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NCT05867407 | ENROLLING BY INVITATION | Ventricular Ejection Fraction


A Multicenter Pragmatic Implementation Study of ECG-AI-Based Clinical Decision Support Software to Identify Low LVEF
Sponsor:

Anumana, Inc.

Brief Summary:

A prospective, cluster-randomized, care-as-usual controlled trial to evaluate the impact of an ECG-based artificial intelligence (ECG-AI) algorithm to detect low left ventricular ejection fraction (LVEF) on diagnosis rates of LVEF ≤ 40% in the outpatient setting. The objective of this study is to evaluate the impacts of an ECG-AI algorithm to detect low LVEF and an associated Medical Device Data System when used during routine outpatient care. The study will be conducted in 2 phases: feasibility assessment phase and clinical impact phase.

Condition or disease

Ventricular Ejection Fraction

Intervention/treatment

Anumana Low EF AI-ECG Algorithm

Care-as-Usual

Phase

NA

Detailed Description:

The study is a prospective, cluster randomized, care-as-usual controlled trial that will be conducted at 6 sites in the USA. Primary care clinicians and general cardiologists will be invited and consented to participate in the study. For clinicians that accept, practice groups will be randomized to receive access to and education about the Low EF AI-ECG software and encompassing software or to provide care-as-usual in the control group. The study will be conducted in two phases: a feasibility pilot to evaluate integration and usability followed by observational period(s) to evaluate clinical outcomes. Analyses of the primary and secondary endpoints will be conducted on data from patients that meet the inclusion and exclusion criteria. The expected duration of the study is 12 months, including a feasibility phase (estimated 6 weeks) followed by a 3-month initial observation period with rolling observation count monitoring until the target number of patient encounters is reached, followed by a 90-day follow up period. At the completion of the feasibility period, we will evaluate quantitative and qualitative outcomes to inform the following observational period(s). Primary endpoints and exploratory endpoints will be assessed the end of the study.

Study Type : INTERVENTIONAL
Estimated Enrollment : 50198 participants
Masking : NONE
Primary Purpose : SCREENING
Official Title : A Prospective Pragmatic Cluster-Randomized Care-as-Usual Controlled Study to Evaluate the Impact of an ECG-Based AI Algorithm to Detect Low Left Ventricular Ejection Fraction on Diagnosis Rates of LVEF ≤40% in the Outpatient Setting
Actual Study Start Date : 2024-06-13
Estimated Primary Completion Date : 2026-01
Estimated Study Completion Date : 2026-04

Information not available for Arms and Intervention/treatment

Ages Eligible for Study: 18 Years
Sexes Eligible for Study: ALL
Accepts Healthy Volunteers:
Criteria
Inclusion Criteria
  • * Males and females 18 years or older (including females who are pregnant, breastfeeding and/or lactating)
  • * Digital ECG captured or available within site for ECG-AI analysis at point-of-care
Exclusion Criteria
  • * Known history of LVEF ≤ 40%
  • * Known history of systolic heart failure
  • * Known history of heart failure with reduced ejection fraction
  • * Opted out of electronic health record-based research

A Multicenter Pragmatic Implementation Study of ECG-AI-Based Clinical Decision Support Software to Identify Low LVEF

Location Details

NCT05867407


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How to Participate

Want to participate in this study, select a site at your convenience, send yourself email to get contact details and prescreening steps.

Locations


Not yet recruiting

United States, Arizona

Mayo Clinic Arizona

Phoenix, Arizona, United States, 85054

Not yet recruiting

United States, Florida

Mayo Clinic Florida

Jacksonville, Florida, United States, 32224

Not yet recruiting

United States, Minnesota

Mayo Clinic Rochester

Rochester, Minnesota, United States, 55905

Not yet recruiting

United States, North Carolina

Duke Health

Durham, North Carolina, United States, 27710

Not yet recruiting

United States, Texas

University of Texas Southwestern

Dallas, Texas, United States, 75390

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