CompletedNot Applicable

A Study to Detect Advanced Liver Disease Via AI-enabled Electrocardiogram

United States279 participantsStarted 2023-04-18

Plain-language summary

The overall objectives of this study are to determine the effectiveness of ACE 2.0 model in early detection of advanced liver fibrosis, and to determine the acceptance and barriers for use of an AI-enabled algorithm for prediction of liver disease in primary care.

Who can participate

Age range18 Years

SexALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Criteria: Inclusion Criteria: * Primary care clinicians (physicians, nurse practitioners, and physician assistants). * Part of a team that cares for adult patients (≥18 years). * Have the ability to order ECG. * Consent will be obtained from primary care clinicians. * Patients' data will be collected from electronic medical records (EMR). * Adult patients (≥ 18 years) undergoing an ECG for any indication over a period of 6 months will be included. Exclusion Criteria: * Patients with known cirrhosis based on noninvasive fibrosis assessment tests, liver biopsy or complications of decompensated disease, or with a documented history of cirrhosis identified by clinical notes.

What they're measuring

The primary objective of this pragmatic trial is to validate a deep learning-based artificial intelligence (AI) model for early detection of cirrhosis-associated signals on digitized ECG.

Timeframe: 6 months

Trial details

NCT IDNCT05782283

SponsorMayo Clinic

Sponsor typeOTHER

Study typeINTERVENTIONAL

Primary completion2025-09-01

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