Diagnosis of obstructive sleep apnea using pulse oximeter derived photoplethysmographic signals

Sleep Apnea is Not an Obstacle for Outpatient Hip and Knee Arthroplasty

BACKGROUND

Up to 25% of patients requiring hip or knee arthroplasty have sleep apnea (SA), and these patients have historically been excluded from outpatient programs. The objectives of this study were to evaluate same-day discharge failure as well as 30-day complications, readmissions, and unexpected visits.

METHODS

A retrospective case-control study comparing patients who have and do not have SA matched for age, sex and arthroplasty type (total hip arthroplasty, total knee arthroplasty, unicompartimental knee arthroplasty) who underwent primary outpatient surgery between February 2019 and December 2022 in 2 academic hospitals was conducted. Cases with mild SA, moderate SA with a body mass index (BMI) <35, and SA of all severity treated by continuous positive airway pressure machines were eligible. There were 156 patients included (78 cases). Complications were assessed according to the Clavien-Dindo Classification and the Comprehensive Complication Index. Continuous variables were evaluated by Student's T or Mann-Whitney tests, while categorical data were analyzed by Chi-square or Fisher tests. Univariate analyses were performed to determine discharge failure risk factors.

RESULTS

There were 6 cases (7.7%) and 5 controls (6.4%) who failed to be discharged on surgery day (P = .754), with postoperative hypoxemia (6, [3.8%]) and apnea periods (3, [1.9%]) being the most common causes. Higher BMI (odds ratio = 1.19, P = .013) and general anesthesia (odds ratio = 11.97, P = .004) were found to be risk factors for discharge failure. No difference was observed on 30-day readmissions (P = .497), unexpected visits (P = 1.000), and complications on the Clavien-Dindo Classification (P > .269) and Comprehensive Complication Index (P > .334) scales.

CONCLUSIONS

Selected patients who have SA can safely undergo outpatient hip or knee arthroplasty. Higher BMI and general anesthesia increased the odds of same-day discharge failure.

LEVEL OF EVIDENCE

Level III, Case-control Study.

Higher ambient temperatures may worsen obstructive sleep apnea: A nationwide smartwatch-based analysis of 6.2 million person-days

Obstructive sleep apnea (OSA) is a serious type of sleep disorder that can lead to cardiometabolic and neurocognitive diseases. We utilized smart device-based photoplethysmography technology to collect sleep data from the Chinese population from 2019 to 2022. Distributed lag nonlinear models combined with a generalized nonlinear model or a linear mixed effects model were used to investigate the short-term associations between daily temperature and indicators of OSA severity. We included a total of 6,232,056 d of sleep monitoring data from 51,842 participants with moderate to severe risk of OSA from 313 Chinese cities. The relationships between ambient temperature and OSA exacerbation, apnea-hypopnea index (AHI), and minimum oxygen saturation (MinSpO2) were almost linear and present only on the same day. Higher temperatures were associated with a greater risk of OSA exacerbation, with an 8.4% (95% confidence interval (CI): 7.6%-9.3%) increase per 10 °C increase in temperature. A 10 °C increase in daily temperature corresponded to an AHI increase of 0.70 events/h (95% CI: 0.65-0.76) and a MinSpO2 decrease of 0.18% (95% CI: 0.16%-0.19%). Exposure to elevated temperatures during the night can also lead to adverse effects. The effects of higher temperatures on OSA severity were stronger among men, participants with a body mass index ≥ 24 kg/m2, those aged 45 years and older, individuals with a history of hypertension and diabetes, and during the cold season. This large-scale, nationwide, longitudinal study provides robust evidence suggesting that higher ambient temperatures may immediately worsen OSA.

Telemedicine for obstructive sleep apnea syndrome: An updated review

Telemedicine (TM) is a new medical service model in which computer, communication, and medical technologies and equipment are used to provide "face-to-face" communication between medical personnel and patients through the integrated transmission of data, voice, images, and video. This model has been increasingly applied to the management of patients with sleep disorders, including those with obstructive sleep apnea syndrome (OSAS). TM technology plays an important role in condition monitoring, treatment compliance, and management of OSAS cases. Herein, we review the concept of TM, its application to OSAS, and the related effects and present relevant application suggestions and strategies, which may provide concepts and references for OSAS-related TM development and application.

Comparative study of the SleepImage ring device and polysomnography for diagnosing obstructive sleep apnea

Purpose We aim to evaluate the diagnostic performance of the SleepImage Ring device in identifying obstructive sleep apnea (OSA) across different severity in comparison to standard polysomnography (PSG). Methods Thirty-nine patients (mean age, 56.8 ± 15.0 years; 29 [74.3%] males) were measured with the SleepImage Ring and PSG study simultaneously in order to evaluate the diagnostic performance of the SleepImage device for diagnosing OSA. Variables such as sensitivity, specificity, positive and negative likelihood ratio, positive and negative predictive value, and accuracy were calculated with PSG-AHI thresholds of 5, 15, and 30 events/h. Receiver operating characteristic curves were also built according to the above PSG-AHI thresholds. In addition, we analyzed the correlation and agreement between the apnea-hypopnea index (AHI) obtained from the two measurement devices. Results There was a strong correlation (r = 0.89, P < 0.001 and high agreement in AHI between the SleepImage Ring and standard PSG. Also, the SleepImage Ring showed reliable diagnostic capability, with areas under the receiver operating characteristic curve of 1.00 (95% CI, 0.91, 1.00), 0.90 (95% CI, 0.77, 0.97), and 0.98 (95% CI, 0.88, 1.000) for corresponding PSG-AHI of 5, 15 and 30 events/h, respectively. Conclusion The SleepImage Ring could be a clinically reliable and cheaper alternative to the gold standard PSG when aiming to diagnose OSA in adults.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13534-023-00304-9.

Factors affecting polysomnography compliance and delays to surgical treatment of obstructive sleep apnea

OBJECTIVE

To evaluate adherence to polysomnography in pediatric patients and determine if demographics, socioeconomic status, polysomnography indication, or prior otolaryngology intervention are associated with polysomnography adherence and time to definitive surgery.

STUDY DESIGN

Retrospective review study.

SETTING

Tertiary-care children's hospital.

METHODS

Electronic medical record was queried to identify patients ordered for a sleep study between January and May 2019. Demographic information, time to sleep study, and time to surgery were collected and calculated.

RESULTS

304 patients were recommended to obtain polysomnography, with adherence rate of 65.4%. There was no significant difference in adherence or loss to follow-up rates based on patient sex, age, language, socioeconomic status, state of residence, single-parent status, or polysomnography indication. There was no difference between time to surgery for patients who did or did not obtain polysomnography (181 vs. 161 days, P = .51). Patients with prior otolaryngology intervention were more likely to obtain polysomnography and less likely to be lost to follow-up (P < .05). Median household income demonstrated a significant inverse relationship with time to polysomnography (P < .05) as well as time to surgery (P < .05). Medically complex patients tended to experience longer time to surgery compared with non-complex patients.

