Multidisciplinary Screening for Heart Failure

(MAPLE-CHF Trial)

Recruiting at 2 trial locations

Overseen By Jennifer Petterson

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Cardiology Research UBC

Disqualifiers: Heart failure, Renal replacement, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 28

1360 Participants Needed

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. ^{1 2 3 4 5}

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. ^{4 6 7 8 9}

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. ^{1 4 10 11 12}

Who Is on the Research Team?

Nathaniel M Hawkins, MD

Principal Investigator

Associate Professor of Medicine, UBC Division of Cardiology

Anique Ducharme, MD

Principal Investigator

Professor of Medicine, Univeriste de Montreal, Montreal Heart Institute

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.

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.

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?

Group I: Investigational arm guided by NT-proBNP result Active Control 4 Interventions

NT-proBNP drawn and if level elevated (\>125 pg/ml) a study visit with artificial intelligence (AI) echocardiogram, electrocardiogram (ECG), and heart failure (HF) focused examination conducted

Group II: Routine care arm Active Control 1 Intervention

Participants will be remotely monitored for number of heart failure events

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

Approved in Canada as AI Echocardiogram for:

• Heart Failure Diagnosis
• Cardiac Function Assessment

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.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

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.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

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.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

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]

In a study of 108,330 heart failure patients, NT-proBNP levels were found to reliably predict clinical outcomes, supporting its use as a surrogate marker in heart failure trials.

The analysis showed that early NT-proBNP measurements can effectively forecast hazard ratios for clinical events, allowing for shorter and smaller heart failure trials without compromising reliability.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

NT-proBNP Qualifies as a Surrogate for Clinical End Points in Heart Failure. Schmitt, W., Rühs, H., Burghaus, R., et al.[2021]

In a study of 245 heart failure patients, those with atrial fibrillation (AF) had significantly higher levels of N-terminal pro brain natriuretic peptide (NT-proBNP) compared to those with sinus rhythm, indicating a potential biomarker for worse outcomes.

NT-proBNP was found to be an independent predictor of death in patients with AF, suggesting that monitoring NT-proBNP levels could be crucial for assessing prognosis in these patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Effect of atrial fibrillation on plasma NT-proBNP in chronic heart failure. Corell, P., Gustafsson, F., Kistorp, C., et al.[2007]

In a blinded, randomized trial involving 3,769 echocardiographic studies, AI assessment of left ventricular ejection fraction (LVEF) was found to be non-inferior to sonographer assessments, with a significantly lower rate of substantial changes in LVEF (16.8% for AI vs. 27.2% for sonographers).

The AI-guided workflow not only matched the accuracy of sonographer assessments but also saved time for both sonographers and cardiologists, indicating that AI can effectively streamline the echocardiography interpretation process.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Blinded, randomized trial of sonographer versus AI cardiac function assessment. He, B., Kwan, AC., Cho, JH., et al.[2023]

A study involving 44,959 patients demonstrated that an AI model applied to ECG data can effectively identify asymptomatic left ventricular dysfunction (ALVD), achieving high accuracy (85.7%) and sensitivity (86.3%).

Patients who screened positive for ALVD using the AI model were found to be four times more likely to develop future ventricular dysfunction, highlighting the potential of AI-enhanced ECG as a proactive screening tool for early intervention.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram. Attia, ZI., Kapa, S., Lopez-Jimenez, F., et al.[2022]

A study involving 221,846 ECGs from four institutions aimed to develop AI models for detecting left ventricular systolic dysfunction (LVSD) with an ejection fraction (EF) <40%, showing promising internal accuracy but variable external validation results.

The performance of AI models varied significantly between institutions, emphasizing the need for external validation and careful consideration of patient characteristics and ECG abnormalities when using AI for LVSD detection.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Importance of external validation and subgroup analysis of artificial intelligence in the detection of low ejection fraction from electrocardiograms. Yagi, R., Goto, S., Katsumata, Y., et al.[2023]

The study compared three NT-proBNP immunoassays for diagnosing heart failure using 160 patient samples, finding that all assays had acceptable analytical performance and good agreement.

