Introduction: Previous studies have demonstrated varying sensitivity and specificity of computer-interpreted electrocardiography (CIE) in identifying ST-segment elevation myocardial infarction (STEMI). This study aims to evaluate the accuracy of contemporary computer software in recognizing electrocardiography (ECG) signs characteristic of STEMI compared to emergency physician overread in clinical practice.
Material And Methods: In this retrospective observational single-center study, we reviewed the records of patients in the emergency department (ED) who underwent ECGs and troponin tests. Both the Philips DXL 16-Lead ECG. Algorithm and on-duty emergency physicians interpreted each standard 12‑lead ECG. The sensitivity and specificity of computer interpretation and physician overread ECGs for the definite diagnosis of STEMI were calculated and compared.
Results: Among the 9340 patients included in the final analysis, 133 were definitively diagnosed with STEMI. When "computer-reported infarct or injury" was used as the indicator, the sensitivity was 87.2% (95% CI 80.3% to 92.4%) and the specificity was 86.2% (95% CI 85.5% to 86.9%). When "physician-overread STEMI" was used as the indicator, the sensitivity was 88.0% (95% CI 81.2% to 93.0%) and the specificity was 99.9% (95% CI 99.8% to 99.9%). The area under the receiver operating characteristic curve for physician-overread STEMI and computer-reported infarct or injury were 0.939 (95% CI 0.907 to 0.972) and 0.867 (95% CI 0.834 to 0.900), respectively.
Conclusions: This study reveals that while the sensitivity of the computer in recognizing ECG signs of STEMI is similar to that of physicians, physician overread of ECGs is more specific and, therefore, more accurate than CIE.
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http://dx.doi.org/10.1016/j.jelectrocard.2023.07.013 | DOI Listing |
Prehosp Emerg Care
November 2024
Department of Emergency Medicine, Newark Beth Israel Medical Center, Newark, New Jersey.
Objectives: Out of Hospital Cardiac Arrest (OHCA) is a frequently encountered pathology with resultant poor outcomes in the majority of patients. Echocardiography has been utilized to help guide clinical decision making and monitor effectiveness of resuscitative efforts. Transthoracic echocardiography (TTE) the mainstay of point-of-care ultrasound (POCUS) real time resuscitative imaging has limitations, most notably is the disruption of closed chest compressions.
View Article and Find Full Text PDFPediatr Cardiol
August 2024
Nationwide Children's Hospital Heart Center, Nationwide Children's Hospital, 700 Children's Drive, Columbus, OH, 43205, USA.
The aim of this study was to evaluate the accuracy of the KardiaMobile (KM) device in adults with a Fontan palliation, and to assess the KM function as a screening tool for atrial arrhythmias. While patient driven electrocardiogram (EKG) devices are becoming a validated way to evaluate cardiac arrhythmias, their role for patients with congenital heart disease is less clear. Patients with single ventricle Fontan palliation have a high prevalence of atrial arrhythmias and represent a unique cohort that could benefit from early detection of atrial arrhythmias.
View Article and Find Full Text PDFHeliyon
May 2024
Division of Nuclear Medicine, Department of Radiology, University of Michigan, Ann Arbor, MI, USA.
Purpose: To determine the accuracy of Tc-99 m sestamibi for the diagnosis of acute cholecystitis during a supply chain disruption of mebrofenin.
Material And Methods: During a national shortage of Tc-99 m mebrofenin in 2019, our institution initiated sestamibi imaging for suspected cases of acute cholecystitis using a standard hepatobiliary imaging protocol. Forty-one patients underwent hepatobiliary imaging with sestamibi, 39 to assess for acute cholecystitis.
Eur Heart J Digit Health
January 2024
Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands.
Aims: Expert knowledge to correctly interpret electrocardiograms (ECGs) is not always readily available. An artificial intelligence (AI)-based triage algorithm (DELTAnet), able to support physicians in ECG prioritization, could help reduce current logistic burden of overreading ECGs and improve time to treatment for acute and life-threatening disorders. However, the effect of clinical implementation of such AI algorithms is rarely investigated.
View Article and Find Full Text PDFPrehosp Disaster Med
February 2024
University of California Los Angeles, Los Angeles, CaliforniaUSA.
Introduction: Early detection of ST-segment elevation myocardial infarction (STEMI) on the prehospital electrocardiogram (ECG) improves patient outcomes. Current software algorithms optimize sensitivity but have a high false-positive rate. The authors propose an algorithm to improve the specificity of STEMI diagnosis in the prehospital setting.
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