CONCLUSION

Families with lower socioeconomic status or medically complex children may require assistance to obtain polysomnography and pursue surgery for sleep-disordered breathing. Patients without prior otolaryngology intervention may be less likely to follow up and may need assistance with navigating the polysomnography process.

Comparative study of a wearable intelligent sleep monitor and polysomnography monitor for the diagnosis of obstructive sleep apnea

PURPOSE

Due to the lack of an objective population-based screening tool for obstructive sleep apnea (OSA), a large number of patients with potential OSA have not been identified in the general population. Our study compared an objective wearable sleep monitoring device with polysomnography (PSG) to provide a reference for OSA screening in a large population.

METHODS

Using a self-control method, patients admitted to our sleep center from July 2020 to March 2021 were selected for overnight PSG and wearable intelligent sleep monitor (WISM) at the same time. The sensitivity and specificity of the device for the diagnosis of OSA were evaluated.

RESULTS

A total of 196 participants (mean age: 45.1 ± 12.3 years [18-80 years]; 168 men [86%]) completed both PSG and WISM monitoring. Using an apnea-hypopnea index (AHI) ≥ 5 events/h as the diagnostic criterion, the sensitivity, specificity, kappa value, and area under the receiver operating characteristic curve of the WISM for OSA diagnosis were 93%, 77%, 0.6, and 0.95, respectively. Using an AHI ≥ 15 events/h as the diagnostic criterion for moderate-to-severe OSA, these values were 92%, 89%, 0.8, and 0.95, respectively. The mean difference in the AHI between PSG and the artificial intelligence oxygen desaturation index from the WISM was 6.8 events/h (95% confidence interval: - 13.1 to 26.7).

CONCLUSION

Compared with the PSG, WISM exhibits good sensitivity and specificity for the diagnosis of OSA. This small, simple, and easy-to-use device is more suitable for OSA screening in a large population because of its single-step application procedure.

Cluster analysis of clinical phenotypic heterogeneity in obstructive sleep apnea assessed using photoplethysmography

BACKGROUND

We evaluated heterogeneity in clinical phenotypes among patients with obstructive sleep apnea syndrome (OSAHS) using photoplethysmography (PPG) in cluster analysis.

METHODS

All enrolled patients underwent polysomnography (PSG) monitoring while wearing a PPG device. Pulse wave signals were recorded with a modified pulse oximetry probe in the PPG device. The pulse wave-derived cardiac risk composite parameter (CRI) and eight derived signal parameters were used to assess OSAHS phenotype. We defined a high cardiovascular risk OSAHS group (CRI ≥0.5) and low cardiovascular risk OSAHS group (CRI <0.5). K-means clustering was performed for analysis of clinical phenotype heterogeneity in OSAHS by combining the CRI and its derived signals.

RESULTS

The OSAHS group had high cardiovascular risk for sex, age, body mass index, systolic and diastolic blood pressure, apnea hypopnea index, and obstructive arousal index and higher risk of developing hypertension, diabetes, and cerebrovascular comorbidities. The low cardiovascular risk OSAHS group had higher blood oxygen levels. Three clinical phenotypes were identified in CRI clustering: 1) typical OSAHS with high risk of hypertension (characterized by middle age, obesity, hypertension with severe OSAHS); 2) older women and mild OSAHS; 3) older men and mild OSAHS. Three subtypes were obtained based on the eight cardiac risk-derived parameters: 1) hypoxia combined with decreased pulse wave amplitude variation; 2) decreased vascular pulse wave amplitude combined with decreased pulse frequency; 3) arrhythmia combined with hypoxia.

CONCLUSIONS

Establishing OSAHS clinical phenotypes with the CRI and derived parameters using PPG may help in establishing multi-dimensional assessment of cardiovascular risk in OSAHS.

Portable evaluation of obstructive sleep apnea in adults: A systematic review

Obstructive sleep apnea (OSA) is a significant healthcare burden affecting approximately one billion people worldwide. The prevalence of OSA is rising with the ongoing obesity epidemic, a key risk factor for its development. While in-laboratory polysomnography (PSG) is the gold standard for diagnosing OSA, it has significant drawbacks that prevent widespread use. Portable devices with different levels of monitoring are available to allow remote assessment for OSA. To better inform clinical practice and research, this comprehensive systematic review evaluated diagnostic performances, study cost and patients' experience of different levels of portable sleep studies (type 2, 3, and 4), as well as wearable devices and non-contact systems, in adults. Despite varying study designs and devices used, portable diagnostic tests are found to be sufficient for initial screening of patients at risk of OSA. Future studies are needed to evaluate cost effectiveness with the incorporation of portable diagnostic tests into the diagnostic pathway for OSA, as well as their application in patients with chronic respiratory diseases and other comorbidities that may affect test performance.

Reliability of STOP-Bang questionnaire and pulse oximetry as predictors of OSA - a retrospective study

OBJECTIVE

To verify the reliability of a STOP-Bang questionnaire and objective blood oxygen concentration (SpO2) estimation by pulse oximetry as an indicator of patients' vulnerability to OSA, by correlating data of these two tests with that of the "gold standard" all-night polysomnography.

METHODS

STOP-Bang score and pulse oximetry value (SpO2) for each patient were tabulated against the total sleep AHI score (obtained from subsequent all-night polysomnography) and analyzed to evaluate the diagnostic accuracy of the STOP-Bang questionnaire and pulse oximetry.

RESULTS

With sensitivity and specificity scores of 91.2% and 88.6%, respectively, positive predictive value 90.5%, negative predictive value 40.2%, the twin diagnostic test (STOP-Bang and pulse oximetry) was found to be highly congruent with the polysomnography (PSG), achieving a diagnostic accuracy of 85%.

CONCLUSION

Dental chairside screening by STOP-Bang questionnaire and pulse oximetry would be a good option, especially where logistic and economic constraints impede all-night polysomnography.

Performance evaluation of a wrist-worn reflectance pulse oximeter during sleep

OBJECTIVES

To characterize and evaluate the estimation of oxygen saturation measured by a wrist-worn reflectance pulse oximeter during sleep.

METHODS

Ninety-seven adults with sleep disturbances were enrolled. Oxygen saturation was simultaneously measured using a reflectance pulse oximeter (Galaxy Watch 4 [GW4], Samsung, South Korea) and a transmittance pulse oximeter (polysomnography) as a reference. The performance of the device was evaluated using the root mean squared error (RMSE) and coverage rate. Additionally, GW4-derived oxygen desaturation index (ODI) was compared with the apnea-hypopnea index (AHI) derived from polysomnography.

