Artificial Intelligence-assisted Diagnosis and Prognostication in Low Ejection Fraction Using Electrocardiograms

National Defense Medical Center, Taiwan13,631 enrolled

Overview

This is a randomized controlled trial (RCT) to test a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis and management of left ventricular systolic dysfunction.

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

SCREENING

Masking

NONE

Enrollment

13,631

Conditions

Left Ventricular Systolic Dysfunction (Disorder)

Interventions

AI-enabled ECG-based Screening ToolOTHER

Primary care clinicians in the intervention group had access to the report, which displayed whether the AI-ECG result was positive or negative.The system will send a message to corresponding physicians if positive finding.

Eligibility

Sex: ALLMin age: 20 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Patients with EF\>50% or without Transesophageal Echocardiography (TEE) Exclusion Criteria: * Patients with a history of heart failure or an EF\<= 35%.

Locations (1)

National Defense Medical Center

Taipei, Taiwan

Outcomes

Primary Outcomes

New Diagnosis of Low Ejection Fraction(defined as ejection fraction ≤50%)

Ejection fraction obtained by echocardiography

Time frame: Within 30 days

Secondary Outcomes

All cause mortality(death)

After performing an electrocardiogram, the patient's survival is tracked.

Time frame: Within 30 days

Completion of an echocardiogram

After performing the ECG examination, perform the echocardiogram examination

Time frame: Within 30 days

Data from ClinicalTrials.gov

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