title: Electrocardiographic diagnosis of ST segment elevation myocardial infarction: An evaluation of three automated interpretation algorithms.
abstract: To assess the validity of three different computerized electrocardiogram (ECG) interpretation algorithms in correctly identifying STEMI patients in the prehospital environment who require emergent cardiac intervention.
  
  
  
  This retrospective study validated three diagnostic algorithms (AG) against the presence of a culprit coronary artery upon cardiac catheterization. Two patient groups were enrolled in this study: those with verified prehospital ST-elevation myocardial infarction (STEMI) activation (cases) and those with a prehospital impression of chest pain due to ACS (controls).
  
  
  
  There were 500 records analyzed resulting in a case group with 151 patients and a control group with 349 patients. Sensitivities differed between AGs (AG1=0.69 vs AG2=0.68 vs AG3=0.62), with statistical differences in sensitivity found when comparing AG1 to AG3 and AG1 to AG2. Specificities also differed between AGs (AG1=0.89 vs AG2=0.91 vs AG3=0.95), with AG1 and AG2 significantly less specific than AG3.
  
  
  
  STEMI diagnostic algorithms vary in regards to their validity in identifying patients with culprit artery lesions. This suggests that systems could apply more sensitive or specific algorithms depending on the needs in their community.
authors.affiliation: Department of Emergency Medicine, Carolinas Medical Center, Charlotte, NC, USA.
authors.forename: J Lee
authors.initials: JL
authors.lastname: Garvey
authors.affiliation: School of Nursing, University of North Carolina, Chapel Hill, NC, USA.
authors.forename: Jessica
authors.initials: J
authors.lastname: Zegre-Hemsey
authors.affiliation: Advanced Algorithm Research Center Philips Healthcare, USA.
authors.forename: Richard
authors.initials: R
authors.lastname: Gregg
authors.affiliation: Mecklenburg EMS Agency, 4525 Statesville Rd, Charlotte, NC, USA. Electronic address: jonst@medic911.com.
authors.forename: Jonathan R
authors.initials: JR
authors.lastname: Studnek
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003324:Coronary Artery Disease / Q000150:complications / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006801:Humans; D000069550:Machine Learning; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D000072657:ST Elevation Myocardial Infarction / Q000175:diagnosis* / Q000209:etiology; D012680:Sensitivity and Specificity
keywords: Electrocardiography; Emergency medical services; Myocardial infarction; Validation studies