RESULTS

The GW4 had an overall RMSE of 2.3% and negligible bias of -0.2%. A Bland-Altman density plot showed good agreement between the GW4 and the reference pulse oximeter. RMSEs were 1.65 ± 0.57%, 1.76 ± 0.65%, 1.93 ± 0.54%, and 2.93 ± 1.71% for normal (n = 18), mild (n = 21), moderate (n = 23), and severe obstructive sleep apnea (n = 35), respectively. The data rejection rate was 26.5%, which was caused by fluctuations in contact pressure and the discarding of data less than 70% of saturation. A GW4-ODI ≥5/h had the highest ability to predict AHI ≥15/h with sensitivity, specificity, accuracy, and area under the curve of 89.7%, 64.1%, 79.4%, and 0.908, respectively.

CONCLUSIONS

This study evaluated the estimation of oxygen saturation by the GW4 during sleep. This device complies with both Food and Drug Administration and International Organization for Standardization standards. Further improvements in the algorithms of wearable devices are required to obtain more accurate and reliable information about oxygen saturation measurements.

Heart Rate Variability from Wearable Photoplethysmography Systems: Implications in Sleep Studies at High Altitude

The interest in photoplethysmography (PPG) for sleep monitoring is increasing because PPG may allow assessing heart rate variability (HRV), which is particularly important in breathing disorders. Thus, we aimed to evaluate how PPG wearable systems measure HRV during sleep at high altitudes, where hypobaric hypoxia induces respiratory disturbances. We considered PPG and electrocardiographic recordings in 21 volunteers sleeping at 4554 m a.s.l. (as a model of sleep breathing disorder), and five alpine guides sleeping at sea level, 6000 m and 6800 m a.s.l. Power spectra, multiscale entropy, and self-similarity were calculated for PPG tachograms and electrocardiography R–R intervals (RRI). Results demonstrated that wearable PPG devices provide HRV measures even at extremely high altitudes. However, the comparison between PPG tachograms and RRI showed discrepancies in the faster spectral components and at the shorter scales of self-similarity and entropy. Furthermore, the changes in sleep HRV from sea level to extremely high altitudes quantified by RRI and PPG tachograms in the five alpine guides tended to be different at the faster frequencies and shorter scales. Discrepancies may be explained by modulations of pulse wave velocity and should be considered to interpret correctly autonomic alterations during sleep from HRV analysis.

Wearable Photoplethysmography for Cardiovascular Monitoring

Smart wearables provide an opportunity to monitor health in daily life and are emerging as potential tools for detecting cardiovascular disease (CVD). Wearables such as fitness bands and smartwatches routinely monitor the photoplethysmogram signal, an optical measure of the arterial pulse wave that is strongly influenced by the heart and blood vessels. In this survey, we summarize the fundamentals of wearable photoplethysmography and its analysis, identify its potential clinical applications, and outline pressing directions for future research in order to realize its full potential for tackling CVD.

Comparison of Ring Pulse Oximetry Using Reflective Photoplethysmography and PSG in the Detection of OSA in Chinese Adults: A Pilot Study

OBJECTIVE

A novel ring-worn oximeter (Circul) uses reflective photoplethysmography and automated signal processing to calculate oxygen desaturations. We evaluated the ability of Circul to detect obstructive sleep apnea in Chinese adults.

METHODS

We recruited 207 Chinese Han subjects: 70% males, mean age 48.2±14.7 years, mean BMI 27.6±4.8 kg/m2 and mean AHI 28.6±25.2 events/h. All participants underwent simultaneous polysomnography (PSG) and Circul testing in a sleep laboratory. Oxygen desaturation index (ODI), mean oxygen saturation (MSpO₂), cumulative time at SpO2<90% (CT90), cumulative percentage of sleep time spent with SpO2<90% (CT90/TST) were derived and compared for the Circul and the PSG.

RESULTS

The ODI was 25.3±24.5 events/h using PSG and 22.2±24.5 events/h using Circul (P<0.0001), with an intraclass correlation coefficient (ICC) of 0.884. CT90 and CT90/TST between the two methods were not different; the MSpO₂ level calculated by PSG was slightly lower than Circul, 95.0% (93.0-96.0%) vs 95.3% (93.9-96.6%), P<0.0001. Circul-ODI had a good correlation (r=0.91, p<0.0001) and close agreement with PSG-AHI (Bland-Altman analysis: Mean Difference 6.4, 95% CI -14.8 to 27.5 events/h). Using a threshold of AHI ≥5 events/h, the Circul had 87% sensitivity, 83% specificity, 5.09 positive likelihood ratio (LR+), 86% accuracy, and 0.929 area under the curve (AUC).

CONCLUSION

Circul ring pulse oximetry can detect OSA with reasonable reliability. The Circul system is a reliable and comfortable choice for OSA assessment.

Associations between nocturnal continuous blood pressure fluctuations and the characteristics of oxygen desaturation in patients with obstructive sleep apnea: a pilot study

BACKGROUND

Patients with obstructive sleep apnea (OSA) frequently experience apnea-related oxygen desaturation events (ODE) accompanied by striking blood pressure (BP) fluctuations during sleep. We aimed to investigate the effects of characteristics of ODE on nocturnal BP fluctuations in OSA patients.

METHODS AND RESULTS

A total of 6199 ODE were obtained from 30 patients with who underwent overnight portable monitoring and beat-to-beat BP monitoring simultaneously. The associations between nocturnal BP parameters and the characteristics of ODE were studied. The mean value of systolic BP (SBP) monitored during ODE was higher than the non-hypoxia SBP value (122.0 ± 15.9 vs. 120.4 ± 15.1 mmHg, P = 0.001) and nighttime SBP value (122.0 ± 15.9 vs. 120.8 ± 15.0 mmHg, P = 0.002). SBP variability (SBPV) during ODE was higher than the values not during ODE (14.0 ± 2.8 vs. 13.2 ± 2.6 mmHg, P = 0.043) and nighttime SBPV (14.0 ± 2.8 vs. 12.9 ± 2.3 mmHg, P < 0.001). Hypoxia SBP index, defined as the percentage of SBP surge (△SBP) ≥10 mmHg to all △SBP during ODE, increased with greater respiratory event index (P = 0.01). Both the coefficient of variation for SBP values of an ODE (SBPV') and event-related SBP elevation (△SBP') increased with raised amplitude of ODE (P < 0.001 for SBPV' and P < 0.001 for △SBP'). Similar results were observed when the duration of events was analyzed (P < 0.001 for SBPV' and P < 0.001 for △SBP').

