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Trial registered on ANZCTR


Registration number
ACTRN12616000409471
Ethics application status
Approved
Date submitted
17/03/2016
Date registered
30/03/2016
Date last updated
24/01/2020
Date data sharing statement initially provided
26/03/2019
Type of registration
Prospectively registered

Titles & IDs
Public title
Snoring Sound Analysis for the Diagnosis of Patients with suspected Obstructive Sleep Apnoea
Scientific title
Comparison of a snoring sound analysis algorithm against polysomnography for the diagnosis of obstructive sleep apnoea in patients attending a Sleep Disorders Centre: a diagnostic test accuracy study
Secondary ID [1] 288816 0
none
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Obstructive Sleep Apnoea 298056 0
Condition category
Condition code
Respiratory 298216 298216 0 0
Sleep apnoea

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
Our proposed study aims to systematically explore the performance of our snore/breathing sound technology algorithm against Type I Polysomnography (PSG) by conducting a statistically powered study in a sleep laboratory as well as a home setting.

We hypothesise that breathing sounds (including snoring), when analysed using appropriate mathematical methods and machine learning techniques, can provide sufficient information to detect Obstructive Sleep Apnoea (OSA) at a sensitivity and specificity >92% simultaneously, with respect to Type 1 PSG.

It is planned to prospectively recruit up to 50 patients with suspected sleep disordered breathing who are already listed for diagnostic PSG study in our sleep lab. These patients will undergo a one night diagnostic PSG sleep study as per usual practice in the sleep laboratory. In addition, study subjects will have sound measurements recorded (with a portable sound recorder, installed on a smart phone), along with oesophageal pressure monitoring.

Following the first night in the laboratory the next phase of snoring sound data collection will occur at home over the next 7 nights. Subjects will be loaned a smart phone for 7 nights, with an application ("app") installed to achieve this. The smart phone "app" will be self activated by patients when going to sleep, and switched off when awakening. The app solely records snoring sounds during the night for later analysis by our software. No other data collection will take place during this phase. The timing of the activation of the "app" can be correlated against a sleep diary to confirm appropriate use.

Data from the PSG will be analysed in the usual fashion by sleep physicians.

Analysis of the recorded snoring sounds using the externally developed algorithm will then be correlated against Apnoea-Hypopnoea Index (AHI) as measured during the PSG by the principal investigators. This information will aid in the validation of a streamlined technique to be used in the diagnosis of sleep disordered breathing.
Intervention code [1] 294237 0
Diagnosis / Prognosis
Comparator / control treatment
The reference-standard for OSA diagnosis is Type 1 Polysomnography (PSG). It requires an overnight laboratory stay connected to between 15-20 channels of measurements. Physiological data regarding patient's sleep is recorded, including cardiovascular, respiratory and neurological parameters.

The test will be administered as it usually would be for these patients with suspected OSA. The test is administered by sleep scientists and technicians. The patient stays for one night. The test subjects will have simultaneous snoring sound recording from the first night (in the lab) and then for 7 nights at home following this on a provided smart phone.
Control group
Active

Outcomes
Primary outcome [1] 297719 0
The sensitivity of the snoring sound technology will then be evaluated against the gold standard Apnoea-Hypopnoea Index (AHI) as measured by laboratory based PSG.
Timepoint [1] 297719 0
8 consecutive nights of data will be collected with the experimental snoring sounds analysis. The PSG will be done on the first night, which is in the laboratory. The following 7 nights will be for further data collection at home.
Primary outcome [2] 297784 0
The specificity of the snoring sound technology will then be evaluated against the gold standard Apnoea-Hypopnoea Index (AHI) as measured by laboratory based PSG.
Timepoint [2] 297784 0
8 consecutive nights of data will be collected with the experimental snoring sounds analysis. The PSG will be done on the first night, which is in the laboratory. The following 7 nights will be for further data collection at home.
Secondary outcome [1] 322009 0
Nil
Timepoint [1] 322009 0
nil

Eligibility
Key inclusion criteria
Patients listed for PSG studies through the Sleep Disorders Centre
Minimum age
18 Years
Maximum age
No limit
Gender
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
1. intellectual impairment or inability to provide valid consent.
2. Less than 18 years old.

Study design
Purpose of the study
Diagnosis
Allocation to intervention
Non-randomised trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Not applicable.
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Not applicable.
Masking / blinding
Who is / are masked / blinded?



Intervention assignment
Other design features
Phase
Not Applicable
Type of endpoint(s)
Efficacy
Statistical methods / analysis
In previous pilot studies, logistic regression models for the diagnosis of OSA (at AHI thresholds of 15 and 30) and the sensitivity and specificity of diagnosis was calculated using snoring sound analysis against Type I PSG. With n=51 (male model) and n=35 (female model) we obtained sensitivity, specificity, positive and negative predictive values all >92%. This forms the basis of our assumption that a population of 50 would be sufficiently powered for the proposed study's purpose.


