1360 Participants Needed

Multidisciplinary Screening for Heart Failure

(MAPLE-CHF Trial)

Recruiting at 2 trial locations
NU
JP
Overseen ByJennifer Petterson
Age: 18+
Sex: Any
Trial Phase: Academic
Sponsor: Cardiology Research UBC
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial uses a computer program to identify potential heart failure patients from medical records, followed by blood tests and AI heart imaging. It targets patients at risk of heart failure to catch the condition early. The process involves scanning records, testing blood for a specific marker, and using AI for detailed heart images if needed.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It is best to discuss this with the trial coordinators or your doctor.

Is the AI-enabled electrocardiogram safe for use in humans?

The AI-enabled electrocardiogram (ECG) has been tested in various studies and is generally considered safe for use in humans. It has been used to accurately predict heart-related conditions and improve screening for heart dysfunction without reported safety concerns.12345

How is the multidisciplinary screening for heart failure treatment different from other treatments?

This treatment is unique because it combines artificial intelligence with traditional heart tests like echocardiograms and electrocardiograms to improve the detection of heart problems. The AI-enhanced approach can identify heart issues earlier and more accurately, especially in non-cardiology settings, and when combined with natriuretic peptide testing, it offers a more comprehensive screening for heart failure.46789

What data supports the effectiveness of the treatment AI echocardiogram, Artificial Intelligence Echocardiogram, AI Echocardiogram, Electrocardiogram, ECG, 12-lead electrocardiogram, NT-proBNP, N-terminal pro-brain natriuretic peptide, N-terminal prohormone of B-type natriuretic peptide for heart failure?

Research shows that AI-enabled electrocardiograms (ECGs) can accurately predict levels of BNP and NT-proBNP, which are important markers for heart health, and may help monitor cardiovascular disease risk. Additionally, AI ECGs have been effective in detecting heart function issues, like left ventricular systolic dysfunction, which is related to heart failure.14101112

Who Is on the Research Team?

NM

Nathaniel M Hawkins, MD

Principal Investigator

Associate Professor of Medicine, UBC Division of Cardiology

AD

Anique Ducharme, MD

Principal Investigator

Professor of Medicine, Univeriste de Montreal, Montreal Heart Institute

SL

Serge LePage, MD

Principal Investigator

Centre Hospitalier Universite de Sherbrooke-Hopital Fleurimont

Are You a Good Fit for This Trial?

This trial is for adults over 40 with risk factors like coronary artery disease, diabetes, atrial fibrillation, stroke history, regular diuretic use, COPD, peripheral artery disease or chronic kidney disease. It's not for those who can't consent, already have heart failure diagnosis or are on renal replacement therapy.

Inclusion Criteria

I have COPD confirmed by tests, a doctor, or I'm on COPD treatment.
I have been using water pills regularly for over a month in the past year.
I have two or more risk factors for heart failure.
See 8 more

Exclusion Criteria

I am on dialysis.
I am able to understand and agree to the study's procedures and risks.
I have been diagnosed with heart failure before.
See 1 more

Timeline for a Trial Participant

Pre-screening

Pre-screening using extracted primary care electronic health records with a case finding algorithm

2 weeks

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Participants in the intervention arm undergo NT-proBNP testing, and if elevated, receive an AI echocardiogram and ECG

6 months
Study visit within 28 days of NT-proBNP result for elevated cases

Routine Care

Participants in the routine care arm are monitored for heart failure events

6 months

Follow-up

Participants are monitored for safety and effectiveness after treatment

6 months

What Are the Treatments Tested in This Trial?

Interventions

  • AI echocardiogram
  • Electrocardiogram
  • NT-proBNP
Trial Overview The study tests if a special algorithm to find heart failure signs in electronic health records plus additional screening (NT-proBNP blood test and AI echocardiogram) can detect heart failure earlier compared to usual care methods.
How Is the Trial Designed?
2Treatment groups
Active Control
Group I: Investigational arm guided by NT-proBNP resultActive Control4 Interventions
Group II: Routine care armActive Control1 Intervention

AI echocardiogram is already approved in Canada for the following indications:

🇨🇦
Approved in Canada as AI Echocardiogram for:

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Who Is Running the Clinical Trial?

