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

NCT04963218 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 16000

Last updated 2022-07-13

No results posted yet for this study

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.

Conditions

  • Cardiac Disease

Interventions

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.

Sponsors & Collaborators

  • Anumana, Inc.

    collaborator INDUSTRY

  • Mayo Clinic

    lead OTHER

Principal Investigators

  • Peter Noseworthy, MD · Mayo Clinic

Eligibility

Min Age
18 Years
Max Age
99 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-08-30
Primary Completion
2022-04-13
Completion
2022-04-13

Countries

  • United States

Study Locations

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04963218 on ClinicalTrials.gov