Clinical trial NCT03457428: Comprehensive Analysis of Respiratory Events Using Smartphone Systems
Official title: Evaluation of Novel Proprietary Biometric as an Aid in the Screening and Diagnosis of Sleep Breathing Disorders
Study type: OBSERVATIONAL
Overall status: TERMINATED
Conditions: Obstructive Sleep Apnea
Keywords: obstructive sleep apnea
home sleep testing
Lead sponsor: Resonea, Inc
Sponsor class: INDUSTRY
First posted: 2018-03-07
Enrollment: 83
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_ONLY
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The study population includes patients who are referred for polysomnography because of possible obstructive sleep apnea (OSA).

Brief summary: Earlier studies suggest that acoustical analysis of snoring sounds can identify obstructive sleep apnea (OSA). The goal of the current study is to refine and validate algorithms for OSA diagnosis.

Detailed description: Obstructive sleep apnea (OSA) is a form of sleep-disordered breathing (SDB) where cessation of breathing occurs during sleep in 9% of middle-aged women and 25% or middle-aged men. Major health issues and risks have been linked to untreated sleep apnea, including drug-resistant hypertension, obesity, congestive heart failure and diabetes.

Patient awareness of this condition is growing, but obtaining adequate data has continuing barriers. The gold standard for sleep testing is the overnight clinical polysomnogram (PSG) where over 20 sensors are attached to a patient and vital signs are monitored and recorded over the course of a 6-8 hour sleep test.

This is a prospective clinical performance study to compare the ability of proprietary algorithms that analyze sleep recordings from smartphones, with FDA cleared Level III home sleep testing (HST) devices, to identify patients with obstructive sleep apnea (OSA).

Consecutive patients referred for home sleep testing (HST) for possible OSA will be offered participation. Participants who provide informed consent will fill out a questionnaire and then proceed with HST in their home. During HST, additional sound recordings will be made with either:

1. Android type smartphone with a recording application (app). The phone will be placed on a table 50-100 cm (20-40 inches) from patient's mouth.

   or
2. IPhone type smartphone with a recording application (app). Phone will be placed on a table 50-100 cm (20-40 inches) from patient's mouth

The sound recordings obtained via smartphones will be analyzed electronically for OSA by the proprietary algorithms. This will be performed by engineers at Resonea, Inc., the study sponsor, who will be blinded to the results obtained by the Level III HST device

HST will be performed using a type III home sleep monitor that has been cleared by the FDA and validated to assist in the diagnosis of OSA. HST results will be interpreted according to the standards established for the device being utilized. HST tests will be interpreted by sleep medicine physicians at the study sites who will be blinded to the assessment from the proprietary algorithms.

The independently determined results of HST and proprietary algorithms analysis will then be compared.

The results of the proprietary algorithm testing will not be known to those providing HST and the proprietary algorithm analysis will not be utilized in the clinical management of study participants

The primary objectives are: (a) to demonstrate that obtaining recordings in home setting for use with the proprietary sound analysis software is feasible and safe; and (b) to compare the results of the proprietary algorithm score with HST for the diagnosis of OSA.

The secondary objectives are: (a) to compare the recorded sound data against various scoring metrics from the HST; and (b) to demonstrate that use of the sound analysis software on smartphones is feasible for patients in the home sleep setting; and (c) to use the proprietary software to identify sleep disordered breathing beyond OSA, including central sleep apnea, snoring and other conditions.

Eligibility criteria: Inclusion Criteria:

* referred for polysomnography (PSG) because of possible obstructive sleep apnea (OSA)
* owns/possesses a smartphone for use during the study. Must be:

  * Android models running Android OS Samsung Galaxy 5 or later
  * iPhone models running iOS 6 or later

Exclusion Criteria:

* previous PSG or home sleep testing (HST) confirmation of OSA
* prior surgery for snoring or OSA
* medical contraindication of HST, as applicable
* congnitive impairment that might interfere with obtaining informed consent, or completing Clinical Questionnaire

Primary outcomes:
measure: Level of agreement between Sleep Breathing Index Score obtained from analysis by the proprietary algorith, and the Apnea-Hypopnea Index (AHI) as obtained by HST, with a cut-off of 15
timeFrame: immediate
Secondary outcomes:
Other outcomes:
Locations:
city: Burlingame
country: United States
facility: Peninsula Sleep Center
state: California
city: Santa Monica
country: United States
facility: Santa Monica Clinical Trials
state: California
city: New York
country: United States
facility: Blue Sleep
state: New York
city: Kirkland
country: United States
facility: Sounds Sleep Health
state: Washington
Study officials:
affiliation: Resonea, Inc
name: Jon Freudman, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Karunajeewa AS, Abeyratne UR, Hukins C. Multi-feature snore sound analysis in obstructive sleep apnea-hypopnea syndrome. Physiol Meas. 2011 Jan;32(1):83-97. doi: 10.1088/0967-3334/32/1/006. Epub 2010 Nov 30.
citation: Abeyratne UR, de Silva S, Hukins C, Duce B. Obstructive sleep apnea screening by integrating snore feature classes. Physiol Meas. 2013 Feb;34(2):99-121. doi: 10.1088/0967-3334/34/2/99. Epub 2013 Jan 23.