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OpenTrials
Completed

NCT Number: NCT05317286

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

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.

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Key information

Conditions

Acute Coronary Syndrome Cardiovascular Diseases Heart Diseases Left Ventricular Dysfunction Myocardial Ischemia Vascular Diseases Ventricular Dysfunction Ventricular Dysfunction, Left

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Robert Avram

Montreal, Quebec, H1T1C8, Canada

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Informed consent signed by the participant
  • Acute coronary syndrome
  • Creatinine clearance ≥30 ml/min/m2 according to MDRD

Exclusion criteria

  • Creatinine clearance <30 ml/min/m2 according to MDRD
  • No indication to perform TTE in the 7 days following coronary angiogram
  • Right bundle branch block
  • Suspected or confirmed left ventricular thrombus
  • Suspected or confirmed aortic dissection
  • Ventriculography not feasible
  • No left coronary system angiogram

Treatment and study plan

Primary outcomes

  1. Area under the curve-Receiver Operating Characteristics (AUC-ROC) of the CathEF algorithm for differentiating a LVEF ≤ or >50%, compared to TTE-LVEF

    Time frame: Either 7 days before or up to 7 days after the coronary angiogram

Secondary outcomes

  1. Comparing AUC-ROC of CathEF and ventriculography for differentiating a LVEF ≤ or >50%

    Time frame: Either 7 days before or up to 7 days after the coronary angiogram

  2. Sensitivity of CathEF and ventriculography for differentiating a LVEF ≤ or >50% in comparison to TTE-LVEF.

    Time frame: Either 7 days before or up to 7 days after the coronary angiogram

  3. Specificity of CathEF and ventriculography for differentiating a LVEF ≤ or >50% in comparison to TTE-LVEF.

    Time frame: Either 7 days before or up to 7 days after the coronary angiogram

  4. Number of participants with major adverse cardiovascular events (Combined outcome of combined outcomeof mortality, ventricular arrhythmia requiring an intervention, heart failure, need for inotropic support, renal failure KDIGO≥2 and stroke)

    Time frame: At 7 days or before discharge, if earlier.

  5. AUC-ROC of the re-trained CathEF algorthim for differentiating a LEVF ≤ or >50%

    Time frame: Either 7 days before or up to 7 days after the coronary angiogram

  6. Sensitivity of the re-trained CathEF algorthim for differentiating a LEVF ≤ or >50%

    Time frame: Either 7 days before or up to 7 days after the coronary angiogram

  7. Specificity of the re-trained CathEF algorthim for differentiating a LEVF ≤ or >50%

    Time frame: Either 7 days before or up to 7 days after the coronary angiogram

  8. Likert scale on the impact on the procedure, ease of use and utility of the CathEF algorithm in the clinical practice, as assessed by interventional cardiologists

    Time frame: Through study completion, an average of 1 year.

Sponsors and collaborators

Lead sponsor

Montreal Heart Institute

Other

Collaborators

  • Ottawa Heart Institute Research Corporation

Registry information

Official study title

Prospective Validation of a Deep Learning Algorithm for Prediction of the Left Ventricular Ejection Fraction From Coronary Angiogram Videos in Patients With Acute Coronary Syndrome

Acronym: CathEF

Important dates

Study start
2022
Primary completion
2023
Study completion
2024
First posted
Apr 7, 2022
Registry last updated
Mar 12, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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