Skip to main content
OpenTrials
Completed

NCT Number: NCT05782283

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

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.

Completed

Looking for future studies?

Notify Me

Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Mayo Clinic Minnesota

Rochester, Minnesota, 55905, United States

About this study

A pragmatic, cluster randomized trial in 45 Mayo Clinic primary care practices will be conducted over a period of 6 months with 6 months of follow up. Care teams will be randomized 1:1 to intervention or usual care, stratified by region and patient volume. In the intervention arm, the DULCE score will be used to alert consenting providers to the likelihood of advanced liver disease with a recommendation for a FibroTest-ActiTest. The primary endpoint will be detection of advanced liver disease. Secondary outcomes will include completion of noninvasive fibrosis assessment tests and hepatology referral within 180 days of ECG, new diagnosis of liver disease stratified by etiology (nonalcoholic fatty liver disease, alcohol-associated liver disease, hepatitis C, and others) and severity (compensated with and without clinically-significant portal hypertension, and decompensated disease), initiation of prophylactic nonselective beta-blockers and imaging for hepatocellular carcinoma surveillance, according to published society guidelines. Post-study surveys to participating clinicians will be applied.

Who can participate

Healthy volunteers accepted: No

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

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.

Treatment and study plan

ACE (AI-Cirrhosis-ECG) 2.0

Device

An electrocardiogram (ECG) based artificial intelligence (AI) powered tool for detection of undiagnosed cirrhosis in primary care practices. And email alert is sent to providers which will display whether the ACE 2.0 result is positive or negative for the likelihood of advanced liver disease.

Primary outcomes

  1. 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.

    Time frame: 6 months

    Number of participants with new diagnosis of advanced liver disease as assessed by a novel electrocardiogram-enabled convoluted neural network (CNN) compared to standard of care at 6 months.

Secondary outcomes

  1. The secondary objective is to assess barriers for adoption of an AI-enabled algorithm for detection of liver disease in routine community clinical practice.

    Time frame: 6 months

    Number of participants to not complete the recommended testing according to the electrocardiogram-enabled CNN.

Sponsors and collaborators

Lead sponsor

Mayo Clinic

Other

Registry information

Official study title

Early Detection of Advanced Liver Disease Via Artificial Intelligence-Enabled Electrocardiogram (Advance): A Pragmatic, Cluster-Randomized Clinical Trial

Acronym: ADVANCE

Important dates

Study start
2023
Primary completion
2025
Study completion
2025
First posted
Mar 23, 2023
Registry last updated
Sep 24, 2025

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.

Published trials that share one or more normalized conditions with this study.