CONCLUSION

BP related to ODE may be the main component of increased BP during sleep in OSA patients. In addition to the frequency of respiratory events, the amplitude and duration of ODE may have a role in nocturnal BP fluctuations in OSA patients.

Belun Ring Platform: a novel home sleep apnea testing system for assessment of obstructive sleep apnea

STUDY OBJECTIVES

The objective of the study is to validate the performance of Belun Ring Platform, a novel home sleep apnea testing system using a patented pulse oximeter sensor and a proprietary cloud-based neural networks algorithm.

METHODS

The Belun Ring captures oxygen saturation, photoplethysmography, and accelerometer signals. The Belun Ring total sleep time is derived from features extracted from accelerometer, oxygen saturation, and photoplethysmography signals. The Belun Ring respiratory event index is derived from Belun Ring total sleep time and features extracted from heart rate variability and oxygen saturation changes. A total of 50 adults without significant cardiopulmonary or neuromuscular comorbidities and heart rate affecting medications were evaluated. In-lab sleep studies were performed simultaneously with the Ring and the studies were manually scored using the American Academy of Sleep Medicine Scoring Manual 4% desaturation criteria.

RESULTS

The Belun Ring respiratory event index correlated well with the polysomnography-apnea-hypopnea index (AHI; r = .894, P < .001). The sensitivity and specificity in categorizing AHI ≥ 15 events/h were 0.85 and 0.87, respectively, and the positive predictive value and negative predictive value were 0.88 and 0.83, respectively. The Belun Ring total sleep time also correlated well with the polysomnography-total sleep time (r = .945, P < .001). Although the Belun Ring Platform has a good overall performance, it tends to overestimate AHI in individuals with AHI under 15 events/h and underestimate AHI in those with AHI over 15 events/h. Conclusions: In this proof-of-concept study, the Belun Ring Platform demonstrated a reasonable accuracy in predicting AHI and total sleep time in patients without significant comorbidities and heart rate-affecting medications.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Name: Validation of a Novel Device for Screening Patients With Symptoms of Obstructive Sleep Apnea; URL: https://clinicaltrials.gov/ct2/show/NCT04121923; Identifier: NCT04121923.

Efficient embedded sleep wake classification for open-source actigraphy

This study presents a thorough analysis of sleep/wake detection algorithms for efficient on-device sleep tracking using wearable accelerometric devices. It develops a novel end-to-end algorithm using convolutional neural network applied to raw accelerometric signals recorded by an open-source wrist-worn actigraph. The aim of the study is to develop an automatic classifier that: (1) is highly generalizable to heterogenous subjects, (2) would not require manual features' extraction, (3) is computationally lightweight, embeddable on a sleep tracking device, and (4) is suitable for a wide assortment of actigraphs. Hereby, authors analyze sleep parameters, such as total sleep time, waking after sleep onset and sleep efficiency, by comparing the outcomes of the proposed algorithm to the gold standard polysomnographic concurrent recordings. The relatively substantial agreement (Cohen's kappa coefficient, median, equal to 0.78 ± 0.07) and the low-computational cost (2727 floating-point operations) make this solution suitable for an on-board sleep-detection approach.

A Single-Center Validation of the Accuracy of a Photoplethysmography-Based Smartwatch for Screening Obstructive Sleep Apnea

BACKGROUND

Obstructive sleep apnea (OSA), the most common upper-airway disease, is closely associated with the risk of cardiovascular diseases. However, the early screening of OSA is a main challenge, relying on polysomnography (PSG) or home sleep apnea test (HSAT) in hospitals. Photoplethysmography (PPG) has been developed as a novel technology for screening of OSA, while the validation of PPG-based smart devices is limited compared to that for PSG or HSAT devices.

OBJECTIVE

This study aimed to investigate the feasibility and validity of a PPG-based smartwatch in the screening of OSA.

METHODS

A total of 119 patients were recruited from the Chinese People's Liberty Army General Hospital (Beijing, China). Among them, 20 patients were assessed for a whole-night sleep study by a smartwatch and PSG simultaneously, as well as 82 cases by a smartwatch and HSAT simultaneously. Using PSG or HSAT as the "gold standard", we compared the accuracy, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and positive likelihood ratio (+LR) or negative likelihood ratio (-LR) at three apnea hypopnea index (AHI) levels: AHI≥5, AHI≥15, and AHI≥30.

RESULTS

A total of 17/119 patients were excluded from the study due to the poor quality of PPG signals. Among the remaining cases, 83 patients were diagnosed with OSA. Compared to HSAT device, the accuracy, sensitivity, and specificity of the PPG-based smartwatch in predicting moderate-to-severe OSA patients (AHI≥15) were 87.9%, 89.7%, and 86.0%, respectively. Compared to PSG device, the accuracy, sensitivity, and specificity of the PPG-based smartwatch in predicting OSA in patients (AHI≥5) were 81.1%, 76.5%, and 100%, respectively.

CONCLUSION

The PPG-based smartwatch outperformed in terms of detecting OSA; nevertheless, validation in a large-scale population is imperative.

TRIAL REGISTRATION

Chinese Clinical Trial Registry of the International Clinical Trials Registry Platform of the World Health Organization ChiCTR-OOC-17014138; http://www.chictr.org.cn/showprojen.aspx?proj=24191.

Airflow from nasal pulse oximetry in the screening of obstructive sleep apnea

Obstructive Sleep Apnea (OSA) is recognized as an increasing health risk, leading to daytime sleepiness and various medical conditions, such as hypertension and heart failure. Polysomnography (PSG), the gold standard to diagnose OSA, is a resource-intensive and expensive investigation confined to the hospital.Portable home monitoring, i.e. pulse oximetry, may become an acceptable OSA screening method. The novel nasal pulse oximeter sensor (Xhale Alar) adds the possibility of combining pulse oximetry (SpO2) with airflow analysis by an integrated thermistor, which might increase the diagnostic accuracy.In the Alar pilot study, 39 adults were measured during an overnight PSG recording together with the Alar sensor. This study aims to investigate the additional value of an airflow signal compared to SpO2 analysis in OSA screening. Both time and spectral features were extracted from SpO2 and airflow signals recorded with the Alar sensor. Leave one out cross-validation was used to develop Random Forest models in screening for apnea-hypopnea index (AHI) thresholds 5 and 10. Using both AHI ≥ 5 and AHI ≥ 10 as the diagnostic cutoff, the airflow signal shows respectively an AUC of 89% and 80% compared to 78% and 77% with SpO2 analysis, showing a higher performance using an airflow signal in screening adults for OSA.

