Validation of Sleep Apnea Diagnosis Device

Completed

• Conditions: Sleep Apnea

• Registration Number: NCT03526133
• Lead Sponsor: University of Sao Paulo General Hospital

Brief Summary

Obstructive sleep apnea (OSA) is common and largely underdiagnosed disease. The standard method for the diagnosis of OSA is a complete night polysomnography (PSG). Simple methods for OSA diagnosis are necessary. The overnight oximetry with the oxygen desaturation index (ODI) has been largely investigated as a diagnostic test for OSA but its accuracy remains undefined. The aim of our study is to evaluate if an wireless polygraph (Oxistar) is accurate to diagnosis OSA in patients referred to a Sleep Lab.

Detailed Description

Consecutive patients referred to the sleep laboratory with suspected diagnosis of OSA underwent in-laboratory polysomnography (PSG) and simultaneously wireless polygraph. The PSG oximeter and the wireless polygraph were worn on different fingers of the same hand. All sleep studies were reviewed by one blind investigator according the 2017 American Academy of Sleep Medicine recommendations. The number of desaturations from wireless polygraph at the 3 predefined threshold levels (of ODI-2%, ODI-3%, or ODI-4%) was derived automatically using proprietary algorithm. Moderate to severe OSA was defined as AHI ≥ 15 events/h. The diagnostic accuracy of ODI-2%, 3%, and 4% for the diagnosis of moderate-severe OSA were calculated for cut-off values from 1 to 20 desaturation events/h. The sleep actimetry was compared with the sleep stages from PSG, most of the statistical metrics applied for diagnosis were used to evaluate the applicability of this proposed method. Finally, the snoring events computed by the smartphone application were compared with the events heard by a specialist and the statistical comparison metrics were evaluated.

Study Timeline

• Study Start: 2017-07-07
• Study First Submitted: 2018-04-12
• Study First Submitted QC: 2018-05-03
• Study First Posted: 2018-05-16
• Status Verified: 2018-07
• Primary Completion: 2018-12-07
• Study Completion: 2019-02-07
• Last Update Submitted: 2019-09-27
• Last Update Posted: 2019-09-30

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 300

Inclusion Criteria

• referred by medical staff for an overnight assessment for suspected sleep apnea

Exclusion Criteria

• polysomnography for the CPAP titration

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Area under the curve (AUC)	Night during the polysomnography exam	AUC from ROC curves reflects the accuracy of Oxistar device to detect apnea events compared to gold-standard polysomnography
Bland-Altman Graph	Night during the polysomnography exam	The Bland-Altman graph evaluates the "agreement" between the gold-standard polysomnography and Oxistar device
Sensitivity	Night during the polysomnography exam	Sensitivity of Oxistar device to detect apnea events compared to gold-standard polysomnography
Specificity	Night during the polysomnography exam	Specificity of Oxistar device to detect apnea events compared to gold-standard polysomnography
Interclass Correlation Coefficient (ICC)	Night during the polysomnography exam	ICC measures the reliability of measurements or ratings between the gold-standard polysomnography and Oxistar device

Secondary Outcome Measures

Name	Time	Method
Sleep Actigraphy	Night during the polysomnography exam	Actigraphy is the continuous measurement of activity or movement with the use of a small device called an actigraph. Periods of movement suggest wakefulness while those of relative stillness would likely correspond to sleep or quiescence. The Oxistar has a embeded actigraph whose data will be compared with the sleep stage scoring from polysomnography (PSG), the gold standard for sleep assessment. Epoch-by-epoch (30 seconds) agreement between the actigraph and PSG will be assessed by calculating sensitivity, specificity, accuracy, area under the curve (AUC), Bland-Altman graph and interclass correlation coefficient (ICC)
Number of snoring events per hour of register (snoring/h)	Night during the polysomnography exam	Snoring is one of the signs suggestive of obstructive sleep apnea and has recently been considered as having great diagnostic potential. The smartphone application (app) through microphone performs the recording and the characteristics extraction of the patient's audio during sleep (register time). A multilayer perceptron (MPL) neural network classifies the event as snoring or non-snoring. Lastly, the amount of snoring occured is accounted and divided by the register time leading to the number of snoring/h. The agreement between snoring/h measured by the app and the heard by a specialist will be assessed by calculating sensitivity, specificity, accuracy and area under the curve (AUC).

Trial Locations

Locations (1)

Incor - Heart Institute, Sleep Laboratory; 🇧🇷 Sao Paulo, Brazil