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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVE, METHODS, RESULTS. Meshes: Aged, Angina, Unstable, Artificial Intelligence, Diagnosis, Computer-Assisted, Electrocardiography, Emergency Medical Services, Female, Humans, Male, Middle Aged, Myocardial Infarction, Quality Assurance, Health Care, Reproducibility of Results, Retrospective Studies, Sensitivity and Specificity, Syndrome.
user
Does best lead in the standard electrocardiogram for the emergency detection of acute coronary syndrome? Context: The purpose of this study was to determine which leads in the standard 12-lead electrocardiogram (ECG) are the best for detecting acute coronary syndrome (ACS) among chest pain patients in the emergency department. Neural network classifiers were used to determine the predictive capability of individual leads and combinations of leads from 862 ECGs from chest pain patients in the emergency department at Lund University Hospital. The best individual lead was aVL, with an area under the receiver operating characteristic curve of 75.5%. The best 3-lead combination was III, aVL, and V2, with a receiver operating characteristic area of 82.0%, compared with the 12-lead ECG performance of 80.5%.
assistant
Our results indicate that leads III, aVL, and V2 are sufficient for computerized prediction of ACS. The present results are likely important in situations where the 12-lead ECG is impractical and for the creation of clinical decision support systems for ECG prediction of ACS. Final Decision: yes