Clinical Trial Details
— Status: Recruiting
Administrative data
NCT number |
NCT04112927 |
Other study ID # |
B2018:094 |
Secondary ID |
|
Status |
Recruiting |
Phase |
|
First received |
|
Last updated |
|
Start date |
October 1, 2021 |
Est. completion date |
June 2023 |
Study information
Verified date |
February 2021 |
Source |
University of Manitoba |
Contact |
Abnoor Kaur, M.Sc. |
Phone |
2044747023 |
Email |
abnoorkaur9[@]gmail.com |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
The purpose of this study is to investigate the feasibility of sound analysis for: a) sleep
apnea detection both during wakefulness and sleep, and b) flow-sound relationship during both
wakefulness and sleep in patients and control individuals. The ultimate goal of our research
is to simplify the current assessments for sleep apnea detection so that it is more
convenient for patients and also much faster than the current techniques.
Description:
Sleep apnea, in particular obstructive sleep apnea (OSA), is one of the most common breathing
disorders and is associated with major comorbidities such as higher risk perioperative
complications. This is particularly concerning given that about 40-80% of people with
moderate-severe OSA remain undiagnosed. Due to the resource-intensive assessments required to
diagnose OSA and the significantly increased risk of car accidents and perioperative
complications associated with undiagnosed OSA, there is a critical need to develop a more
effective method to screen for OSA quickly and reliably.
The most widely used clinical OSA screening tool is the STOP-Bang questionnaire, which is a
quick and easy-to-implement inquiry form that has a high sensitivity to detect moderate and
severe OSA (>93%), but it has a very high rate of false positives (>63%). Thus, a significant
number of patients without OSA will continue to be referred for PSG, which contributes to a
strain on the healthcare system. Therefore, a quick and reliable screening tool for OSA and
its severity during wakefulness is very appealing but challenging, as people with OSA do not
show any apparent symptoms during wakefulness.
We have developed a novel screening algorithm for OSA based on the analysis of tracheal
breathing sounds recorded from an individual during wakefulness, called AWakeOSA. It can
predict OSA with a sensitivity (86%) similar to STOP-Bang, but with a much higher specificity
(84%) for detecting individuals without OSA. The AWakeOSA technology still needs significant
research and quality improvements to become a reliable home-care device for screening under
unsupervised conditions, which is the central purpose of this project. In addition, we are
interested to investigate the breathing sound changes from wakefulness to sleep in both
groups of healthy and apneic population. For that, we need to record PSG data and breathing
sounds during sleep in addition to recording breathing sounds during wakefulness.
We have also designed a specialized hardware device, called ASAD-3, capable of recording
breathing sounds with high quality during both wakefulness (short-period recording) and
during sleep (long hours recording) that uses two small microphones that are placed in
contact with the skin over the trachea and lung, respectively. The hardware device will be
utilized to optimize the AWakeOSA algorithm and work towards achieving a reliable home-care
device for screening under unsupervised conditions.
The proposed technology will enable a reliable and quick diagnosis of OSA that can be either
used in a clinician's office during wakefulness and/or used at home by people to monitor
their own OSA. The outcomes of this study will benefit the health care system and society
significantly as it will: 1) reduce the financial burden of OSA on the healthcare system by
reducing the need for PSG and unnecessary preoperative resources; and 2) provide a quick and
reliable personal OSA home-care monitoring system for better OSA treatment management.