CARDIOLOGIST Trial: Artificial Intelligence Enabled Electrocardiogram for Atrial Fibrillation Detection

NCT ID: NCT05127460

Last Updated: 2023-03-28

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

25732 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-01-01

Study Completion Date

2023-01-31

Brief Summary

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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 Atrial Fibrillation.

Detailed Description

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Conditions

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Atrial Fibrillation New Onset

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SCREENING

Blinding Strategy

NONE

Study Groups

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Intervention

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

Group Type EXPERIMENTAL

AI-enabled ECG-based Screening Tool

Intervention Type OTHER

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.

Control

Patients randomized to control will continue routine practice.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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AI-enabled ECG-based Screening Tool

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 Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Patients in emergency department or inpatient department
* Patients had at least 1 ECG
* Patients cared by non-cardiologist

Exclusion Criteria

* Patients without history of atrial fibrillation diagnosis.
* Patients without history of long-term NOAC or warfarin usage.
* Patients without history of hemorrhagic stoke or ishemic stroke.
* Patients with low eGFR (\<30 ml/min)
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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National Defense Medical Center, Taiwan

OTHER

Sponsor Role lead

Responsible Party

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Chin Lin

Assistant Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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National Defense Medical Center

Taipei, , Taiwan

Site Status

Countries

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Taiwan

References

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Liu WT, Lin C, Lee CC, Chang CH, Fang WH, Tsai DJ, Lin WY, Hung Y, Chen KC, Lee CH, Tsai TN, Lin WS, Hung YJ, Lin SH, Tsai CS, Lin CS. Artificial Intelligence-Enabled ECGs for Atrial Fibrillation Identification and Enhanced Oral Anticoagulant Adoption: A Pragmatic Randomized Clinical Trial. J Am Heart Assoc. 2025 Jul 15;14(14):e042106. doi: 10.1161/JAHA.125.042106. Epub 2025 Jul 3.

Reference Type DERIVED
PMID: 40611485 (View on PubMed)

Other Identifiers

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NDMC2021002

Identifier Type: -

Identifier Source: org_study_id

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