跳至主要内容
临床试验/NCT05867407
NCT05867407终止不适用

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

Anumana, Inc.5 个研究点 分布在 1 个国家目标入组 11,610 人开始时间: 2024年6月13日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
终止
发起方
Anumana, Inc.
入组人数
11,610
试验地点
5
主要终点
Diagnosis rates of low ejection fraction of less than or equal to 40 percent by echocardiography compared to care-as-usual

研究概览

简要总结

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.

详细描述

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.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Screening
盲法
None

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者
否

入选标准

  • •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

排除标准

  • •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

研究组 & 干预措施

Anumana Low EF AI-ECG Algorithm

Experimental

Anumana Low EF AI-ECG Algorithm

干预措施: Anumana Low EF AI-ECG Algorithm (Device)

Care-as-Usual

Other

Care-as-Usual

干预措施: Care-as-Usual (Other)

结局指标

主要结局

Diagnosis rates of low ejection fraction of less than or equal to 40 percent by echocardiography compared to care-as-usual

时间窗: 90 days

Diagnosis rates of low ejection fraction of less than or equal to 40 percent by echocardiography compared to care-as-usual

次要结局

未报告次要终点

研究者

发起方
Anumana, Inc.
申办方类型
Industry
责任方
Sponsor

研究点 (5)

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