Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Sep 7, 2020
Date Accepted: May 24, 2021
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Can we trust the smartwatch and armband in screening obstructive sleep apnea?
ABSTRACT
Background:
Obstructive sleep apnea (OSA) is the most prevalent respiratory sleep disorder occurring in 9-38% of the general population. But about 90% of the suspected OSA patients go undiagnosed due to the lack of sleep laboratories/specialists and the high-cost of in-lab polysomnography (PSG) diagnosis, leading to decreased life qualities and increased healthcare burden in cardio-/cerebrovascular diseases. Wearable sleep trackers like smartwatches/armbands are booming, creating a hope of cost-efficient at-home OSA screening and assessment of treatment (e.g., continuous positive airway pressure [CPAP] therapy) effectiveness. However, such wearables currently are still not available. One of the major limitations in measuring OSA with wearables is the detection of sleep hypopnea. Because sleep apnea is defined by a complete pause/stop of breathing and many wearables can measure surrogate markers for breathing frequency, but hypopnea is defined by ≥ 30% drop in breathing and at least 3% drop in peripheral capillary oxygen saturation (SpO2) measured at fingertip. Whether the conventional measures of oxygen desaturation (OD) at the fingertip and at the arm/wrist are identical, is essentially unknown.
Objective:
We aimed to compare event-by-event the arm OD (arm_OD) with the fingertip OD (finger_OD) in sleep hypopneas during both naïve sleep and CPAP therapy.
Methods:
30 OSA patients did the incremental stepwise CPAP titration protocol during all-night in-lab video-PSG monitoring, i.e., 1-h baseline sleep without CPAP followed by stepwise increment of 1-cmH2O pressure per-hour starting from 5-8 cmH2O depending on the individuals. The arm_OD of left bicep muscular and the finger_OD of left index fingertip in sleep hypopneas were simultaneously measured by frequency-domain near-infrared spectroscopy and video-PSG photoplethysmography, respectively. Bland-Altman plots were used to illustrate the agreements between arm_OD and finger_OD during baseline sleep and under CPAP, respectively. T-test tested whether the differences between arm_OD and finger_OD were significantly different from 0 (P<.05).
Results:
Totally 2185 hypopneas from our patients were analyzed, including 668 ones during baseline sleep and 1517 ones during CPAP. The mean difference between finger_OD and arm_OD was 2.86% (95% confidence interval [CI]: 2.67-3.06%, t-test: P<.001) during baseline sleep and 1.83% (95% CI: 1.72-1.94%, t-test: P<.001) during CPAP, with the 95% limits of agreement as [-2.27%, 8.00%] and [-2.54%, 6.19%], respectively. Using the criterion of arm_OD ≥3% can only define 16.32% (109/668) and 14.90% (226/1517) hypopneas at baseline and during CPAP, respectively.
Conclusions:
arm_OD is 2-3% smaller than standard finger_OD in sleep hypopnea, probably because the measured arm_OD physiologically comes from arterioles, venules and capillaries thus the venous blood adversely affects its value. Our findings cannot recommend directly using a drop of ≥ 3% OD at arm/wrist as a criterion to define hypopnea because it could provide large false negative results in screening OSA and assessing the CPAP treatment effectiveness.
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