Point of Care Artificial Intelligence Tool for Heart Failure Diagnosis

Heart Failure Clinical Trial

— DUO-EF-19  

Official title:

Diagnosis of Heart Failure in the Post-COVID-19 Clinic, Primary Care and Hospital Setting Using a Digital Stethoscope With Artificial Intelligence (AI) Electrocardiogram (ECG)

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04601415
• Other study ID #: 285417
• Status: Completed
• Start date: February 6, 2021
• Est. completion date: May 27, 2021

Study information

• Verified date: October 2023
• Source: Imperial College London
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Abbreviations/acronyms:

DUO-EF = prediction of ejection fraction (EF) using the Eko-DUO digital stethoscope algorithm HF = heart failure HFrEF = heart failure with reduced ejection fraction COVID-19 = coronavirus disease 2019 Eko DUO = digital stethoscope device cMRI = cardiac magnetic resonance imaging ECG = electrocardiogram

Prospective observational study of left ventricular ejection fraction predicted by application of artificial intelligence to single-lead ECG acquired by a digital stethoscope; in the post-covid-19 follow up clinic, in patients presenting with heart failure symptoms in primary care, and in patients attending for echocardiography and cardiac MRI.

Description:

Abbreviations/acronyms:

DUO-EF = prediction of ejection fraction (EF) using the Eko-DUO digital stethoscope algorithm HF = heart failure HFrEF = heart failure with reduced ejection fraction COVID-19 = coronavirus disease 2019 Eko DUO = digital stethoscope device cMRI = cardiac magnetic resonance imaging ECG = electrocardiogram

AIMS

To demonstrate DUO-EF can identify heart failure (HF) with reduced ejection fraction (HFrEF) post-COVID-19 where diagnosis would otherwise be missed/delayed To demonstrate DUO-EF can reliably and accurately diagnose new HFrEF in the primary care setting To further validate DUO-EF diagnostic performance at-scale against gold-standard investigations (echocardiography and cardia MRI) To measure if DUO-EF suggestive of HFrEF but with normal gold standard investigations predicts future risk of developing HFrEF

Methods To demonstrate DUO-EF can identify heart failure (HF) with reduced ejection fraction (HFrEF) post-COVID-19 where diagnosis would otherwise be missed/delayed To demonstrate DUO-EF can reliably and accurately diagnose new HFrEF in the primary care setting To further validate DUO-EF diagnostic performance at-scale against gold-standard investigations (echocardiography and cardiac magnetic resonance imaging - cMRI) To measure if DUO-EF suggestive of HFrEF but with normal gold standard investigations predicts future risk of developing HFrEF

DUO-EF prediction of ejection fraction in patients attending COVID-19 follow up clinic and comparison with:

subsequent DUO-EF at time of gold-standard investigation for HF ejection fraction as calculated by gold-standard investigation

DUO-EF prediction of ejection fraction in patients where their GP suspects new heart failure and comparison with:

subsequent DUO-EF at time of gold-standard investigation ejection fraction as calculated by gold-standard investigation DUO-EF prediction of ejection fraction in unselected patients attending for echocardiography or cardiac MRI, comparing DUO-EF predicted with gold-standard calculated ejection fraction Telephone call follow-up at 24 months for all patients with DUO-EF suggestive of HFrEF but normal gold standard investigations

OUTCOME MEASURES Area under curve (AUC) of DUO-EF calibrated for detection of EF below 40%; classification accuracy Positive predictive value of DUO-EF in COVID-19 clinic and GP context based on subsequent gold-standard estimation of EF; negative predictive value of DUO-EF in COVID-19 follow up cohort; positive predictive value of DUO-EF at 24 months in those with negative gold standard investigations Qualitative measurement of patient and clinical end user acceptability of Eko DUO

POPULATION Group 1: Patients seen in the COVID-19 follow-up clinic (n = 400) Group 2:

Patients seen in primary care with symptoms newly suggestive of heart failure (n = 400) Group 3: All-comers to echocardiography departments across Imperial College Healthcare NHS Trust (n = 1,500) Group 4: patients undergoing cardiac MRI investigation (n = 100)

Recruitment information / eligibility

• Status: Completed
• Enrollment: 1050
• Est. completion date: May 27, 2021
• Est. primary completion date: May 27, 2021
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Attendance at GP with ?HF symptoms

• Referral from GP or elsewhere for echocardiogram in hospital

• Age >18

Exclusion Criteria:

• Unable to give informed consent

Related Conditions & MeSH terms

• Heart Failure

Intervention

Diagnostic Test:
• ECG from handheld device
Acquisition of a single-lead ECG at time of presentation to GP and at echo appointment

Locations

Country	Name	City	State
United Kingdom	Patrik Bachtiger	London	Non-US/Non-Canadian

Sponsors (1)

Lead Sponsor	Collaborator
Imperial College London

Country where clinical trial is conducted

United Kingdom, 

References & Publications (1)

Attia ZI, Noseworthy PA, Lopez-Jimenez F, Asirvatham SJ, Deshmukh AJ, Gersh BJ, Carter RE, Yao X, Rabinstein AA, Erickson BJ, Kapa S, Friedman PA. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction. Lancet. 2019 Sep 7;394(10201):861-867. doi: 10.1016/S0140-6736(19)31721-0. Epub 2019 Aug 1. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Area under receiver operating curve	Area under curve (AUC) where maximum value is '1', describing ability of algorithm to discriminate low from not-low ejection fraction	up to 18 months