Cardiology Research UBC

Lead Sponsor

Trials
16
Recruited
7,100+

Centre for Cardiovascular Innovation

Collaborator

Trials
1
Recruited
1,400+

NHS Greater Glasgow & Clyde

Collaborator

Trials
1
Recruited
1,400+

Montreal Heart Institute

Collaborator

Trials
125
Recruited
85,400+

AstraZeneca

Industry Sponsor

Trials
4,491
Recruited
290,540,000+

Sir Pascal Soriot

AstraZeneca

Chief Executive Officer since 2012

Veterinary Medicine from École nationale vétérinaire d'Alfort, MBA from HEC Paris

Dr. Cristian Massacesi

AstraZeneca

Chief Medical Officer since 2021

MD from Marche Polytechnic University, Oncology training at Royal Marsden Hospital, Kaplan Comprehensive Cancer Center, and European Institute of Oncology

Pascal Soriot

AstraZeneca

Chief Executive Officer since 2012

Veterinary Medicine from École nationale vétérinaire d'Alfort, MBA from HEC Paris

Cristian Massacesi

AstraZeneca

Chief Medical Officer since 2021

MD from Marche Polytechnic University, Medical Oncology training at Royal Marsden Hospital, Kaplan Comprehensive Cancer Center, and European Institute of Oncology

Canadian Heart Function Alliance

Collaborator

Trials
2
Recruited
1,400+

HeartLife Foundation

Collaborator

Trials
1
Recruited
1,400+

Published Research Related to This Trial

The AI-enabled electrocardiogram (ECG) system can accurately predict levels of B-type natriuretic peptide (BNP) and N-terminal pro-brain natriuretic peptide (pBNP) using deep learning models, with high accuracy in distinguishing between mild and severe abnormalities.
ECG-pBNP was found to be a better predictor of all-cause mortality compared to ECG-BNP, suggesting it may be more effective for monitoring cardiovascular disease risk in patients.
Artificial Intelligence-Enabled Electrocardiography Detects B-Type Natriuretic Peptide and N-Terminal Pro-Brain Natriuretic Peptide.Liu, PY., Lin, C., Lin, CS., et al.[2023]
Artificial intelligence-enabled electrocardiography (AIeECG) shows high diagnostic accuracy for detecting left ventricular systolic dysfunction (LVSD), with a median area under the curve (AUC) of 0.90, sensitivity of 83.3%, and specificity of 87% across various populations.
AIeECG can be particularly beneficial in non-cardiology settings and when used alongside natriuretic peptide testing, but further prospective randomized trials are needed to assess its impact on treatment outcomes and cost-effectiveness.
Artificial intelligence enabled ECG screening for left ventricular systolic dysfunction: a systematic review.Bjerkén, LV., Rønborg, SN., Jensen, MT., et al.[2023]
In a study of 271 patients with acute heart failure, NT-proBNP-guided therapy, which involved intensifying treatment based on NT-proBNP levels, did not significantly improve outcomes compared to standard care.
However, a decrease in NT-proBNP levels from predischarge to discharge was found to be an independent predictor of better outcomes, indicating that monitoring NT-proBNP could still be valuable in assessing patient prognosis.
N-terminal pro-B-type natriuretic peptide-guided therapy in patients hospitalized for acute heart failure.Carubelli, V., Lombardi, C., Lazzarini, V., et al.[2017]

Citations

Artificial Intelligence-Enabled Electrocardiography Detects B-Type Natriuretic Peptide and N-Terminal Pro-Brain Natriuretic Peptide. [2023]
Artificial intelligence enabled ECG screening for left ventricular systolic dysfunction: a systematic review. [2023]
N-terminal pro-B-type natriuretic peptide-guided therapy in patients hospitalized for acute heart failure. [2017]
NT-proBNP Qualifies as a Surrogate for Clinical End Points in Heart Failure. [2021]
Effect of atrial fibrillation on plasma NT-proBNP in chronic heart failure. [2007]
Blinded, randomized trial of sonographer versus AI cardiac function assessment. [2023]
Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram. [2022]
Importance of external validation and subgroup analysis of artificial intelligence in the detection of low ejection fraction from electrocardiograms. [2023]
Evaluation of Analytical Performances and Comparison of 3 NT-proBNP Assays for Diagnosing Heart Failure. [2023]
10.United Statespubmed.ncbi.nlm.nih.gov
B-type natriuretic peptides and echocardiographic measures of cardiac structure and function. [2016]
Plasma cardiac natriuretic peptide determination as a screening test for the detection of patients with mild left ventricular impairment. [2019]
[Natriuretic peptides as cardiac markers in clinical practice]. [2015]
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