The Challenges and Pitfalls of Detecting Sleep Hypopnea Using a Wearable Optical Sensor: Comparative Study.

BACKGROUND: Obstructive sleep apnea (OSA) is the most prevalent respiratory sleep disorder occurring in 9% to 38% of the general population. About 90% of patients with suspected OSA remain undiagnosed due to the lack of sleep laboratories or specialists and the high cost of gold-standard in-lab polysomnography diagnosis, leading to a decreased quality of life and increased health care burden in cardio- and cerebrovascular diseases. Wearable sleep trackers like smartwatches and armbands are booming, creating a hope for cost-efficient at-home OSA diagnosis and assessment of treatment (eg, continuous positive airway pressure [CPAP] therapy) effectiveness. However, such wearables are currently still not available and cannot be used to detect sleep hypopnea. Sleep hypopnea is defined by ≥30% drop in breathing and an at least 3% drop in peripheral capillary oxygen saturation (Spo2) measured at the fingertip. Whether the conventional measures of oxygen desaturation (OD) at the fingertip and at the arm or wrist are identical is essentially unknown. OBJECTIVE: We aimed to compare event-by-event arm OD (arm_OD) with fingertip OD (finger_OD) in sleep hypopneas during both naïve sleep and CPAP therapy. METHODS: Thirty patients with OSA underwent an incremental, stepwise CPAP titration protocol during all-night in-lab video-polysomnography monitoring (ie, 1-h baseline sleep without CPAP followed by stepwise increments of 1 cmH2O pressure per hour starting from 5 to 8 cmH2O depending on the individual). Arm_OD of the left biceps muscle and finger_OD of the left index fingertip in sleep hypopneas were simultaneously measured by frequency-domain near-infrared spectroscopy and video-polysomnography photoplethysmography, respectively. Bland-Altman plots were used to illustrate the agreements between arm_OD and finger_OD during baseline sleep and under CPAP. We used t tests to determine whether these measurements significantly differed. RESULTS: In total, 534 obstructive apneas and 2185 hypopneas were recorded. Of the 2185 hypopneas, 668 (30.57%) were collected during baseline sleep and 1517 (69.43%), during CPAP sleep. The mean difference between finger_OD and arm_OD was 2.86% (95% CI 2.67%-3.06%, t667=28.28; P<.001; 95% limits of agreement [LoA] -2.27%, 8.00%) during baseline sleep and 1.83% (95% CI 1.72%-1.94%, t1516=31.99; P<.001; 95% LoA -2.54%, 6.19%) during CPAP. Using the standard criterion of 3% saturation drop, arm_OD only recognized 16.32% (109/668) and 14.90% (226/1517) of hypopneas at baseline and during CPAP, respectively. CONCLUSIONS: arm_OD is 2% to 3% lower than standard finger_OD in sleep hypopnea, probably because the measured arm_OD originates physiologically from arterioles, venules, and capillaries; thus, the venous blood adversely affects its value. Our findings demonstrate that the standard criterion of ≥3% OD drop at the arm or wrist is not suitable to define hypopnea because it could provide large false-negative results in diagnosing OSA and assessing CPAP treatment effectiveness.

Cumulative brain desaturation: Time to consider brain derived parameters to measure daytime sleepiness in obstructive sleep apnea.