Validation of an Overnight Wireless High-Resolution Oximeter plus Cloud-Based Algorithm for the Diagnosis of Obstructive Sleep Apnea

OBJECTIVES

Obstructive sleep apnea (OSA) is a common but largely underdiagnosed condition. This study aimed to test the hypothesis that the oxygen desaturation index (ODI) obtained using a wireless high-resolution oximeter with a built-in accelerometer linked to a smartphone with automated cloud analysis, Overnight Digital Monitoring (ODM), is a reliable method for the diagnosis of OSA.

METHODS

Consecutive patients referred to the sleep laboratory with suspected OSA underwent in-laboratory polysomnography (PSG) and simultaneous ODM. The PSG apnea-hypopnea index (AHI) was analyzed using the criteria recommended and accepted by the American Academy of Sleep Medicine (AASM) for the definition of hypopnea: arousal or ≥3% O2 desaturation (PSG-AHI3%) and ≥4% O2 desaturation (PSG-AHI4%), respectively. The results of PSG and ODM were compared by drawing parallels between the PSG-AHI3% and PSG-AHI4% with ODM-ODI3% and ODM-ODI4%, respectively. Bland-Altman plots, intraclass correlation, receiver operating characteristics (ROC) and area under the curve (AUC) analyses were conducted for statistical evaluation. ClinicalTrial.gov: NCT03526133.

RESULTS

This study included 304 participants (men: 55%; age: 55±14 years; body mass index: 30.9±5.7 kg/m2; PSG-AHI3%: 35.3±30.1/h, ODM-ODI3%: 30.3±25.9/h). The variability in the AASM scoring bias (PSG-AHI3% vs PSG-AHI4%) was significantly higher than that for PSG-AHI3% vs ODM-ODI3% (3%) and PSG-AHI4% vs ODM-ODI4% (4%) (9.7, 5.0, and 2.9/h, respectively; p<0.001). The limits of agreement (2±SD, derived from the Bland-Altman plot) of AASM scoring variability were also within the same range for (PSG vs ODM) 3% and 4% variability: 18.9, 21.6, and 16.5/h, respectively. The intraclass correlation/AUC for AASM scoring variability and PSG vs ODM 3% or 4% variability were also within the same range (0.944/0.977 and 0.953/0.955 or 0.971/0.964, respectively).

CONCLUSION

Our results showed that ODM is a simple and accurate method for the diagnosis of OSA.

The uses of overnight pulse oximetry

Overnight pulse oximetry (OPO) has proven to be an effective and beneficial technique to determine the cardiorespiratory status of patients in both the inpatient and outpatient settings. It is a cheap, safe, reliable, simple, and accurate method of patient monitoring as compared to the expensive and labor-intensive method of multichannel polysomnography for detecting sleep-disordered breathing. It provides accurate information about patient's oxygenation status and also helps in monitoring the response to continuous positive airway pressure and in the surgical treatment of obstructive sleep apnea (OSA). Nocturnal hypoxemia portends a poor prognosis in patients of chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD), and neuromuscular diseases. OPO can help its early detection and management.

Advanced polysomnographic analysis for OSA: A pathway to personalized management?

Obstructive sleep apnea (OSA) is a highly heterogeneous disorder, with diverse pathways to disease, expression of disease, susceptibility to co-morbidities and response to therapy, and is ideally suited to precision medicine approaches. Clinically, the content of the information-rich polysomnogram (PSG) is not currently fully utilized in determining patient management. Novel PSG parameters such as hypoxic burden, pulse transit time, cardiopulmonary coupling and the frequency representations of PSG sensor signals could predict a variety of cardiovascular disease, cancer and neurodegeneration co-morbidities. The PSG can also be used to identify key pathophysiological parameters such as loop gain, arousal threshold and muscle compensation which can enhance understanding of the causes of OSA in an individual, and thereby guide choices on therapy. Machine learning methods performing their own parameter extraction coupled with large PSG data sets offer an exciting opportunity for discovering new links between the PSG variables and disease outcomes. By exploiting existing and emerging analytical methods, the PSG may offer a pathway to personalized management for OSA.

Smart technologies toward sleep monitoring at home

With progress in sensors and communication technologies, the range of sleep monitoring is extending from professional clinics into our usual home environments. Information from conventional overnight polysomnographic recordings can be derived from much simpler devices and methods. The gold standard of sleep monitoring is laboratory polysomnography, which classifies brain states based mainly on EEGs. Single-channel EEGs have been used for sleep stage scoring with accuracies of 84.9%. Actigraphy can estimate sleep efficiency with an accuracy of 86.0%. Sleep scoring based on respiratory dynamics provides accuracies of 89.2% and 70.9% for identifying sleep stages and sleep efficiency, respectively, and a correlation coefficient of 0.94 for apnea-hypopnea detection. Modulation of autonomic balance during the sleep stages are well recognized and widely used for simpler sleep scoring and sleep parameter estimation. This modulation can be recorded by several types of cardiovascular measurements, including ECG, PPG, BCG, and PAT, and the results showed accuracies up to 96.5% and 92.5% for sleep efficiency and OSA severity detection, respectively. Instead of using recordings for the entire night, less than 5 min ECG recordings have used for sleep efficiency and AHI estimation and resulted in high correlations of 0.94 and 0.99, respectively. These methods are based on their own models that relate sleep dynamics with a limited number of biological signals. Parameters representing sleep quality and disturbed breathing are estimated with high accuracies that are close to the results obtained by polysomnography. These unconstrained technologies, making sleep monitoring easier and simpler, will enhance qualities of life by expanding the range of ubiquitous healthcare.

Opportunities for utilizing polysomnography signals to characterize obstructive sleep apnea subtypes and severity

BACKGROUND

Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder with many pathophysiological pathways to disease. Currently, the diagnosis and classification of OSA is based on the apnea-hypopnea index, which poorly correlates to underlying pathology and clinical consequences. A large number of in-laboratory sleep studies are performed around the world every year, already collecting an enormous amount of physiological data within an individual. Clinically, we have not yet fully taken advantage of this data, but combined with existing analytical approaches, we have the potential to transform the way OSA is managed within an individual patient. Currently, respiratory signals are used to count apneas and hypopneas, but patterns such as inspiratory flow signals can be used to predict optimal OSA treatment. Electrocardiographic data can reveal arrhythmias, but patterns such as heart rate variability can also be used to detect and classify OSA. Electroencephalography is used to score sleep stages and arousals, but specific patterns such as the odds-ratio product can be used to classify how OSA patients responds differently to arousals.

OBJECTIVE

In this review, we examine these and many other existing computer-aided polysomnography signal processing algorithms and how they can reflect an individual's manifestation of OSA.

SIGNIFICANCE

Together with current technological advance, it is only a matter of time before advanced automatic signal processing and analysis is widely applied to precision medicine of OSA in the clinical setting.

