Trial Review

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The ANZCTR now automatically displays published trial results and simplifies the addition of trial documents such as unpublished protocols and statistical analysis plans.

These enhancements will offer a more comprehensive view of trials, regardless of whether their results are positive, negative, or inconclusive.

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been endorsed by the ANZCTR. Before participating in a study, talk to your health care provider and refer to this information for consumers
Trial registered on ANZCTR


Registration number
ACTRN12619000366156
Ethics application status
Approved
Date submitted
5/03/2019
Date registered
7/03/2019
Date last updated
6/08/2021
Date data sharing statement initially provided
7/03/2019
Type of registration
Prospectively registered

Titles & IDs
Public title
Automated artificial-intelligence based, preliminary cardiac diagnostics decision support tool to the medical practitioner.
Scientific title
A feasibility study to assess Artificial Intelligence (AI) algorithm performance in identifying heart murmurs in the general echocardiography referred patient’s population.
Secondary ID [1] 297610 0
None
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Valvular Heart Disease 311873 0
Condition category
Condition code
Cardiovascular 310467 310467 0 0
Other cardiovascular diseases

Intervention/exposure
Study type
Observational
Patient registry
False
Target follow-up duration
Target follow-up type
Description of intervention(s) / exposure
Participants will be exposed to auscultation done with a digital stethoscope. The patient's heart sounds audio will be recorded and analysed remotely. An Echocardiography will follow, which is done as a part of the patient's routine investigation.

We estimate that the auscultation will not add to the patient visit at the Echocardiography laboratory more than 5-10 minutes. An Echocardiograph which is done as part of the patient routine investigation and done in accordance to standard of care will follow and is estimated to take approximately 45 minutes. This will conclude the participant involvement in the trial.

The gathered data would be used to train an Artificial-Intelligence system to identify valvular heart diseases based on auscultation.
Intervention code [1] 313842 0
Diagnosis / Prognosis
Intervention code [2] 313843 0
Early Detection / Screening
Comparator / control treatment
No control group
Control group
Uncontrolled

Outcomes
Primary outcome [1] 319332 0
The ability of an AI system to identify a valvular heart disease compared with Echocardiography analysed report, will be assessed.
Timepoint [1] 319332 0
An interim analysis will be conducted after the enrollment of the first 200 patients. Additional analysis would be conducted after 500 patients are enrolled.
Secondary outcome [1] 367812 0
The ability of an AI system to identify a murmur type compared with Echocardiography analysed report, will be assessed.
Timepoint [1] 367812 0
An interim analysis will be conducted after the enrollment of the first 200 patients. Additional analysis would be conducted after 500 patients are enrolled.

Eligibility
Key inclusion criteria
o Patient over the age of 18 years old, who is able to provide written informed consent and verbal consent to participate in this study.
o The patient is referred to perform an Echocardiography.
Minimum age
18 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
o A patient who is unable to provide written and verbal informed consent.
o A female patient who is aware she is pregnant.

Study design
Purpose
Screening
Duration
Cross-sectional
Selection
Convenience sample
Timing
Prospective
Statistical methods / analysis

Recruitment
Recruitment status
Recruiting
Date of first participant enrolment
Anticipated
12/03/2019
Actual
15/03/2019
Date of last participant enrolment
Anticipated
12/03/2022
Actual
Date of last data collection
Anticipated
13/04/2022
Actual
Sample size
Target
500
Accrual to date
118
Final
Recruitment in Australia
Recruitment state(s)
NSW
Recruitment hospital [1] 13298 0
Royal North Shore Hospital - St Leonards
Recruitment postcode(s) [1] 25872 0
2065 - St Leonards

Funding & Sponsors
Funding source category [1] 302153 0
Commercial sector/Industry
Name [1] 302153 0
Visionware Solutions Pty Ltd
Country [1] 302153 0
Australia
Funding source category [2] 302155 0
Hospital
Name [2] 302155 0
Northern Sydney Local Health District
Country [2] 302155 0
Australia
Primary sponsor type
Commercial sector/Industry
Name
Visionware Solutions Pty Ltd
Address
4/8-10 Parraween Street
Cremorne, NSW 2090
Country
Australia
Secondary sponsor category [1] 301992 0
None
Name [1] 301992 0
Address [1] 301992 0
Country [1] 301992 0
Other collaborator category [1] 280582 0
Hospital
Name [1] 280582 0
Northern Sydney Local Health District
Address [1] 280582 0
Executive Unit, level 5 Douglas Building, Royal North Shore Hospital, Pacific Highway, St Leonards, NSW, 2065
Country [1] 280582 0
Australia

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 302835 0
Northern Sydney Local Health District HREC
Ethics committee address [1] 302835 0
Research Office Kolling Building, Level 13 Royal North Shore Hospital St Leonards NSW 2065
Ethics committee country [1] 302835 0
Australia
Date submitted for ethics approval [1] 302835 0
22/10/2018
Approval date [1] 302835 0
07/11/2018
Ethics approval number [1] 302835 0

Summary
Brief summary
MedAl Cardiology is a software tool that will enable health care professionals to diagnose
various heart conditions in real time using Artificial Intelligence (AI). It would provide a diagnosis of heart functioning by analysing heart sounds recordings. The MedAI Cardiology algorithm will classify the patient status as “Normal” or “Abnormal” and will provide in-depth insights about various heart conditions. An automated analysis capability will support medical practitioners in deciding whether or not to refer the patient for further investigation.
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 91554 0
Prof Ravinay Bhindi
Address 91554 0
Department of Cardiology, Level 5, Acute Services Building, Royal North Shore Hospital
Reserve Rd, St Leonards, NSW, 2065
Country 91554 0
Australia
Phone 91554 0
+61294395290
Fax 91554 0
Email 91554 0
[email protected]
Contact person for public queries
Name 91555 0
Dina Peleg Kowarski
Address 91555 0
Dina Peleg Kowarski, Director
Visionware Solutions
4/8-10 Parraween Street
Cremorne, NSW 2090
Country 91555 0
Australia
Phone 91555 0
+61481548166
Fax 91555 0
Email 91555 0
[email protected]
Contact person for scientific queries
Name 91556 0
Dina Peleg Kowarski
Address 91556 0
Dina Peleg Kowarski, Director
Visionware Solutions
4/8-10 Parraween Street
Cremorne, NSW 2090
Country 91556 0
Australia
Phone 91556 0
+61481548166
Fax 91556 0
Email 91556 0
[email protected]

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment


What supporting documents are/will be available?

No Supporting Document Provided



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
No additional documents have been identified.