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NCT05867407 | Not yet recruiting | Ventricular Ejection Fraction


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

Estimate, this.

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

Not Applicable

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 (Open Label)
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 : February 2024
Estimated Primary Completion Date : May 2024
Estimated Study Completion Date : May 2024
Arm Intervention/treatment

Experimental: Anumana Low EF AI-ECG Algorithm

Anumana Low EF AI-ECG Algorithm

Device: Anumana Low EF AI-ECG Algorithm

Other: Care-as-Usual

Care-as-Usual

Other: Care-as-Usual

Ages Eligible for Study: 18 Years
Sexes Eligible for Study: All
Accepts Healthy Volunteers: No
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


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

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Locations


Not yet recruiting

United States, Minnesota

Mayo Clinic

Rochester, Minnesota, United States, 55905

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