are limited in their ability to help clinicians make rational decisions due to their inability to predict the apnea-hypopnea index. Our study aimed to develop a new prediction model that can provide a reliable apnea-hypopnea index value during wakefulness. We hypothesized that patients with more severe obstructive sleep apnea would exhibit more attenuated waking vagal tone, which may result in lower effectiveness in decreasing heart rate as a response to deep inspiration breath-holding. Prior to conducting nocturnal in-laboratory polysomnography, 30 non-obstructive sleep apnea (apnea-hypopnea index<5events/h) subjects and 246 patients with obstructive sleep apnea participated in a 75-second experiment that consisted of a 60-second baseline measurement and consecutive 15-second deep inspiration breath-hold sessions. Two apnea-hypopnea index predictors were devised by considering the vagal activities reflected in the electrocardiographic recordings acquired during the experiment. Using the predictors obtained from 184 individuals, regression analyses and k-fold cross-validation tests were performed to develop an apnea-hypopnea index prediction model. For the remaining 92 individuals, the developed model provided an absolute error (mean±SD) of 3.53±2.67events/h and a Pearson's correlation coefficient of 0.99 (P<0.01) between the apnea-hypopnea index predictive values and the reference values reported by polysomnography. Our study is the first to achieve reliable and time-efficient prediction of the apnea-hypopnea index during wakefulness.Copyright © 2016 Elsevier Inc. All rights reserved.

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