Recruitment
Recruitment status
Recruiting
Date of first participant enrolment
Anticipated
Actual
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
Sample size
Target
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
QLD
Recruitment hospital [1] 5467 0
Princess Alexandra Hospital - Woolloongabba
Recruitment postcode(s) [1] 12962 0
4102 - Woolloongabba

Funding & Sponsors
Funding source category [1] 293152 0
Hospital
Name [1] 293152 0
Princess Alexandra Hospital
Address [1] 293152 0
Department of Respiratory and Sleep Medicine
Princess Alexandra Hospital.
199 Ipswich Rd
Woolloongabba QLD 4102
Country [1] 293152 0
Australia
Primary sponsor type
Hospital
Name
Department of Respiratory and Sleep Medicine Princess Alexandra Hospital.
Address
Department of Respiratory and Sleep Medicine
Princess Alexandra Hospital.
199 Ipswich Rd
Woolloongabba QLD 4102
Country
Australia
Secondary sponsor category [1] 291952 0
None
Name [1] 291952 0
None
Address [1] 291952 0
None
Country [1] 291952 0

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 294650 0
Metro South Health Human Research Ethics Committee
Ethics committee address [1] 294650 0
Kent St Woolloongabba QLD 4102
Ethics committee country [1] 294650 0
Australia
Date submitted for ethics approval [1] 294650 0
01/04/2016
Approval date [1] 294650 0
10/05/2016
Ethics approval number [1] 294650 0

Summary
Brief summary
It has been well established in the literature that snoring sounds can be used to detect the presence of obstructive sleep apnoea (OSA). Currently the gold standard in the diagnosis of obstructive sleep apnoea is Type I Polysomnography (PSG), which is both time and resource intensive. Streamlining the diagnostic process for patients with OSA is of great significance given the increasing prevalence and awareness of the condition.

Retrospective pilot studies have been conducted previously through our unit to assess the utility of analysing snoring sounds as a predictor for obstructive sleep apnoea. Our proposed study aims to systematically explore the performance of our snore/breathing sound technology algorithm against Type I PSG by conducting a statistically powered study in a sleep laboratory as well as a home setting.

We hypothesise that breathing sounds (including snoring), when analysed using appropriate mathematical methods and machine learning techniques, can provide sufficient information to detect OSA at a sensitivity and specificity >92% simultaneously, with respect to Type 1 PSG.

It is planned to prospectively recruit up to 50 patients with suspected sleep disordered breathing who are already listed for diagnostic PSG study in our sleep lab. These patients will undergo the sleep study as planned, and will undergo a slightly modified protocol with additional sound measurements, along with oesophageal pressure monitoring. The patient will then proceed to have another 7 nights data collected with a portable sound recorded (stored as an "app" on a provided smart phone) to further validate data against PSG.

Analysis of the recorded snoring sounds using the externally developed algorithim will then be correlated against Apnoea-Hypopnoea Index (AHI) as measured during the PSG, which is considered the current diagnostic gold standard. Ideally this information will aid in the validation of a streamlined technique to be used in the diagnosis of sleep disordered breathing.
Trial website
None
Trial related presentations / publications
None
Public notes
None

Contacts
Principal investigator
Name 64482 0
Dr Robert Sheehy
Address 64482 0
Department of Respiratory and Sleep Medicine
Princess Alexandra Hospital.
199 Ipswich Rd
Woolloongabba QLD 4102
Country 64482 0
Australia
Phone 64482 0
+61731762111
Fax 64482 0
Email 64482 0
Robert.Sheehy@health.qld.gov.au
Contact person for public queries
Name 64483 0
Dr Robert Sheehy
Address 64483 0
Department of Respiratory and Sleep Medicine
Princess Alexandra Hospital.
199 Ipswich Rd
Woolloongabba QLD 4102
Country 64483 0
Australia
Phone 64483 0
+61731762111
Fax 64483 0
Email 64483 0
Robert.Sheehy@health.qld.gov.au
Contact person for scientific queries
Name 64484 0
Dr Robert Sheehy
Address 64484 0
Department of Respiratory and Sleep Medicine
Princess Alexandra Hospital.
199 Ipswich Rd
Woolloongabba QLD 4102
Country 64484 0
Australia
Phone 64484 0
+61731762111
Fax 64484 0
Email 64484 0
Robert.Sheehy@health.qld.gov.au

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment
Raw, individual participant data will be utilised and interpreted by current investigation team only.
What supporting documents are/will be available?
No other documents available
Summary results
No Results