title: Computerized interpretation of the prehospital electrocardiogram: predictive value for ST segment elevation myocardial infarction and impact on on-scene time.
abstract: BACKGROUND
  Computerized interpretation of the prehospital electrocardiogram (ECG) is increasingly being used in the basic life support (BLS) ambulance setting to reduce delays to treatment for patients suspected of ST segment elevation myocardial infarction (STEMI).
  
  
  OBJECTIVE
  To estimate 1) predictive values of computerized prehospital 12-lead ECG interpretation for STEMI and 2) additional on-scene time for 12-lead ECG acquisition.
  
  
  METHODS
  Over a 2-year period, 1,247 ECGs acquired by primary care paramedics for suspected STEMI were collected. ECGs were interpreted in real time by the GE-Marquette 12SL ECG analysis program. Predictive values were estimated with a bayesian latent class model incorporating the computerized ECG interpretations, consensus ECG interpretations by study cardiologists, and hospital diagnosis. On-scene time was compared for ambulance-transported patients with (n  =  985) and without (n  =  5,056) prehospital ECGs who received prehospital aspirin and/or nitroglycerin.
  
  
  RESULTS
  The computer's positive and negative predictive values for STEMI were 74.0% (95% credible interval [CrI] 69.6-75.6) and 98.1% (95% CrI 97.8-98.4), respectively. The sensitivity and specificity were 69.2% (95% CrI 59.0-78.5) and 98.9% (95% CrI 98.1-99.4), respectively. Prehospital ECGs were associated with a mean increase in on-scene time of 5.9 minutes (95% confidence interval 5.5-6.3).
  
  
  CONCLUSIONS
  The predictive values of the computerized prehospital ECG interpretation appear to be adequate for diversion programs that direct patients with a positive result to hospitals with angioplasty facilities. The estimated 26.0% chance that a positive interpretation is false is likely too high for activation of a catheterization laboratory from the field. Acquiring prehospital ECGs does not substantially increase on-scene time in the BLS setting.
authors.forename: François
authors.initials: F
authors.lastname: de Champlain
authors.forename: Lucy J
authors.initials: LJ
authors.lastname: Boothroyd
authors.forename: Alain
authors.initials: A
authors.lastname: Vadeboncoeur
authors.forename: Thao
authors.initials: T
authors.lastname: Huynh
authors.forename: Viviane
authors.initials: V
authors.lastname: Nguyen
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Eisenberg
authors.forename: Lawrence
authors.initials: L
authors.lastname: Joseph
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Boivin
authors.forename: Eli
authors.initials: E
authors.lastname: Segal
mesh_terms: D000368:Aged; D001499:Bayes Theorem; D004562:Electrocardiography; D001330:Electronic Data Processing / Q000379:methods*; D004632:Emergency Medical Services / Q000379:methods*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D009203:Myocardial Infarction / Q000175:diagnosis*; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D013997:Time Factors