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

Overview

About this study

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.

Participation eligibility

Participant eligibility includes age, gender, type and stage of disease, and previous treatments or health concerns. Guidelines differ from study to study, and identify who can or cannot participate. There is no guarantee that every individual who qualifies and wants to participate in a trial will be enrolled. Contact the study team to discuss study eligibility and potential participation.

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. 

Eligibility last updated 10/26/22. Questions regarding updates should be directed to the study team contact.

Participating Mayo Clinic locations

Study statuses change often. Please contact the study team for the most up-to-date information regarding possible participation.

Mayo Clinic Location Status Contact

Rochester, Minn.

Mayo Clinic principal investigator

Douglas Simonetto, M.D.

Contact us for the latest status

Contact information:

Amy Olofson R.N.

(507) 538-6547

Olofson.Amy@mayo.edu

More information

Publications

Publications are currently not available
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CLS-20547081

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