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A Multi-Center Study of Detection of Low Ventricular Ejection Fraction

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 evaluated by the U.S. Federal Government. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04963218
Recruitment Status : Completed
First Posted : July 15, 2021
Last Update Posted : July 13, 2022
Sponsor:
Collaborator:
Anumana, Inc.
Information provided by (Responsible Party):
Peter A. Noseworthy, M.D., Mayo Clinic

Brief Summary:
This is a multi-site, retrospective study to evaluate the performance of a locked AI-based algorithm for detection of left ventricular systolic dysfunction. A prerequisite for inclusion of subjects from each institution will be the availability of at least one digital 12-lead ECG paired with an echocardiogram with LVEF information within 30 days of the date of the ECG. The AI-ECG LVSD algorithm will be applied on all ECGs and diagnostic performance features for the detection of LVSD will be estimated using the provided paired LVEF value (Low LVEF as the reference label). Performance will also be assessed in subgroups of subjects determined by demographic and clinical factors.

Condition or disease Intervention/treatment
Cardiac Disease Diagnostic Test: AI Algorithm to detect LVEF in ECG

Detailed Description:

Following institutional review board approval, 12,000 12-lead ECG's paired with an echocardiogram with LVEF information within 30 days of the date of the ECG will be collected across three enrolled sites. Each site will provide data from up to 4000 enrolled subjects that meet the inclusion criteria. No other demographic characteristics or enrichment will be considered in the selection of subjects in order to best represent the general population for that site. Sites will securely transfer the data to a centralized repository for processing.

Once data is collected, the device will be used to analyze the ECG data for all enrolled subjects without reference or access to the echocardiogram data. The device will display a binary 36 prediction of the likelihood of LVEF less than or equal to 40%. Results will be compared to the echocardiogram reference standard in accordance with the statistical analysis plan.

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Study Type : Observational
Actual Enrollment : 16000 participants
Observational Model: Cohort
Time Perspective: Retrospective
Official Title: A Multicenter Study of Detection of Low Ventricular Ejection Fraction (LVEF) ≤ 40% Based on Point-of-Care 12- Lead ECG Data
Actual Study Start Date : August 30, 2021
Actual Primary Completion Date : April 13, 2022
Actual Study Completion Date : April 13, 2022

Intervention Details:
  • Diagnostic Test: AI Algorithm to detect LVEF in ECG
    A clinical decision support software as a medical device that detects whether a patient has LVEF less than or equal to 40% based upon the input of one or more ECG vectors at the point-of-care.


Primary Outcome Measures :
  1. Established Diagnostic Performance [ Time Frame: 1 month ]
    Number of participants with presence of EF less than of equal to 40% identified by 12-lead AI ECG algorithm



Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years to 99 Years   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Probability Sample
Study Population
Adult subjects with or without known cardiac disease who are either inpatients or outpatients with ECGs and an echocardiogram within 30-days of the ECG date.
Criteria

Inclusion Criteria:

- Adult subjects with or without known cardiac disease who are either inpatients or outpatients with ECGs and an echocardiogram within 30-days of the ECG date.

Exclusion Criteria:

  • No research authorization provided
  • An ECG signal shorter than 10 seconds or that is not interpretable
  • An echocardiogram is considered technically challenging
  • Only qualitative interpretation of left ventricular systolic function available (i.e., "decreased EF") without a numerical value.
  • A paced rhythm

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04963218


Locations
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United States, Massachusetts
Beth Israel Deacon Medical Center
Boston, Massachusetts, United States, 02215
United States, New York
Montefiore Medical Center
Bronx, New York, United States, 10467
United States, South Dakota
Monument Health
Rapid City, South Dakota, United States, 57701
United States, Utah
University of Utah
Salt Lake City, Utah, United States, 84132
Sponsors and Collaborators
Mayo Clinic
Anumana, Inc.
Investigators
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Principal Investigator: Peter Noseworthy, MD Mayo Clinic
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Responsible Party: Peter A. Noseworthy, M.D., Professor of Medicine, Mayo Clinic
ClinicalTrials.gov Identifier: NCT04963218    
Other Study ID Numbers: 21-003530
First Posted: July 15, 2021    Key Record Dates
Last Update Posted: July 13, 2022
Last Verified: July 2022
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Additional relevant MeSH terms:
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Heart Diseases
Cardiovascular Diseases