A Study to Evaluate Electrocardiogram Artificial Intelligence-Guided Screening for Low Ejection Fraction (EAGLE)

Overview

About this study

The purpose of this study is to prospectively evaluate a newly-developed screening tool for ALVSD.

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 who are part of a care team that cares for adult patients (≥18 years) and who have the ability to order ECG and TTE.
  • Patient data will be included in the analysis if the patient is ≥ 18 years old and receives an ECG ordered by a participating clinician.

Exclusion Criteria:

  • Among the care teams across Mayo Clinic’s practice in Rochester and Mayo Clinic Health System, we excluded pediatrics care teams and resident care teams.

 

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

Xiaoxi Yao, Ph.D., M.P.H.

Closed-enrolling by invitation

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"Close"
Not open to everyone who meets the eligibility criteria, but only those invited to participate by the study team.

Contact information:

Emma Behnken

(507)293-0177

Behnken.Emma@mayo.edu

More information

Publications

  • A deep learning algorithm to detect low ejection fraction (EF) using routine 12-lead electrocardiogram (ECG) has recently been developed and validated. The algorithm was incorporated into the electronic health record (EHR) to automatically screen for low EF, encouraging clinicians to obtain a confirmatory transthoracic echocardiogram (TTE) for previously undiagnosed patients, thereby facilitating early diagnosis and treatment. Read More on PubMed