J Korean Med Sci.  2022 Mar;37(10):e81. 10.3346/jkms.2022.37.e81.

A Retrospective Clinical Evaluation of an Artificial Intelligence Screening Method for Early Detection of STEMI in the Emergency Department

Affiliations
  • 1Department of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
  • 2Department of Cardiology, Seoul National University Bundang Hospital, Seongnam, Korea
  • 3Big Data Center, Seoul National University Bundang Hospital, Seongnam, Korea

Abstract

Background
Rapid 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.
Methods
This 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.
Results
Eighty 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.
Conclusion
AI-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.

Keyword

Artificial Intelligence; Myocardial Infarction; Triage; Time-to-Treatment; Myocardial Revascularization

Figure

  • Fig. 1 ROC curve of QCG score (black solid line), binary QCG (score ≥ 50, blue dashed line), EPs (brown dashed line), and cardiologists (joint evaluation, red dashed line) in the prediction of STEMI. Binary QCG had the highest AUC, which was significantly higher than that of EPs.ROC = receiver operating characteristic, QCG = quantitative electrocardiography, EP = emergency physician, STEMI = ST-elevation myocardial infarction, AUC = area under the curve.

  • Fig. 2 Event progress of study subjects in ED. (A) Event progress since ED arrival in confirmed STEMI patients: Circles, time of initial ECG; Vertical line, time of call by EM physicians; Squares, time of confirmation by cardiologists; Cyan, predicted as STEMI; Pink, predicted as not STEMI. (B) Event progress since ED arrival in patients confirmed to be free of STEMI: Circles, time of initial ECG; Vertical line, time of call by EM physicians; Squares, time of CP confirmation by cardiologists; Cyan, predicted as STEMI; Pink, predicted as not STEMI.ED = emergency department, STEMI = ST-elevation myocardial infarction, ECG = electrocardiography, EM = emergency medicine, CP = coronary perforation.


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Donghoon Kim, Joo Jeong, Joonghee Kim, Youngjin Cho, Inwon Park, Sang-Min Lee, Young Taeck Oh, Sumin Baek, Dongin Kang, Eunkyoung Lee, Bumi Jeong
J Korean Med Sci. 2023;38(45):e322.    doi: 10.3346/jkms.2023.38.e322.


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