NCT05117970

Brief Summary

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.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
13,631

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Dec 2021

Typical duration for not_applicable

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

November 1, 2021

Completed
10 days until next milestone

First Posted

Study publicly available on registry

November 11, 2021

Completed
28 days until next milestone

Study Start

First participant enrolled

December 9, 2021

Completed
1.5 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

May 31, 2023

Completed
7 months until next milestone

Study Completion

Last participant's last visit for all outcomes

December 31, 2023

Completed
Last Updated

October 23, 2024

Status Verified

October 1, 2024

Enrollment Period

1.5 years

First QC Date

November 1, 2021

Last Update Submit

October 21, 2024

Conditions

Left Ventricular Systolic Dysfunction (Disorder)

Outcome Measures

Primary Outcomes (1)

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

    Ejection fraction obtained by echocardiography

    Within 30 days

Secondary Outcomes (2)

  • All cause mortality(death)

    Within 30 days

  • Completion of an echocardiogram

    Within 30 days

Study Arms (2)

Intervention

EXPERIMENTAL

Patients randomized to intervention will have access to the screening tool.

Other: AI-enabled ECG-based Screening Tool

Control

NO INTERVENTION

Patients randomized to control will continue routine practice.

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.

Intervention

Eligibility Criteria

Age20 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Patients with EF\>50% or without Transesophageal Echocardiography (TEE)

You may not qualify if:

  • Patients with a history of heart failure or an EF\<= 35%.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

National Defense Medical Center

Taipei, 114, Taiwan

Location

Related Publications (1)

  • Tsai DJ, Lin C, Liu WT, Lee CC, Chang CH, Lin WY, Liu YL, Chang DW, Hsieh PH, Tsai CS, Chen YH, Hung YJ, Lin CS. Artificial intelligence-assisted diagnosis and prognostication in low ejection fraction using electrocardiograms in inpatient department: a pragmatic randomized controlled trial. BMC Med. 2025 Jun 9;23(1):342. doi: 10.1186/s12916-025-04190-z.

    PMID: 40484925DERIVED

MeSH Terms

Conditions

Ventricular Dysfunction, Left

Condition Hierarchy (Ancestors)

Ventricular DysfunctionHeart DiseasesCardiovascular Diseases

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Purpose
SCREENING
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Assistant Professor

Study Record Dates

First Submitted

November 1, 2021

First Posted

November 11, 2021

Study Start

December 9, 2021

Primary Completion

May 31, 2023

Study Completion

December 31, 2023

Last Updated

October 23, 2024

Record last verified: 2024-10

Data Sharing

IPD Sharing
Will not share

Locations

TW(1)