Validation of a photoplethysmography device for detection of obstructive sleep apnea in the perioperative setting

Obstructive sleep apnea (OSA) is a risk factor for perioperative complications, but many OSA patients present undiagnosed. While polysomnography (PSG) is the "gold standard" for diagnosis, its application is technology-intense, time-consuming, expensive, and requires specialists, often delaying surgery. Thus, miniaturized devices were developed for OSA screening aimed at ruling out major OSA while measuring a lesser number of biological signals. We evaluated the accuracy of a photoplethysmography (PPG)-based device for OSA detection. 48 patients with established or strongly suspected (STOP-Questionnaire) OSA scheduled for surgery underwent in their preoperative nights parallel recordings by PPG and a classic polygraphy (PG) devices (SomnoLab2®). We compared the diagnostic accuracy of the PPG in diagnosing mild [Apnea-/Hypopnea-Index (AHI) 5-14 events/h] and moderate-to-severe OSA (AHI > 15). PPG and PG-derived AHI correlated significantly (r = 0.85, p < 0.0001) and high area under curve (AUC) in receiver operator characteristics (ROC) values were seen for both AHI thresholds (0.93 and 0.95, respectively). For an AHI > 5, sensitivity was 100%, specificity 44%, positive predictive value (PPV) 62%, negative predictive value (NPV) 100%, likelihood ratio (LHR) 1.79, and Cohen κ was 0.43. For an AHI > 15, sensitivity was 92%, specificity 77%, PPV 60%, NPV 96%, LHR 4.04, and Cohen κ was 0.59. In a typical perioperative cohort of confirmed and suspected OSA patients, PPG reliably detected OSA patients while showing some false-positive results. Such devices are helpful for preoperative OSA screening.

Diagnostic accuracy of level IV portable sleep monitors versus polysomnography for obstructive sleep apnea: a systematic review and meta-analysis

PURPOSE

Obstructive sleep apnea (OSA) is the most common sleep-related breathing disorder. In-laboratory, overnight type I polysomnography (PSG) is the current "gold standard" for diagnosing OSA. Home sleep apnea testing (HSAT) using portable monitors (PMs) is an alternative testing method offering better comfort and lower costs. We aimed to systematically review the evidence on diagnostic ability of type IV PMs compared to PSG in diagnosing OSA.

METHODS

Participants: patients ≥16 years old with symptoms suggestive of OSA;intervention: type IV PMs (devices with < 2 respiratory channels); comparator: in-laboratory PSG; outcomes: diagnostic accuracy measures;studies: cross-sectional, prospective observational/experimental/quasi-experimental studies; information sources: MEDLINE and Cochrane Library from January 1, 2010 to May 10, 2016. All stages of review were conducted independently by two investigators.

RESULTS

We screened 6054 abstracts and 117 full-text articles to select 24 full-text articles for final review. These 24 studies enrolled a total of 2068 patients with suspected OSA and evaluated 10 different PMs with one to six channels. Only seven (29%) studies tested PMs in the home setting. The mean difference (bias) between PSG-measured and PM-measured apnea-hypopnea index (AHI) ranged from - 14.8 to 10.6 events/h. At AHI ≥ 5 events/h, the sensitivity of type IV PMs ranged from 67.5-100% and specificity ranged from 25 to 100%.

CONCLUSION

While current evidence is not very strong for the stand-alone use of level IV PMs in clinical practice, they can potentially widen access to diagnosis and treatment of OSA. Policy recommendations regarding HSAT use should also consider the health and broader social implications of false positive and false negative diagnoses.

Comparison of two home sleep testing devices with different strategies for diagnosis of OSA

PURPOSE

Home sleep testing devices are being widely used in diagnosis/screening for obstructive sleep apnea (OSA). We examined differences in OSA metrics obtained from two devices with divergent home monitoring strategies, the Apnea Risk Evaluation System (ARES™, multiple signals plus forehead reflectance oximetry) and the Nonin WristOx₂™ (single channel finger transmission pulse oximeter), compared to differences from night-night variability of OSA.

METHODS

One hundred fifty-two male/26 female subjects (BMI = 30.3 ± 5.6 kg/m², age = 52.5 ± 8.9 years) were recruited without regard to OSA symptoms and simultaneously wore both ARES™ and Nonin WristOx₂™ for two nights (n = 351 nights). Automated analysis of the WristOx₂ yielded oxygen desaturation index (ODI_Ox2, ≥4% O2 dips/h), and automated analysis with manual editing of ARES™ yielded AHI4_ARES (apneas + hypopneas with ≥4% O2 dips/h) and RDI_ARES (apneas + hypopneas with ≥4% O2 dips/h or arousal surrogates). Baseline awake oxygen saturation, percent time < 90% O2 saturation (%time < 90%O2Sat), and O2 signal loss were compared between the two methods.

RESULTS

Correlation between AHI4_ARES and ODI_Ox2 was high (ICC = 0.9, 95% CI = 0.87-0.92, p < 0.001, bias ± SD = 0.7 ± 6.1 events/h). Agreement values for OSA diagnosis (77-85%) between devices were similar to those seen from night-to-night variability of OSA using a single device. Awake baseline O2 saturation was significantly higher in the ARES™ (96.2 ± 1.6%) than WristOx₂™ (92.2 ± 2.1%, p < 0.01). There was a significantly lower %time < 90%O2Sat reported by the ARES™ compared to WristOx₂ (median (IQR) 0.5 (0.0, 2.6) vs. 2.1 (0.3, 9.7), p < 0.001), and the correlation was low (ICC = 0.2).

CONCLUSIONS

OSA severity metrics predominantly dependent on change in oxygen saturation and metrics used in diagnosis of OSA (AHI4 and ODI) correlated well across devices tested. However, differences in cumulative oxygen desaturation measures (i.e., %time < 90%O2Sat) between the devices suggest that caution is needed when interpreting this metric particularly in populations likely to have significant hypoxia.

Identifying individual sleep apnea/hypoapnea epochs using smartphone-based pulse oximetry

Sleep apnea, characterized by frequent pauses in breathing during sleep, poses a serious threat to the healthy growth and development of children. Polysomnography (PSG), the gold standard for sleep apnea diagnosis, is resource intensive and confined to sleep laboratories, thus reducing its accessibility. Pulse oximetry alone, providing blood oxygen saturation (SpO2) and blood volume changes in tissue (PPG), has the potential to identify children with sleep apnea. Thus, we aim to develop a tool for at-home sleep apnea screening that provides a detailed and automated 30 sec epoch-by-epoch sleep apnea analysis. We propose to extract features characterizing pulse oximetry (SpO2 and pulse rate variability [PRV], a surrogate measure of heart rate variability) to create a multivariate logistic regression model that identifies epochs containing apnea/hypoapnea events. Overnight pulse oximetry was collected using a smartphone-based pulse oximeter, simultaneously with standard PSG from 160 children at the British Columbia Children's hospital. The sleep technician manually scored all apnea/hypoapnea events during the PSG study. Based on these scores we labeled each epoch as containing or not containing apnea/hypoapnea. We randomly divided the subjects into training data (40%), used to develop the model applying the LASSO method, and testing data (60%), used to validate the model. The developed model was assessed epoch-by-epoch for each subject. The test dataset had a median area under the receiver operating characteristic (ROC) curve of 81%; the model provided a median accuracy of 74% sensitivity of 75%, and specificity of 73% when using a risk threshold similar to the percentage of apnea/hypopnea epochs. Thus, providing a detailed epoch-by-epoch analysis with at-home pulse oximetry alone is feasible with accuracy, sensitivity and specificity values above 73% However, the performance might decrease when analyzing subjects with a low number of apnea/hypoapnea events.

