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Evaluation of Clinical Intelligence Support to Reduce Errors in Normal ECGs

Study acronym: PRECISE-ECG
StatusNot Yet Recruiting
PhaseNot applicable
Started
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Record status
This record was last updated September 22, 2025 (before its estimated October 5, 2025 completion). Its status may not reflect the trial's current state.

Record History

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  1. Study title shortened, about 2 wordsv2
  2. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
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.
Trial Details
NCT Number NCT07179185
Lead Sponsor Federal University of Minas Gerais
Collaborators: Uppsala University
Conditions
(from sponsor)		 Electrocardiogram, Cardiovascular Abnormalities
Related terms Cardiovascular Abnormalities
Enrollment 710 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov