SNORE (Smartphone Analyses of Nocturnal Obstruction by Respiratory Evaluation) SOUNDS
- Conditions
- Chronic Obstructive Pulmonary DiseaseSleep Apnea, Obstructive
- Registration Number
- NCT03288376
- Lead Sponsor
- Incyphae, Inc.
- Brief Summary
This is a prospective multipart clinical performance study to compare the ability of the SnoreSounds algorithm with polysomnography (PSG) and a type III Home Sleep Testing (HST) device to identify patients with obstructive sleep apnea (OSA).
- Detailed Description
Consecutive patients referred to a sleep lab for possible OSA (obstructive sleep apnea) will be offered participation in this study. Study subjects will participate in either Part A, Part B or Part C of the study. Subjects will not participate in more than one part of the study. Study sites can participate in multiple parts of the study.
Part A: Sleep Lab
Consecutive patients referred to a sleep lab for possible OSA will be offered participation. Participants who provide informed consent will fill out a questionnaire and then have PSG, as it would normally be performed. During PSG additional sound recordings will be made in three ways:
1. Microphone placed 50-100 cm (20-40 inches) from the patient's mouth.
2. Android type Smart Phone with a recording application (app). The phone will be placed on a table 50-100 cm (20-40 inches)) from patient's mouth.
3. iPhone type Smart Phone with a recording app. Phone will be placed on a table 50-100 cm (20-40 inches) from patient's mouth.
The sound recordings obtained via the microphone and Smart Phones will be analyzed electronically for OSA by the sponsor's proprietary algorithm. A blinded comparison will be made between the PSG results and SnoreSounds algorithm results.
PSG will be performed and scored in a manner consistent with current (2012) American Academy of Sleep Medicine (AASM) standards. PSGs will be scored twice - with each scoring performed independently. If the Apnea Hypopnea Index (AHI) for each score places the patient in the same OSA severity range \[0-4 normal/minimal OSA, 5-14 mild, 15-30 moderate, \>30 severe\] the average of the two scores will be utilized. If however the scores put the patent in different OSA severity ranges, then the study will be scored by an independent sleep medicine physician-sleep technician team and assigned an AHI.
The results of the SnoreSounds testing will not be known to the sleep lab and the results obtained from Snore Sounds analysis will not be utilized in the clinical management of study participants.
Part B: Comparison of SnoreSounds algorithm to Home Sleep Testing (HST) (currently not enrolling in Part B)
Part C: Comparison of SnoreSounds algorithm to Home Sleep Testing (HST) and to Polysomnography (PSG) (currently not enrolling in Part C)
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 272
- Patients >or= 18 years old who are referred for polysomnography (PSG) or Home Sleep Test (HST) because of possible obstructive sleep apnea (OSA)
- Previous PSG or HST confirming OSA
- Prior surgery for snoring or OSA
- Medical contraindication for PSG
- Cognitive impairment that might interfere with obtaining informed consent or completing Clinical Questionnaire
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Agreement between algorithm with PSG reference standard for detection of OSA at an AHI cut-off of 15 immediate Agreement between algorithm with PSG reference standard for detection of OSA at an AHI cut-off of 15
- Secondary Outcome Measures
Name Time Method Comparison between algorithm and PSG assignment of OSA severity based on AHI [0-4 normal/minimal OSA, 5-14 mild, 15-30 moderate, >30 severe]. immediate Comparison between algorithm and PSG assignment of OSA severity based on AHI \[0-4 normal/minimal OSA, 5-14 mild, 15-30 moderate, \>30 severe\].
Trial Locations
- Locations (3)
Peninsula Sleep Center
🇺🇸Burlingame, California, United States
Doctors Community Hospital
🇺🇸Lanham, Maryland, United States
Northeast Medical Group
🇺🇸New London, Connecticut, United States