Among the assays, the Elecsys proBNP II demonstrated higher specificity and a better positive likelihood ratio for diagnosing heart failure, suggesting it may be the most effective option for clinicians.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluation of Analytical Performances and Comparison of 3 NT-proBNP Assays for Diagnosing Heart Failure. Cho, J., Lee, JH., Lee, SG.[2023]

Echocardiography combined with B-type natriuretic peptides (BNPs) significantly enhances the assessment of cardiac function and can improve the diagnosis and management of cardiovascular diseases.

Using amino-terminal pro-B-type natriuretic peptide (NT-proBNP) alongside echocardiography helps identify asymptomatic left ventricular dysfunction and stratifies risk in heart failure patients, guiding timely interventions for those at greatest risk.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

B-type natriuretic peptides and echocardiographic measures of cardiac structure and function. Troughton, RW., Richards, AM.[2016]

In a study of 254 patients undergoing cardiac catheterization, plasma brain natriuretic peptide was found to be the most effective marker for identifying left ventricular impairment, significantly predicting increased left ventricular end diastolic pressure and decreased ejection fraction.

While brain natriuretic peptide showed better diagnostic accuracy compared to atrial natriuretic factor and N-terminal pro-atrial natriuretic factor, the overall effectiveness of these natriuretic peptides in diagnosing left ventricular dysfunction in patients with coronary heart disease was still considered modest.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Plasma cardiac natriuretic peptide determination as a screening test for the detection of patients with mild left ventricular impairment. Omland, T., Aakvaag, A., Vik-Mo, H.[2019]

Cardiac natriuretic peptides, BNP and NT-proBNP, are effective for screening left ventricular systolic dysfunction in patients with heart failure symptoms, particularly in those under 75 years old, where they show high sensitivity and negative predictive values.

These peptides also serve as important prognostic markers for mortality and cardiovascular hospitalization, and can be useful in monitoring heart failure patients over time.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[Natriuretic peptides as cardiac markers in clinical practice]. Veien, KT., Jensen, JK., Hildebrandt, P., et al.[2015]

Citations

1. Switzerland pubmed.ncbi.nlm.nih.gov

Artificial Intelligence-Enabled Electrocardiography Detects B-Type Natriuretic Peptide and N-Terminal Pro-Brain Natriuretic Peptide. [2023]

2. United States pubmed.ncbi.nlm.nih.gov

Artificial intelligence enabled ECG screening for left ventricular systolic dysfunction: a systematic review. [2023]

3. United States pubmed.ncbi.nlm.nih.gov

N-terminal pro-B-type natriuretic peptide-guided therapy in patients hospitalized for acute heart failure. [2017]

4. United States pubmed.ncbi.nlm.nih.gov

NT-proBNP Qualifies as a Surrogate for Clinical End Points in Heart Failure. [2021]

5. Netherlands pubmed.ncbi.nlm.nih.gov

Effect of atrial fibrillation on plasma NT-proBNP in chronic heart failure. [2007]

6. England pubmed.ncbi.nlm.nih.gov

Blinded, randomized trial of sonographer versus AI cardiac function assessment. [2023]

7. United States pubmed.ncbi.nlm.nih.gov

Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram. [2022]

8. England pubmed.ncbi.nlm.nih.gov

Importance of external validation and subgroup analysis of artificial intelligence in the detection of low ejection fraction from electrocardiograms. [2023]

9. United States pubmed.ncbi.nlm.nih.gov

Evaluation of Analytical Performances and Comparison of 3 NT-proBNP Assays for Diagnosing Heart Failure. [2023]

10. United States pubmed.ncbi.nlm.nih.gov

B-type natriuretic peptides and echocardiographic measures of cardiac structure and function. [2016]

11. England pubmed.ncbi.nlm.nih.gov

Plasma cardiac natriuretic peptide determination as a screening test for the detection of patients with mild left ventricular impairment. [2019]

12. Denmark pubmed.ncbi.nlm.nih.gov

[Natriuretic peptides as cardiac markers in clinical practice]. [2015]