A Study to Detect Advanced Liver Disease Via AI-enabled Electrocardiogram (ADVANCE)
Early Detection of Advanced Liver Disease Via Artificial Intelligence-Enabled Electrocardiogram (Advance): A Pragmatic, Cluster-Randomized Clinical Trial
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
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Minnesota
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Rochester, Minnesota, United States, 55905
- Mayo Clinic Minnesota
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
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.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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No Intervention: Usual Care Group
Primary care providers will treat subject per standard of care
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Experimental: Electrocardiogram AI Group
The ACE (AI-Cirrhosis-ECG) 2.0 will be used to alert primary care providers to the likelihood of advanced liver disease with a recommendation for laboratory tests.
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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.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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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
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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.
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6 months
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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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
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Number of participants to not complete the recommended testing according to the electrocardiogram-enabled CNN.
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6 months
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Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Douglas Simonetto, MD, Mayo Clinic
Publications and helpful links
Helpful Links
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Estimated)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 22-009726
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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