ArticleJournal of Korean medical science2022
A Retrospective Clinical Evaluation of an Artificial Intelligence Screening Method for Early Detection of STEMI in the Emergency Department.
Article in Journal of Korean medical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Pooled it
- Screening for Left Ventricular Dysfunction in Sepsis Using a Smartphone ECG Analysis Application: A Multicenter Validation Study.Journal of Korean medical science · 2026Observational
- Multitask Artificial Intelligence-Based Electrocardiogram Tool for Preoperative Cardiac Testing in Noncardiac Surgery: Retrospective Cohort Study of Health Care Utilization and Costs.Journal of medical Internet research · 2026Article
- A large-scale 12-lead electrocardiogram dataset for acute coronary syndrome prediction containing 19,955 ECGs.Scientific data · 2026Article
- External validation of ECG artificial intelligence for emergency and cardiac assessment across a large-scale U.S. healthcare system.NPJ digital medicine · 2026Article
- Five-year retrospective analysis of invasiveCardiovascular diagnosis and therapy · 2026Article
- Real-Time Integration of an AI-Based ECG Interpretation System in the Emergency Department: A Pragmatic Alternating-Day Study of Diagnostic Performance and Clinical Process Metrics.Healthcare (Basel, Switzerland) · 2026Article
- Artificial intelligence-enhanced ECG score for perioperative risk assessment in non-cardiac surgery.European heart journal. Digital health · 2026Article
- Application of a Commercial Artificial Intelligence Software in Unilateral Mammography: Simulating Total Mastectomy Scenarios.Journal of imaging informatics in medicine · 2025Article
- Article
- Artificial Intelligence (AI) and Emergency Medicine: Balancing Opportunities and Challenges.JMIR medical informatics · 2025Review
- Interethnic validation of electrocardiogram image analysis software for detecting left ventricular dysfunction in an emergency department population.Clinical and experimental emergency medicine · 2025Article
- AI-ECG Supported Decision-Making for Coronary Angiography in Acute Chest Pain: The QCG-AID Study.Journal of Korean medical science · 2025Article
- Non-Inferiority Analysis of Electrocardiography Analysis Application vs. Point-of-Care Ultrasound for Screening Left Ventricular Dysfunction.Yonsei medical journal · 2025Article
- Smartwatch ECG and artificial intelligence in detecting acute coronary syndrome compared to traditional 12-lead ECG.International journal of cardiology. Heart & vasculature · 2025Article
- AI derived ECG global longitudinal strain compared to echocardiographic measurements.Scientific reports · 2024Article
- Artificial Intelligence-Based Electrocardiographic Biomarker for Outcome Prediction in Patients With Acute Heart Failure: Prospective Cohort Study.Journal of medical Internet research · 2024Observational
- Artificial intelligence-enhanced electrocardiography analysis as a promising tool for predicting obstructive coronary artery disease in patients with stable angina.European heart journal. Digital health · 2024Article
- Smartphone AI vs. Medical Experts: A Comparative Study in Prehospital STEMI Diagnosis.Yonsei medical journal · 2024Article
- Hyperkalemia Detection in Emergency Departments Using Initial ECGs: A Smartphone AI ECG Analyzer vs. Board-Certified Physicians.Journal of Korean medical science · 2023Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
backgroundRapid revascularization is the key to better patient outcomes in ST-elevation myocardial infarction (STEMI). Direct activation of cardiac catheterization laboratory (CCL) using artificial intelligence (AI) interpretation of initial electrocardiography (ECG) might help reduce door-to-balloon (D2B) time. To prove that this approach is feasible and beneficial, we assessed the non-inferiority of such a process over conventional evaluation and estimated its clinical benefits, including a reduction in D2B time, medical cost, and 1-year mortality.
methodsThis is a single-center retrospective study of emergency department (ED) patients suspected of having STEMI from January 2021 to June 2021. Quantitative ECG (QCG™), a comprehensive cardiovascular evaluation system, was used for screening. The non-inferiority of the AI-driven CCL activation over joint clinical evaluation by emergency physicians and cardiologists was tested using a 5% non-inferiority margin.
resultsEighty patients (STEMI, 54 patients [67.5%]) were analyzed. The area under the curve of QCG score was 0.947. Binned at 50 (binary QCG), the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 98.1% (95% confidence interval [CI], 94.6%, 100.0%), 76.9% (95% CI, 60.7%, 93.1%), 89.8% (95% CI, 82.1%, 97.5%) and 95.2% (95% CI, 86.1%, 100.0%), respectively. The difference in sensitivity and specificity between binary QCG and the joint clinical decision was 3.7% (95% CI, -3.5%, 10.9%) and 19.2% (95% CI, -4.7%, 43.1%), respectively, confirming the non-inferiority. The estimated median reduction in D2B time, evaluation cost, and the relative risk of 1-year mortality were 11.0 minutes (interquartile range [IQR], 7.3-20.0 minutes), 26,902.2 KRW (22.78 USD) per STEMI patient, and 12.39% (IQR, 7.51-22.54%), respectively.
conclusionAI-assisted CCL activation using initial ECG is feasible. If such a policy is implemented, it would be reasonable to expect some reduction in D2B time, medical cost, and 1-year mortality.
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