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NCT Number: NCT07179185

Evaluation of Clinical Intelligence Support to Reduce Errors in Normal ECGs

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.

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Key information

Conditions

Electrocardiogram Cardiovascular Abnormalities Cardiovascular Diseases Congenital Abnormalities Congenital, Hereditary, and Neonatal Diseases and Abnormalities

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

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

Exclusion criteria

  • ECGs from patients younger than 18 years

Treatment and study plan

AI-Assisted ECG Interpretation (AI-ECG)

Diagnostic Test

Neural network-based AI software that analyzes ECG tracings and provides a classification as normal suggestion to the interpreting specialist.

Specialist ECG Interpretation Without AI

Diagnostic Test

Manual interpretation of ECGs by specialists without AI support, following standard diagnostic procedures

Primary outcomes

  1. Precision (Positive Predictive Value) for detection of normal ECG tracings

    Time frame: One week

    Precision (Positive Predictive Value) of detecting normal ECG by the physician or physician+model compared against the reference standard defined by a panel of three specialists. Precision (Positive Predictive Value) is defined by the number of true positive normal cases divided by all positive predictions.

Secondary outcomes

  1. Sensitivity, Specificity, Negative Predictive Value, and F1 score for detection of normal ECG tracings

    Time frame: One week

    Accuracy evaluated by Sensitivity, Specificity, Negative Predictive Value, and F1 score of normal ECGs correctly identified by the physician or physician+model, in relation to a reference standard defined by a panel of three specialists.

  2. ECGs with major abnormalities incorrectly classified as normal

    Time frame: One week

    Ratio of ECGs with major abnormalities according to the Minnesota Code system among those incorrectly classified as normal by the physician or physician+model, in relation to a reference standard defined by a panel of three specialists.

  3. Time of analysis for normal cases (seconds per case)

    Time frame: One week

    Time required by the physician, or physician+model, to interpret normal ECGs, measured in seconds per case; the reference standard of normal cases defined by a panel of three specialists.

Study contacts

Contact information is provided by the study sponsor or research team.

Antonio Luiz P. Ribeiro, MD, PhD

CONTACT

[email protected]

55(31)3307-9201

Gabriela Miana M. Paixão, MD, PhD

CONTACT

[email protected]

55(31) 3307-9201

Sponsors and collaborators

Lead sponsor

Federal University of Minas Gerais

Other

Collaborators

  • Uppsala University

Registry information

Official study title

PRECISE-ECG: Prospective Randomized Evaluation of Clinical Intelligence Support to Reduce Errors in Normal ECGs

Acronym: PRECISE-ECG

Important dates

Study start
2025
Primary completion
2025
Study completion
2025
First posted
Sep 17, 2025
Registry last updated
Sep 22, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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