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

A consumer wearable device for tracking sleep respiratory events

PURPOSE

The diagnosis of obstructive sleep apnea (OSA) is instrument, operator, and time-dependent and therefore requires long waiting times. In recent decades, technological development has produced useful devices to monitor the health status of the population, including sleep. Therefore, the aim of this study was to evaluate a wearable device (WD) in a group of individuals at high risk of OSA.

METHODS

The study was conducted on consecutive subjects with high risk of OSA assessed by sleep questionnaires and clinical evaluation. All subjects performed cardio-respiratory monitoring (CRM) and WD simultaneously on a single night, after which the parameters of the two sleep investigations were compared.

RESULTS

Of 20 individuals enrolled, 60% were men and mean age was 57.3 ± 10.7 years. The apnea-hypopnea index (AHI) for the CRM was 23.1 ± 19.6 events·h-1 while it was 10.3 ± 8.3 events·h-1 for the WD. Correlation analysis between the results of the two investigations showed r = 0.19 (p = 0.40) for AHI and r = 0.4076 (p = 0.07) for sO2%. The accuracy for different stages of OSA severity was 70% in OSA cases and 60% in moderate to severe cases with sensitivity and specificity varying a great deal.

CONCLUSION

Small and low-cost devices may prove to be a valuable resource to reduce costs and waiting times for a sleep investigation in suspected OSA. However, diagnosis of sleep apnea requires valid and reliable instruments, so validation tests are necessary before a device can be commercialized.

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.

Application of photoplethysmography signals for healthcare systems: An in-depth review

BACKGROUND AND OBJECTIVES

Photoplethysmography (PPG) is a device that measures the amount of light absorbed by the blood vessel, blood, and tissues, which can, in turn, translate into various measurements such as the variation in blood flow volume, heart rate variability, blood pressure, etc. Hence, PPG signals can produce a wide variety of biological information that can be useful for the detection and diagnosis of various health problems. In this review, we are interested in the possible health disorders that can be detected using PPG signals.

METHODS

We applied PRISMA guidelines to systematically search various journal databases and identified 43 PPG studies that fit the criteria of this review.

RESULTS

Twenty-five health issues were identified from these studies that were classified into six categories: cardiac, blood pressure, sleep health, mental health, diabetes, and miscellaneous. Various routes were employed in these PPG studies to perform the diagnosis: machine learning, deep learning, and statistical routes. The studies were reviewed and summarized.

CONCLUSIONS

We identified limitations such as poor standardization of sampling frequencies and lack of publicly available PPG databases. We urge that future work should consider creating more publicly available databases so that a wide spectrum of health problems can be covered. We also want to promote the use of PPG signals as a potential precision medicine tool in both ambulatory and hospital settings.

A Minimum Set of Physiological Parameters to Diagnose Obstructive Sleep Apnea Syndrome Using Non-Invasive Portable Monitors. A Systematic Review

Introduction. Despite its high accuracy, polysomnography (PSG) has several drawbacks for diagnosing obstructive sleep apnea (OSA). Consequently, multiple portable monitors (PMs) have been proposed. Objective. This systematic review aims to investigate the current literature to analyze the sets of physiological parameters captured by a PM to select the minimum number of such physiological signals while maintaining accurate results in OSA detection. Methods. Inclusion and exclusion criteria for the selection of publications were established prior to the search. The evaluation of the publications was made based on one central question and several specific questions. Results. The abilities to detect hypopneas, sleep time, or awakenings were some of the features studied to investigate the full functionality of the PMs to select the most relevant set of physiological signals. Based on the physiological parameters collected (one to six), the PMs were classified into sets according to the level of evidence. The advantages and the disadvantages of each possible set of signals were explained by answering the research questions proposed in the methods. Conclusions. The minimum number of physiological signals detected by PMs for the detection of OSA depends mainly on the purpose and context of the sleep study. The set of three physiological signals showed the best results in the detection of OSA.

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.

Toward standardizing the clinical testing protocols of point-of-care devices for obstructive sleep apnea diagnosis

PURPOSE

In recent years, point-of-care (POC) devices, especially smart wearables, have been introduced to provide a cost-effective, comfortable, and accessible alternative to polysomnography (PSG)-the current gold standard-for the monitoring, screening, and diagnosis of obstructive sleep apnea (OSA). Thorough validation and human subject testing are essential steps in the translation of these device technologies to the market. However, every device development group tests their device in their own way. No standard guidelines exist for assessing the performance of these POC devices. The purpose of this paper is to critically distill the key aspects of the various protocols reported in the literature and present a protocol that unifies the best practices for testing wearable and other POC devices for OSA.

METHODS

A limited review and graphical descriptive analytics of literature-including journal articles, web sources, and clinical manuscripts by authoritative agencies in sleep medicine-are performed to glean the testing and validation methods employed for POC devices, specifically for OSA.

RESULTS

The analysis suggests that the extent of heterogeneity of the demographics, the performance metrics, subject survey, hypotheses, and statistical analyses need to be carefully considered in a systematic protocol for testing POC devices for OSA.

CONCLUSION

We provide a systematic method and list specific recommendations to extensively assess various performance criteria for human subject testing of POC devices. A rating scale of 1-3 is provided to encourage studies to put a focus on addressing the key elements of a testing protocol.

Journal of Clinical Monitoring and Computing 2018-2019 end of year summary: respiration

This paper reviews 28 papers or commentaries published in Journal of Clinical Monitoring and Computing in 2018 and 2019, within the field of respiration. Papers were published covering endotracheal tube cuff pressure monitoring, ventilation and respiratory rate monitoring, lung mechanics monitoring, gas exchange monitoring, CO2 monitoring, lung imaging, and technologies and strategies for ventilation management.

Synchronized mandibular movement and capnography: a novel approach to obstructive airway detection during procedural sedation-a post hoc analysis of a prospective study

Perioperative complications related to obstructive sleep apnea still occur despite the use of partial pressure end-tidal CO₂[Formula: see text] and pulse oximetry. Airway obstruction can complicate propofol sedation and a novel monitor combining mandibular movement analysis with capnography may facilitate its detection. Patients scheduled for sleep endoscopy were recruited and monitored with standard monitoring, [Formula: see text] and Jaw Activity (JAWAC) mandibular movement sensors. A post hoc analysis investigated airway obstruction prediction using a Respiratory Effort Sequential Detection Algorithm (RESDA) based on [Formula: see text] and mandibular movement signals. 21 patients were recruited and 54 episodes of airway obstruction occurred. RESDA detected obstructive apnea [mean ± SD (median)] 29 ± 29 (21) s, p < 0.0001, before [Formula: see text] alone. This prolonged the time between obstructive apnea detection and decrease to 90% oxygen saturation 64 ± 38 (54) versus 38 ± 20 (35) s, p < 0.0001. It predicted airway obstruction with a sensitivity and specificity of 81% and 93%, respectively. The RESDA algorithm, which is based on the combination of capnography with mandibular movement assessment of respiratory effort, can more rapidly alarm anesthetists of airway obstruction during propofol sedation than [Formula: see text] alone. However, [Formula: see text] pulse oximetry, and clinical monitoring are still required.Trial Registry numbers: ClinicalTrial.gov (NCT02909309) https://clinicaltrials.gov/ct2/show/NCT02909309 .