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LVEF Prediction During ACS Using AI Algorithm Applied on Coronary Angiogram Videos

NCT05317286 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 240

Last updated 2024-03-12

No results posted yet for this study

Summary

Left ventricular ejection fraction (LVEF) is one of the strongest predictors of mortality and morbidity in patients with acute coronary syndrome (ACS). Transthoracic echocardiography (TTE) remains the gold standard for LVEF measurement. Currently, LVEF can be estimated at the time of the coronary angiogram but requires a ventriculography. This latter is performed at the price of an increased amount of contrast media injected and puts the patients at risk for mechanical complications, ventricular arrhythmia or atrio-ventricular blocks. Artificial intelligence (AI) has previously been shown to be an accurate method for determining LVEF using different data sources. Fur the purpose of this study, we aim at validating prospectively an AI algorithm, called CathEF, for the prediction of real-time LVEF (AI-LVEF) compared to TTE-LVEF and ventriculography in patients undergoing coronary angiogram for ACS.

Conditions

  • Acute Coronary Syndrome
  • Left Ventricular Dysfunction

Sponsors & Collaborators

  • Ottawa Heart Institute Research Corporation

    collaborator OTHER

  • Montreal Heart Institute

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-06-01
Primary Completion
2023-12-31
Completion
2024-02-29

Countries

  • Canada

Study Locations

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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 NCT05317286 on ClinicalTrials.gov