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Smartphone AI vs. Medical Experts: A Comparative Study in Prehospital STEMI Diagnosis.
Lee, Seung Hyo; Hong, Won Pyo; Kim, Joonghee; Cho, Youngjin; Lee, Eunkyoung.
Afiliación
  • Lee SH; National Fire Agency Pre-hospital Emergency Medical Research TF, Sejong, Korea.
  • Hong WP; National Emergency Medical Center, National Medical Center, Seoul, Korea.
  • Kim J; Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea. pyotang@gmail.com.
  • Cho Y; Department of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam, Korea.
  • Lee E; ARPI Inc., Seongnam, Korea. joonghee@snubh.org.
Yonsei Med J ; 65(3): 174-180, 2024 Mar.
Article en En | MEDLINE | ID: mdl-38373837
ABSTRACT

PURPOSE:

Prehospital telecardiology facilitates early ST-elevation myocardial infarction (STEMI) detection, yet its widespread implementation remains challenging. Extracting digital STEMI biomarkers from printed electrocardiograms (ECGs) using phone cameras could offer an affordable and scalable solution. This study assessed the feasibility of this approach with real-world prehospital ECGs. MATERIALS AND

METHODS:

Patients suspected of having STEMI by emergency medical technicians (EMTs) were identified from a policy research dataset. A deep learning-based ECG analyzer (QCG™ analyzer) extracted a STEMI biomarker (qSTEMI) from prehospital ECGs. The biomarker was compared to a group of human experts, including five emergency medical service directors (board-certified emergency physicians) and three interventional cardiologists based on their consensus score (number of participants answering "yes" for STEMI). Non-inferiority of the biomarker was tested using a 0.100 margin of difference in sensitivity and specificity.

RESULTS:

Among 53 analyzed patients (24 STEMI, 45.3%), the area under the receiver operating characteristic curve of qSTEMI and consensus score were 0.815 (0.691-0.938) and 0.736 (0.594-0.879), respectively (p=0.081). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of qSTEMI were 0.750 (0.583-0.917), 0.862 (0.690-0.966), 0.826 (0.679-0.955), and 0.813 (0.714-0.929), respectively. For the consensus score, sensitivity, specificity, PPV, and NPV were 0.708 (0.500-0.875), 0.793 (0.655-0.966), 0.750 (0.600-0.941), and 0.760 (0.655-0.880), respectively. The 95% confidence interval of sensitivity and specificity differences between qSTEMI and consensus score were 0.042 (-0.099-0.182) and 0.103 (-0.043-0.250), respectively, confirming qSTEMI's non-inferiority.

CONCLUSION:

The digital STEMI biomarker, derived from printed prehospital ECGs, demonstrated non-inferiority to expert consensus, indicating a promising approach for enhancing prehospital telecardiology.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Servicios Médicos de Urgencia / Infarto del Miocardio con Elevación del ST / Infarto del Miocardio Límite: Humans Idioma: En Revista: Yonsei Med J Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Servicios Médicos de Urgencia / Infarto del Miocardio con Elevación del ST / Infarto del Miocardio Límite: Humans Idioma: En Revista: Yonsei Med J Año: 2024 Tipo del documento: Article