Evaluation of pulse oximeter derived photoplethysmographic signals for obstructive sleep apnea diagnosis

High prevalence of obstructive sleep apnea (OSA) has increased the demands for more convenient and accessible diagnostic devices other than standard in-lab polysomnography (PSG). Despite the increasing utility of photoplethysmograph (PPG), it remains understudied in underserved populations. This study aimed to evaluate the reliability of a standard pulse oximeter system with an automated analysis based on the PPG signal for the diagnosis of OSA, as compared with PSG derived measures.Consecutive out-patients with suspect OSA completed a PPG monitoring simultaneous with an overnight in-lab standard PSG. Forty-nine OSA patients (38 males, age 43.5 ± 16.9 years, BMI 26.9 ± 0.5 kg/m) were included in this study. Automated analyses were based on PPG and oximetry signals only. The PPG calculated measures were compared with PSG derived measures for agreement tests.Respiratory events index derived from PPG significantly correlated with PSG-derived apnea-hypopnea index (r = 0.935, P < .001). The calculation of total sleep time and oxygen desaturation index from PPG and PSG also significantly correlated (r = 0.418, P = .003; r = 0.933, P < .001, respectively). Bland-Altman plots showed good agreement between the PPG and the PSG measures. The overall sensitivity and specificity of PPG are good, especially in moderate and severe OSA groups.The tested PPG approach yielded acceptable results compared to the gold standard PSG among moderate to severe OSA patients. A pulse oximeter system with PPG recording can be used for the diagnosis or screening of OSA in high risk population.

The Association between Regional Fat Distribution and Acute Mountain Sickness in Young Hikers

Acute mountain sickness (AMS) can occur upon rapid ascent from low to high altitude. This study examined the association between central adiposity and the development of AMS in young adults during a high-altitude hike. Total and regional body fat were measured at sea level using dual-energy X-ray absorptiometry. Within 24 h of arriving in Cusco, Peru (3 400 meters) participants embarked on a 14-mile hike across the Andes Mountain range in southern Peru. Symptoms of AMS were assessed using the Lake Louise score at 24 h (3 400 meters), 29 h (4 100 meters), 34 h (3 800 meters) and 53 h (2 900 meters). 14 participants (mean age 21±2 years; women: 11, men: 3) completed the study. The number of participants exhibiting at least mild AMS increased from 6 (54%) at 3 400 meters to 9 (64%) at 3 800 meters. A higher AMS score at 4 100 meters was associated with greater android (r=0.72, p<0.01), trunk (r=0.73, p<0.01) and total body (r=0.71, p<0.01) fat, but not with total body fat % (r=0.39, p=0.16). Our findings suggest that central obesity, but not total body fat per se, may be an important factor in the development of AMS.

A Brief Review of Non-invasive Monitoring of Respiratory Condition for Extubated Patients with or at Risk for Obstructive Sleep Apnea after Surgery

Obstructive sleep apnea (OSA) is one of the important risk factors contributing to postoperative airway complications. OSA alters the respiratory physiology and increases the sensitivity of muscle tone of the upper airway after surgery to residual anesthetic medication. In addition, the prevalence of OSA was reported to be much higher among surgical patients than the general population. Therefore, appropriate monitoring to detect early respiratory impairment in postoperative extubated patients with possible OSA is challenging. Based on the comprehensive clinical observation, several equipment have been used for monitoring the respiratory conditions of OSA patients after surgery, including the continuous pulse oximetry, capnography, photoplethysmography (PPG), and respiratory volume monitor (RVM). To date, there has been no consensus on the most suitable device as a recommended standard of care. In this review, we describe the advantages and disadvantages of some possible monitoring strategies under certain clinical conditions. According to the literature, the continuous pulse oximetry, with its high sensitivity, is still the most widely used device. It is also cost-effective and convenient to use but has low specificity and does not reflect ventilation. Capnography is the most widely used device for detection of hypoventilation, but it may not provide reliable data for extubated patients. Even normal capnography cannot exclude the existence of hypoxia. PPG shows the state of both ventilation and oxygenation, but its sensitivity needs further improvement. RVM provides real-time detection of hypoventilation, quantitative precise demonstration of respiratory rate, tidal volume, and MV for extubated patients, but no reflection of oxygenation. Altogether, the sole use of any of these devices is not ideal for monitoring of extubated patients with or at risk for OSA after surgery. However, we expect that the combined use of continuous pulse oximetry and RVM may be promising for these patients due to their complementary function, which need further study.

A Brief Review of Non-invasive Monitoring of Respiratory Condition for Extubated Patients with or at Risk for Obstructive Sleep Apnea after Surgery

Obstructive sleep apnea (OSA) is one of the important risk factors contributing to postoperative airway complications. OSA alters the respiratory physiology and increases the sensitivity of muscle tone of the upper airway after surgery to residual anesthetic medication. In addition, the prevalence of OSA was reported to be much higher among surgical patients than the general population. Therefore, appropriate monitoring to detect early respiratory impairment in postoperative extubated patients with possible OSA is challenging. Based on the comprehensive clinical observation, several equipment have been used for monitoring the respiratory conditions of OSA patients after surgery, including the continuous pulse oximetry, capnography, photoplethysmography (PPG), and respiratory volume monitor (RVM). To date, there has been no consensus on the most suitable device as a recommended standard of care. In this review, we describe the advantages and disadvantages of some possible monitoring strategies under certain clinical conditions. According to the literature, the continuous pulse oximetry, with its high sensitivity, is still the most widely used device. It is also cost-effective and convenient to use but has low specificity and does not reflect ventilation. Capnography is the most widely used device for detection of hypoventilation, but it may not provide reliable data for extubated patients. Even normal capnography cannot exclude the existence of hypoxia. PPG shows the state of both ventilation and oxygenation, but its sensitivity needs further improvement. RVM provides real-time detection of hypoventilation, quantitative precise demonstration of respiratory rate, tidal volume, and MV for extubated patients, but no reflection of oxygenation. Altogether, the sole use of any of these devices is not ideal for monitoring of extubated patients with or at risk for OSA after surgery. However, we expect that the combined use of continuous pulse oximetry and RVM may be promising for these patients due to their complementary function, which need further study.

