Evaluation of Clinical Intelligence Support to Reduce Errors in Normal ECGs (PRECISE-ECG)

Federal University of Minas Gerais

Status: Not yet enrolling

Conditions: Electrocardiogram; Cardiovascular Abnormalities

Treatments: Diagnostic Test: Specialist ECG Interpretation Without AI; Diagnostic Test: AI-Assisted ECG Interpretation (AI-ECG)

Study type: Interventional

Funder types: Other

Identifiers

NCT07179185

409604/2022-4

Details and patient eligibility

About

This study will evaluate the performance of specialist physicians in interpreting normal electrocardiograms (ECGs) with and without the assistance of an artificial intelligence (AI) neural network. The primary aim is to determine whether AI support affects the rate of false-positive interpretations of normal tracings. Secondary aims include evaluating the time required for interpretation, the sensitivity for detecting abnormalities, and the effect on false positives in ECGs with major abnormalities according to the Minnesota Code system. All ECGs in the sample will be reviewed by a panel of three specialists, to determine the reference classification.

Enrollment: 710 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• ECGs performed routinely by the Rede de Telemedicina de Minas Gerais (RTMG)

Exclusion criteria

• ECGs from patients younger than 18 years

Trial design

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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710 participants in 2 patient groups

Control - Specialist Interpretation Without AI

Active Comparator group

Description:

Specialist physicians interpret normal ECGs without the assistance of the AI-ECG tool. ECGs are routine tracings performed by the Rede de Telemedicina de Minas Gerais (RTMG). Final classification for study endpoints will be based on a panel review by three specialists.

Treatment:

Diagnostic Test: Specialist ECG Interpretation Without AI

Specialist interpretation with AI assistance

Experimental group

Description:

Specialist physicians interpret ECGs using the AI-ECG tool, which provides automated classification support indicating whether the ECG is normal or not. ECGs are routine tracings performed by RTMG. Final classification for study endpoints will be based on a panel review by three specialists.

Treatment:

Diagnostic Test: AI-Assisted ECG Interpretation (AI-ECG)