An interventional study of Belun Sleep platform in Sleep-Disordered Breathing, Sleep Architecture and Stroke, Acute, sponsored by Taipei Medical University Shuang Ho Hospital. Status unknown at 1 site in Taiwan. Open to participants aged 18 Years to 80 Years. Per ClinicalTrials.gov, last updated 2022-07-20.
Sponsored by Taipei Medical University Shuang Ho Hospital · Not applicable, Interventional, and Diagnostic
Obstructive sleep apnea (OSA) is prevalent in patients with stroke and has a negative effect on outcomes by predisposing them to recurrent stroke, increasing mortality, and so forth. Therefore, it is extremely important to identify OSA in patients with stroke.
Wearable devices can greatly reduce the manpower and material requirements of traditional laboratory-based polysomnography (PSG). With Photoplethysmography (PPG) technology and neural network algorithms, the Belun ring and the sleeping platform not only can detect blood oxygen, and heart rate but also can identify sleep stage and estimate the severity of sleep apnea.
In this study, inpatients with acute ischemic stroke in the hospital will proceed with three nights test for recording the parameters of the autonomic nervous system in the acute phase, evaluate whether sleep apnea and the feasibility of the Belun sleep platform.
It is important that early recognition of OSA and prompt treatment, which can potentially improve OSA-associated adverse outcomes, as well as understanding the degree of autonomic nervous function impairment for patients with acute ischemic stroke. After smoothing this process, it can help clinicians more accurately comprehend the condition, timing of admission, and discharge.
2,183 studies on the registry are indexed under Sleep Apnea Syndromes; 284 are open to participants now.
This study's planned enrollment of 120 is above the median of 53 across 1,400 interventional studies indexed under Sleep Apnea Syndromes.
Browse Sleep Apnea Syndromes studies →Taipei Medical University Shuang Ho Hospital is the lead sponsor of 101 studies on the registry; 18 are open to participants now.
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Exclusion Criteria:
Potential participants with suspected OSA will be identified from the schedule of the TMU sleep labs. Those subjects who satisfy the study conclusion and exclusion criteria will be approached and invited to participate in the study.
Device: Belun Sleep platform
BSP(Belun Technology Company Limited) is a novel wearable system using a neural network algorithm that consists of a patented wearable device (Belun Ring), a charging cradle, and cloud-based software. The Belun Ring, an FDA-cleared pulse oximeter, acquires signals from the radialis indicis artery of the proximal index finger. The Belun Ring total sleep time can be derived from features extracted from accelerometer, SpO2, and PPG signals, whereas Belun Ring AHI can be derived from Ring-TST and features extracted from HRV and SpO2 changes. The BSP proprietary OSA detection algorithm was using neural network. BSP performance can be improved by training the algorithm through continual data collection. To our knowledge, BSP is the only validated sleep platform using a medical-grade wearable pulse oximeter, actigraphy, and artificial intelligence algorithm that has the capability to identify sleep stages, detect OSA events, and monitor autonomic nervous system activity changes during sleep.
AHI, duration with SpO2 < 90%, and SpO2 nadir, as well as sleep stage parameters (total sleep time [TST], wake time, REM time, and NREM time)
To specifically assess the accuracy of BSP bAHI in predicting OSA by comparing to the concurrent in-lab PSG-AHI and to determine the accuracy of BSP sleep stage parameters by comparing to the concurrent PSG. BSP bAHI, BSP time with SpO2 \< 90%, and BSP-SpO2 nadir will be extracted from BSP and compared to PSGAHI (4% hypopnea criteria), PSG time with SpO2 \< 90% (PSG-T90), PSG-SpO2 nadir extracted from the concurrent PSG. BSP sleep stage parameters (total sleep time \[TST\], wake time, REM time, and NREM time) will be extracted from BSP and compared to the same parameters of the concurrent PSG. Epoch-by-epoch comparison will be performed.
Time frame: 1 year
Duration of BSP use and technically valid recording time
Duration of BSP use and technically valid recording time will be extracted from BSP for assessment feasibility of BSP testing in hospitalized patients.
Time frame: 1 year
Score of STOP-Bang
Stop-Bang cutoff of 3, 4, and 5 will be combined with PSG-cutoff of 5 events/h, 15 events/h, and 30 events/h and compared for accuracy of OSA prediction.
Time frame: 1 year
HRV parameters (including both frequency and time domain) ,the length of hospital stay, NIH Stroke Scale (NIHSS) score, and modified Rankin score (mRS)
ANS parameters including HRV frequency domain parameters (low frequency \[LF\], high frequency \[HF\], and LF/HF ratio) as well as time domain parameters (standard deviation of normal to normal R-R intervals \[SDNN\] and root mean square of successive heartbeat interval difference \[RMSSD\]) will be extracted from BSP and test the correlations with the length of hospital stay, NIH Stroke Scale (NIHSS) score, and modified Rankin score (mRS) will be analyzed.
Time frame: 1 year
Plan to share: No
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This study is status unknown, as verified in Jul 2022. You cannot join it, but the record below documents what was studied.
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