OBJECTIVE: /Background: The change in cerebral hemodynamics induced by sleep apneas and hypopneas may contribute to the daytime sleepiness in patients with obstructive sleep apnea (OSA). However, previous studies failed to discovery their relationship. We propose and test a new parameter, the cumulative brain oxygen desaturation, which may contribute to OSA patient's daytime sleepiness. PATIENTS/METHODS: 22 patients with severe OSA (apnea-hypopnea index (AHI) at diagnosis [mean ± standard deviation, std.]: 52.1 ± 21.6/h, median: 45.1/h, interquartile range: 34.4-60.2/h) were monitored by polysomnography during routine continuous positive airway pressure titration. The reductions of brain tissue oxygen saturation (StO2) in all respiratory events at baseline sleep were measured by frequency-domain near-infrared spectroscopy (NIRS). The cumulative brain desaturation was calculated as AHI times the mean StO2 desaturation (i.e., AHI×ΔStO2‾). Similarly, cumulative peripheral desaturation was also calculated, i.e., AHI×ΔSpO2‾ where ΔSpO2‾ was the mean reduction of peripheral arterial oxygen saturation (SpO2). The correlations between Epworth sleepiness scale (ESS) and AHI, ΔStO2‾, AHI×ΔStO2‾, and AHI×ΔSpO2‾ were tested, respectively. Linear regression was applied to predict ESS using AHI×ΔStO2‾ and AHI×ΔSpO2‾, with age and BMI as covariates. RESULTS: ESS significantly correlates to the cumulative brain desaturation (Pearson's correlation coefficient: 0.68, p = 0.00056), not the other parameters. Regression analysis only finds significant association between ESS and the cumulative cerebral desaturation (p = 0.00195) but not the cumulative peripheral desaturation (p = 0.71). CONCLUSIONS: The cumulative brain oxygen desaturation, which comprehensively combines total sleep time, the frequency of apnea and hypopnea events, and the severity of cerebral oxygen desaturation, is a new indicator for daytime sleepiness in severe OSA.

Predictors of changes in cerebral perfusion and oxygenation during obstructive sleep apnea.

Obstructive sleep apnea syndrome (OSAS) is a common sleep disorder. Severe OSAS defined as apnea-hypopnea index (AHI) ≥ 30/h is a risk factor for developing cerebro-cardiovascular diseases. The mechanisms of how repetitive sleep apneas/hypopneas damage cerebral hemodynamics are still not well understood. In this study, changes in blood volume (BV) and oxygen saturation (StO2) in the left forehead of 29 newly diagnosed severe OSAS patients were measured by frequency-domain near-infrared spectroscopy during an incremental continuous positive airway pressure (CPAP) titration protocol together with polysomnography. The coefficients of variation of BV (CV-BV) and the decreases of StO2 (de-StO2) of more than 2000 respiratory events were predicted using linear mixed-effect models, respectively. We found that longer events and apneas rather than hypopneas induce larger changes in CV-BV and stronger cerebral desaturation. Respiratory events occurring during higher baseline StO2 before their onsets, during rapid-eye-movement sleep and those associated with higher heart rate induce smaller changes in CV-BV and de-StO2. The stepwise increased CPAP pressures can attenuate these changes. These results suggest that in severe OSAS the length and the type of respiratory event rather than widely used AHI may be better parameters to indicate the severity of cerebral hemodynamic changes.

Quantitative Changes in Muscular and Capillary Oxygen Desaturation Measured by Optical Sensors during Continuous Positive Airway Pressure Titration for Obstructive Sleep Apnea.

Obstructive sleep apnea (OSA) is a common sleep disorder, and continuous positive airway pressure (CPAP) is the most effective treatment. Poor adherence is one of the major challenges in CPAP therapy. The recent boom of wearable optical sensors measuring oxygen saturation makes at-home multiple-night CPAP titrations possible, which may essentially improve the adherence of CPAP therapy by optimizing its pressure in a real-life setting economically. We tested whether the oxygen desaturations (ODs) measured in the arm muscle (arm_OD) by gold-standard frequency-domain multi-distance near-infrared spectroscopy (FDMD-NIRS) change quantitatively with titrated CPAP pressures in OSA patients together with polysomnography. We found that the arm_OD (2.08 ± 1.23%, mean ± standard deviation) was significantly smaller (p-value < 0.0001) than the fingertip OD (finger_OD) (4.46 ± 2.37%) measured by a polysomnography pulse oximeter. Linear mixed-effects models suggested that CPAP pressure was a significant predictor for finger_OD but not for arm_OD. Since FDMD-NIRS measures a mixture of arterial and venous OD, whereas a fingertip pulse oximeter measures arterial OD, our results of no association between arm_OD and finger_OD indicate that the arm_OD mainly represented venous desaturation. Arm_OD measured by optical sensors used for wearables may not be a suitable indicator of the CPAP titration effectiveness.