Long-term monitoring of cardiorespiratory patterns in drug-resistant epilepsy

OBJECTIVE

Sudden unexplained death in epilepsy (SUDEP) during inpatient electroencephalography (EEG) monitoring has been a rare but potentially preventable event, with associated cardiopulmonary markers. To date, no systematic evaluation of alarm settings for a continuous pulse oximeter (SpO₂ ) has been performed. In addition, evaluation of the interrelationship between the ictal and interictal states for cardiopulmonary measures has not been reported.

METHODS

Patients with epilepsy were monitored using video-EEG, SpO₂ , and electrocardiography (ECG). Alarm thresholds were tested systematically, balancing the number of false alarms with true seizure detections. Additional cardiopulmonary patterns were explored using automated ECG analysis software.

RESULTS

One hundred ninety-three seizures (32 generalized) were evaluated from 45 patients (7,104 h recorded). Alarm thresholds of 80-86% SpO₂ detected 63-73% of all generalized convulsions and 20-28% of all focal seizures (81-94% of generalized and 25-36% of focal seizures when considering only evaluable data). These same thresholds resulted in 25-146 min between false alarms. The sequential probability of ictal SpO₂ revealed a potential common seizure termination pathway of desaturation. A statistical model of corrected QT intervals (QTc), heart rate (HR), and SpO₂ revealed close cardiopulmonary coupling ictally. Joint probability maps of QTc and SpO₂ demonstrated that many patients had baseline dysfunction in either cardiac, pulmonary, or both domains, and that ictally there was dissociation-some patients exhibited further dysfunction in one or both domains.

SIGNIFICANCE

Optimal selection of continuous pulse oximetry thresholds involves a tradeoff between seizure detection accuracy and false alarm frequency. Alarming at 86% for patients that tend to have fewer false alarms and at 80% for those who have more, would likely result in a reasonable tradeoff. The cardiopulmonary findings may lead to SUDEP biomarkers and early seizure termination therapies.

A gender-aware framework for the daytime detection of obstructive sleep apnea

Sleep is an activity that is necessary for our survival. While the body may be still during sleep, the brain is actively progressing through repeating cycles of light and deep sleep whose purpose is physical and mental recovery and regeneration. Obstructive sleep apnea (OSA) is a sleep disorder in which breathing is frequently and repeatedly stopped during sleep. OSA severely interrupts the normal sleep cycle and the regeneration work associated with it and can thus result in detrimental health consequences. OSA, with all the adverse health effects associated with it, places a significant burden on the US healthcare system. Polysomnography (PSG) - the gold standard OSA diagnostic test - is an overnight sleep test that monitors the biophysiological changes that occur during sleep. The test is notorious for its intrusiveness, discomfort, prohibitive cost, and scarcity - all reasons contributing to OSA being a severely underdiagnosed sleep disorder. In this paper, we propose a system that can serve as an early-stage OSA diagnostic tool that can non-intrusively, affordably and accurately screen patients for the disorder before proceeding with a full-night PSG. Unlike existing tools, our solution is gender-aware and does not rely on detecting apneic events in the data to make a diagnosis; rather, it is designed to trigger brain responses that are indicative of the disorder. Our tool can therefore make diagnoses even while patients are awake and breathing normally. The system was tested in a pilot study of 21 patients and our preliminary results show an average accuracy of 96.25%.

Decreased exercise capacity and sleep-disordered breathing in patients with hypertrophic cardiomyopathy

BACKGROUND

Mechanisms of decreased exercise capacity in patients with hypertrophic cardiomyopathy (HCM) are not well understood. Sleep-disordered breathing (SDB) is a highly prevalent but treatable disorder in patients with HCM. The role of comorbid SDB in the attenuated exercise capacity in HCM has not been studied previously.

METHODS

Overnight oximetry, cardiopulmonary exercise testing, and echocardiographic studies were performed in consecutive patients with HCM seen at the Mayo Clinic. SDB was considered present if the oxygen desaturation index (number of ≥ 4% desaturations/h) was ≥ 10. Peak oxygen consumption (VO2 peak) (the most reproducible and prognostic measure of cardiovascular fitness) was then correlated with the presence and severity of SDB.

RESULTS

A total of 198 patients with HCM were studied (age, 53 ± 16 years; 122 men), of whom 32% met the criteria for the SDB diagnosis. Patients with SDB had decreased VO2 peak compared with those without SDB (16 mL O2/kg/min vs 21 mL O2/kg/min, P < .001). SDB remained significantly associated with VO2 peak after accounting for confounding clinical variables (P < .001) including age, sex, BMI, atrial fibrillation, and coronary artery disease.

CONCLUSIONS

In patients with HCM, the presence of SDB is associated with decreased VO2 peak. SDB may represent an important and potentially modifiable contributor to impaired exercise tolerance in this unique population.

Could transient hypoxia be associated with rhythmic masticatory muscle activity in sleep bruxism in the absence of sleep-disordered breathing? A preliminary report

Sleep bruxism (SB) is a repetitive jaw-muscle activity characterised by clenching or grinding of the teeth during sleep. Sleep bruxism activity is characterised by rhythmic masticatory muscle activity (RMMA). Many but not all RMMA episodes are associated with sleep arousal. The aim of this study was to evaluate whether transient oxygen saturation level change can be temporally associated with genesis of RMMA/SB. Sleep laboratory or home recordings data from 22 SB (tooth grinding history in the absence of reported sleep-disordered breathing) and healthy subjects were analysed. A total of 143 RMMA/SB episodes were classified in four categories: (i) no arousal + no body movement; (ii) arousal + no body movement; (iii) no arousal + body movement; (iv) arousal + body movement. Blood oxygen levels (SaO2 ) were assessed from finger oximetry signal at the baseline (before RMMA), and during RMMA. Significant variation in SaO2 over time (P = 0·001) was found after RMMA onset (+7 to +9 s). No difference between categories (P = 0·91) and no interaction between categories and SaO2 variation over time (P = 0·10) were observed. SaO2 of six of 22 subjects (27%) remained equal or slight increase after the RMMA/SB onset (+8 s) compared to baseline; 10 subjects (45%) slightly decreased (drop 0·01-1%) and the remaining (27%) decreased between 1% and 2%. These preliminary findings suggest that a subgroup of SB subjects had (i) a minor transient hypoxia potentially associated with the onset of RMMA episodes, and this (ii) independently of concomitant sleep arousal or body movements.