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NCT06580158Recruiting

AI in Outpatient Practice for Diagnosing Aortic Stenosis and Diastolic Dysfunction

Mayo Clinic

Start Date

11/8/2024

Completion Date

3/1/2027

Summary

Two recently developed artificial intelligence-enabled electrocardiogram (AI-ECG) models have been developed to detect aortic stenosis (AS) and diastolic dysfunction (DD). AI-ECG for AS has a sensitivity of 78% and specificity of 74%, and AI-ECG for DD has a sensitivity of 83% and specificity of 80%. However, these models have never been prospectively applied to diagnose AS or DD, which may be useful for patients and providers from a diagnostic and prognostic perspective and especially in settings where access to higher- level medical care is limited. In this study, we aim to determine the clinical utility of these AI-ECG models by prospectively applying them to an outpatient cohort and then completing a focused point-of-care ultrasound to evaluate those who are AI-ECG positive for AS and DD.

Eligibility Criteria

Age Range: 60 years to No maximum

Inclusion Criteria: * ≥ 60 years of age must have a clinical scheduled ECG performed. Exclusion Criteria: * \< 59 years of age * Is not scheduled for a clinical ECG * Unable to provide consent.

Interventions

DEVICE

AI-ECG Dashboard

DIAGNOSTIC_TEST

Point of care ultrasound (POCUS)

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Conditions

Aortic StenosisDiastolic Dysfunction

Locations

Mayo Clinic

Rochester, Minnesota 55905

United States