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Artificial Intelligence
AI-Enabled ECG for Liver Disease (ADVANCE Trial)
N/A
Waitlist Available
Led By Douglas Simonetto, MD
Research Sponsored by Mayo Clinic
Eligibility Criteria Checklist
Specific guidelines that determine who can or cannot participate in a clinical trial Must have
Be older than 18 years old
Timeline
Screening 3 weeks
Treatment Varies
Follow Up 6 months
Awards & highlights
No Placebo-Only Group
Summary
This trial aims to see if an AI-enabled algorithm can accurately detect liver disease early & if it's accepted in primary care.
Who is the study for?
This trial is for adults who are getting an ECG test and whose doctors can order such tests. It's aimed at those in primary care settings, including physicians, nurse practitioners, and physician assistants who agree to participate. People with known advanced liver disease or a history of cirrhosis are not eligible.
What is being tested?
The study is testing the ACE (AI-Cirrhosis-ECG) 2.0 model to see if it can effectively detect early signs of severe liver fibrosis using AI analysis of ECG results. The goal is also to assess how well this AI tool is accepted in a primary care environment.
What are the potential side effects?
Since the intervention involves non-invasive ECG monitoring and data analysis through an AI algorithm, there are no direct physical side effects associated with the trial itself.
Timeline
Screening ~ 3 weeks3 visits
Treatment ~ Varies
Follow Up ~ 6 months
Screening ~ 3 weeks
Treatment ~ Varies
Follow Up ~6 months
Treatment Details
Study Objectives
Study objectives can provide a clearer picture of what you can expect from a treatment.Primary study objectives
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.
Secondary study objectives
The secondary objective is to assess barriers for adoption of an AI-enabled algorithm for detection of liver disease in routine community clinical practice.
Awards & Highlights
No Placebo-Only Group
All patients enrolled in this study will receive some form of active treatment.
Trial Design
2Treatment groups
Experimental Treatment
Active Control
Group I: Electrocardiogram AI GroupExperimental Treatment1 Intervention
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.
Group II: Usual Care GroupActive Control1 Intervention
Primary care providers will treat subject per standard of care
Find a Location
Who is running the clinical trial?
Mayo ClinicLead Sponsor
3,339 Previous Clinical Trials
3,061,745 Total Patients Enrolled
19 Trials studying Liver Cirrhosis
6,474 Patients Enrolled for Liver Cirrhosis
Douglas Simonetto, MDPrincipal InvestigatorMayo Clinic
2 Previous Clinical Trials
90 Total Patients Enrolled
Media Library
Eligibility Criteria:
This trial includes the following eligibility criteria:- The study will involve adults aged 18 and above who have undergone an electrocardiogram over a 6-month period for any reason.You are attended to by a primary healthcare provider such as a doctor, nurse practitioner or physician assistant.Information will be gathered from patients' EMRs.You possess the capacity to order an electrocardiogram (ECG).You are part of a team that provides care to adults aged 18 and above.Primary care clinicians will be asked to provide their consent.
Research Study Groups:
This trial has the following groups:- Group 1: Usual Care Group
- Group 2: Electrocardiogram AI Group
Awards:
This trial has 1 awards, including:- No Placebo-Only Group - All patients enrolled in this study will receive some form of active treatment.
Timeline:
This trial has the following timeline:- Screening: It may take up to 3 Weeks to process to see if you qualify in this trial.
- Treatment: The duration you will receive the treatment varies.
- Follow Ups: You may be asked to continue sharing information regarding the trial for 6 Months after you stop receiving the treatment.
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