Dataset Information

Performance of peripheral arterial tonometry-based testing for the diagnosis of obstructive sleep apnea in a large sleep clinic cohort.

ABSTRACT:

Study objectives

Peripheral arterial tonometry (PAT)-based technology represents a validated portable monitoring modality for the diagnosis of OSA. We assessed the diagnostic accuracy of PAT-based technology in a large point-of-care cohort of patients studied with concurrent polysomnography (PSG).

Methods

During study enrollment, all participants suspected to have OSA and tested by in-laboratory PSG underwent concurrent PAT device recordings.

Results

Five hundred concomitant PSG and WatchPat tests were analyzed. Median (interquartile range) PSG AHI was 18 (8-37) events/h and PAT AHI_3% was 25 (12-46) events/h. Average bias was + 4 events/h. Diagnostic concordance was found in 42%, 41%, and 83% of mild, moderate, and severe OSA, respectively (accuracy = 53%). Among patients with PAT diagnoses of moderate or severe OSA, 5% did not have OSA and 19% had mild OSA; in those with mild OSA, PSG showed moderate or severe disease in 20% and no OSA in 30% of patients (accuracy = 69%). On average, using a 3% desaturation threshold, WatchPat overestimated disease prevalence and severity (mean + 4 events/h) and the 4% threshold underestimated disease prevalence and severity by -6 events/h.

Conclusions

Although there was an overall tendency to overestimate the severity of OSA, a significant percentage of patients had clinically relevant misclassifications. As such, we recommend that patients without OSA or with mild disease assessed by PAT undergo repeat in-laboratory PSG. Optimized clinical pathways are urgently needed to minimize therapeutic decisions instituted in the presence of diagnostic uncertainty.

SUBMITTER: Ioachimescu OC

PROVIDER: S-EPMC7954003 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Performance of peripheral arterial tonometry-based testing for the diagnosis of obstructive sleep apnea in a large sleep clinic cohort.

Ioachimescu Octavian C OC Allam J Shirine JS Samarghandi Arash A Anand Neesha N Fields Barry G BG Dholakia Swapan A SA Venkateshiah Saiprakash B SB Eisenstein Rina R Ciavatta Mary-Margaret MM Collop Nancy A NA

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine 20201001 10

<h4>Study objectives</h4>Peripheral arterial tonometry (PAT)-based technology represents a validated portable monitoring modality for the diagnosis of OSA. We assessed the diagnostic accuracy of PAT-based technology in a large point-of-care cohort of patients studied with concurrent polysomnography (PSG).<h4>Methods</h4>During study enrollment, all participants suspected to have OSA and tested by in-laboratory PSG underwent concurrent PAT device recordings.<h4>Results</h4>Five hundred concomitan ...[more]

PMID: 32515348

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Project description:Study objectivesWe investigated the diagnostic accuracy for the identification of obstructive sleep apnea (OSA) and its severity of a noninvasive technology based on image processing (SleepWise).MethodsThis is an observational, prospective study to evaluate the degree of agreement between polysomnography (PSG) and SleepWise. We recruited 56 consecutive subjects with suspected OSA who were referred as outpatients to the Sleep Unit of the Hospital Universitari Germans Trias i Pujol (HUGTiP) from January 2013 to January 2014. All patients underwent laboratory PSG and image processing with SleepWise simultaneously the same night. Both PSG and SleepWise analyses were carried independently and blindly.ResultsWe analyzed 50 of the 56 patients recruited. OSA was diagnosed through PSG in a total of 44 patients (88%) with a median apnea-hypopnea index (AHI) of 25.35 (24.9). According to SleepWise, 45 patients (90%) met the criteria for a diagnosis of OSA, with a median AHI of 22.8 (22.03). An analysis of the ability of PSG and SleepWise to classify patients by severity on the basis of their AHI shows that the two diagnostic systems distribute the different groups similarly. According to PSG, 23 patients (46%) had a diagnosis of severe OSA, 11 patients (22%) moderate OSA, and 10 patients (20%) mild OSA. According to SleepWise, 20, 13, and 12 patients (40%, 26%, and 24%, respectively) had a diagnosis of severe, moderate, and mild OSA respectively. For OSA diagnosis, SleepWise was found to have sensitivity of 100% and specificity of 83% in relation to PSG. The positive predictive value was 97% and the negative predictive value was 100%. The Bland-Altman plot comparing the mean AHI values obtained through PSG and SleepWise shows very good agreement between the two diagnostic techniques, with a bias of -3.85, a standard error of 12.18, and a confidence interval of -0.39 to -7.31.ConclusionsSleepWise was reasonably accurate for noninvasive and automatic diagnosis of OSA in outpatients. SleepWise determined the severity of OSA with high reliability. The current study including simultaneous laboratory PSG and SleepWise processing image is proposed as a reasonable validation standard.

Project description:Study objectivesThe 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.MethodsThe 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.ResultsThe 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 registrationRegistry: 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.

Dataset Information

Performance of peripheral arterial tonometry-based testing for the diagnosis of obstructive sleep apnea in a large sleep clinic cohort.

Study objectives

Methods

Results

Conclusions

Publications

Performance of peripheral arterial tonometry-based testing for the diagnosis of obstructive sleep apnea in a large sleep clinic cohort.

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