Evaluation of Clinical Intelligence Support to Reduce Errors in Normal ECGs
NCT ID: NCT07179185
Last Updated: 2025-09-22
Study Results
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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NOT_YET_RECRUITING
NA
710 participants
INTERVENTIONAL
2025-10-01
2025-11-30
Brief Summary
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
DIAGNOSTIC
NONE
Study Groups
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Control - Specialist Interpretation Without AI
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.
Specialist ECG Interpretation Without AI
Manual interpretation of ECGs by specialists without AI support, following standard diagnostic procedures
Specialist interpretation with AI assistance
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.
AI-Assisted ECG Interpretation (AI-ECG)
Neural network-based AI software that analyzes ECG tracings and provides a classification as normal suggestion to the interpreting specialist.
Interventions
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AI-Assisted ECG Interpretation (AI-ECG)
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
Manual interpretation of ECGs by specialists without AI support, following standard diagnostic procedures
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
ALL
No
Sponsors
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Uppsala University
OTHER
Federal University of Minas Gerais
OTHER
Responsible Party
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Antonio Luiz Pinho Ribeiro
Full Professor, Internal Medicine Department, School of Medicine
Central Contacts
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References
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Oliveira CRA, Paixao GMM, Tostes VC, Gomes PR, Mendes MS, Paixao MC, Marcolino MS, Ribeiro ALP. Upscaling a regional telecardiology service to a nationwide coverage and beyond: the experience of the Telehealth Network of Minas Gerais. BMJ Glob Health. 2025 Jan 19;10(1):e016692. doi: 10.1136/bmjgh-2024-016692.
Ribeiro ALP, Paixao GMM, Gomes PR, Ribeiro MH, Ribeiro AH, Canazart JA, Oliveira DM, Ferreira MP, Lima EM, Moraes JL, Castro N, Ribeiro LB, Macfarlane PW. Tele-electrocardiography and bigdata: The CODE (Clinical Outcomes in Digital Electrocardiography) study. J Electrocardiol. 2019 Nov-Dec;57S:S75-S78. doi: 10.1016/j.jelectrocard.2019.09.008. Epub 2019 Sep 7.
Ribeiro AH, Ribeiro MH, Paixao GMM, Oliveira DM, Gomes PR, Canazart JA, Ferreira MPS, Andersson CR, Macfarlane PW, Meira W Jr, Schon TB, Ribeiro ALP. Automatic diagnosis of the 12-lead ECG using a deep neural network. Nat Commun. 2020 Apr 9;11(1):1760. doi: 10.1038/s41467-020-15432-4.
Other Identifiers
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409604/2022-4
Identifier Type: -
Identifier Source: org_study_id
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