title: Pre-hospital triage of patients with suspected myocardial infarction. Evaluation of previously developed algorithms and new proposals.
abstract: OBJECTIVE
  To evaluate previously developed algorithms for the improvement of pre-hospital triage of patients with suspected acute cardiac disease.
  
  
  METHODS
  Prospective study.
  
  
  METHODS
  Patients with symptoms of possible cardiac origin, who were seen by a general practitioner and subsequently referred to hospital in the municipality of Rotterdam.
  
  
  METHODS
  Prior to hospital admission, patients with suspected acute coronary disease recorded their symptoms by standardized questionnaire and a computerized ECG was made. All patients were hospitalized and a final diagnosis was established. Algorithms proposed by other investigators to distinguish patients with, from those without, acute cardiac disease were tested.
  
  
  RESULTS
  Identification of patients whose likelihood for acute cardiac pathology was low (stable angina, atypical chest pain, other pathology) or high (myocardial infarction, unstable angina).
  
  
  RESULTS
  A total of 1005 patients were studied. Forty-two percent had myocardial infarction or unstable angina pectoris. Evaluation of previously developed algorithms showed that their diagnostic accuracy was poor in the pre-hospital setting. In a separate multivariate analysis, six characteristics from the clinical history and an electrocardiogram appeared to be independently and significantly associated with acute cardiac pathology. The presence of an abnormal ECG proved to be the most important predictor.
  
  
  CONCLUSIONS
  The hospital-based algorithms were unsuitable as a predictor for pre-hospital acute cardiac pathology. A new practical hospital admission model was developed, based on six clinical predictors, including analysis of an electrocardiogram. Following appropriate validation, this out-of-hospital protocol may lead to better triage decisions by the general practitioner.
authors.affiliation: Thoraxcentre, Erasmus University Rotterdam, The Netherlands.
authors.forename: E W
authors.initials: EW
authors.lastname: Grijseels
authors.forename: J W
authors.initials: JW
authors.lastname: Deckers
authors.forename: A W
authors.initials: AW
authors.lastname: Hoes
authors.forename: J A
authors.initials: JA
authors.lastname: Hartman
authors.forename: E
authors.initials: E
authors.lastname: Van der Does
authors.forename: E
authors.initials: E
authors.lastname: Van Loenen
authors.forename: M L
authors.initials: ML
authors.lastname: Simoons
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D000787:Angina Pectoris / Q000145:classification / Q000175:diagnosis* / Q000628:therapy; D000789:Angina, Unstable / Q000145:classification / Q000175:diagnosis* / Q000628:therapy; D003327:Coronary Disease / Q000145:classification / Q000175:diagnosis* / Q000628:therapy; D003661:Decision Support Techniques; D004562:Electrocardiography; D004632:Emergency Medical Services; D005500:Follow-Up Studies; D006801:Humans; D008875:Middle Aged; D009203:Myocardial Infarction / Q000145:classification / Q000175:diagnosis* / Q000628:therapy; D009426:Netherlands; D010343:Patient Admission; D012307:Risk Factors; D016896:Treatment Outcome; D014218:Triage