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Trial details imported from ClinicalTrials.gov

For full trial details, please see the original record at https://clinicaltrials.gov/study/NCT05558605




Registration number
NCT05558605
Ethics application status
Date submitted
11/09/2022
Date registered
28/09/2022
Date last updated
22/08/2024

Titles & IDs
Public title
Use of Artificial Intelligence-Guided Echocardiography to assIst cardiovascuLar Patient managEment
Scientific title
Use of Artificial Intelligence-Guided Echocardiography to assIst cardiovascuLar Patient managEment
Secondary ID [1] 0 0
325-22
Universal Trial Number (UTN)
Trial acronym
AGILE-Echo
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Heart Failure 0 0
Valve Heart Disease 0 0
Condition category
Condition code
Cardiovascular 0 0 0 0
Coronary heart disease
Cardiovascular 0 0 0 0
Other cardiovascular diseases

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
Diagnosis / Prognosis - AI-guided echo
Diagnosis / Prognosis - Standard echo

Experimental: Screening/Management Plan - AI-guided echo acquisition performed using a desktop echo machine (uSmart 3300, Terason, Burlington, MA) with AI software (Caption Health, Brisbane, CA) obtained by a non-expert (eg. clinic nurse, registrar general practitioner or physician) at the remote clinic, usually on the day of clinic review. Images will then be uploaded onto a secure cloud and downloaded at the core lab for measurement, interpretation and reporting.

Active comparator: Usual care - Standard echo acquisition by a sonographer either at a referral hospital, or by a visiting team - usually necessitating a delay. Measurement, interpretation and reporting will happen as usual.


Diagnosis / Prognosis: AI-guided echo
AI-guided echocardiography

Diagnosis / Prognosis: Standard echo
Standard echocardiography
Intervention code [1] 0 0
Diagnosis / Prognosis
Comparator / control treatment
Control group

Outcomes
Primary outcome [1] 0 0
Diagnosis of cardiac dysfunction or heart valve disease
Timepoint [1] 0 0
12 months

Eligibility
Key inclusion criteria
* Age >45 years
* eligible for Medicare
* exercise intolerance or cardiovascular (CV) risk factors
Minimum age
45 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
* Known HF or HVD
* situations where cardio-protection is already indicated (eg. known CAD)
* comorbid conditions with life expectancy <2 years
* inability to provide written informed consent

Study design
Purpose of the study
Diagnosis
Allocation to intervention
Randomised controlled trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Masking / blinding
Blinded (masking used)
Who is / are masked / blinded?


The people assessing the outcomes
Intervention assignment
Parallel
Other design features
Phase
Not applicable
Type of endpoint/s
Statistical methods / analysis

Recruitment
Recruitment status
Recruiting
Data analysis
Reason for early stopping/withdrawal
Other reasons
Date of first participant enrolment
Anticipated
Actual
24/02/2023
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
30/12/2025
Actual
Sample size
Target
612
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
NT
Recruitment hospital [1] 0 0
Alice Springs Hospital - Alice Springs
Recruitment postcode(s) [1] 0 0
- Alice Springs

Funding & Sponsors
Primary sponsor type
Other
Name
Baker Heart and Diabetes Institute
Address
Country
Other collaborator category [1] 0 0
Other
Name [1] 0 0
Alice Springs Hospital
Address [1] 0 0
Country [1] 0 0
Other collaborator category [2] 0 0
Other
Name [2] 0 0
Princess Alexandra Hospital, Brisbane, Australia
Address [2] 0 0
Country [2] 0 0
Other collaborator category [3] 0 0
Other
Name [3] 0 0
Royal Perth Hospital
Address [3] 0 0
Country [3] 0 0
Other collaborator category [4] 0 0
Other
Name [4] 0 0
Ochre Health
Address [4] 0 0
Country [4] 0 0
Other collaborator category [5] 0 0
Other
Name [5] 0 0
Walgett Aboriginal Medical Services
Address [5] 0 0
Country [5] 0 0
Other collaborator category [6] 0 0
Other
Name [6] 0 0
Merriden Health Service
Address [6] 0 0
Country [6] 0 0
Other collaborator category [7] 0 0
Government body
Name [7] 0 0
Royal Hobart Hospital
Address [7] 0 0
Country [7] 0 0

Ethics approval
Ethics application status

Summary
Brief summary
Heart Failure and valvular heart disease are disproportionate problems in rural and remote Australia (RRA). Echocardiography is the best imaging investigation, and essential for management, but access to this essential test shows huge geographic variations, primarily because of dependence on expert acquisition. This trial seeks to demonstrate the effectiveness of artificial intelligence-based echocardiography for triage and management of patients with known or suspected heart disease in RRA.
Trial website
https://clinicaltrials.gov/study/NCT05558605
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 0 0
Tom Marwick, MBBS, PhD
Address 0 0
Baker Heart and Diabetes Institute
Country 0 0
Phone 0 0
Fax 0 0
Email 0 0
Contact person for public queries
Name 0 0
Tom Marwick, MBBS, PhD
Address 0 0
Country 0 0
Phone 0 0
+61385321550
Fax 0 0
Email 0 0
[email protected]
Contact person for scientific queries



Summary Results

For IPD and results data, please see https://clinicaltrials.gov/study/NCT05558605