Test of the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI) for prehospital use

Ann Emerg Med. 1996 Feb;27(2):193-8. doi: 10.1016/s0196-0644(96)70322-0.

Abstract

Study objectives: To test diagnostic performance for acute cardiac ischemia (ACI) in a manually calculated and in a computerized, ECG-calculated ACI time-insensitive predictive instrument (ACI-TIPI) in prehospital chest pain patients.

Methods: We carried out prospective inclusion and data acquisition with retrospective analysis. Over a 6-month period, 439 adult emergency medical services patients with chest pain underwent prehospital electrocardiography. Because of incomplete data, 77 cases were excluded, leaving a study sample of 362 patients. Excluded patients did not differ significantly with respect to age, sex, final diagnosis, or history of myocardial infarction, heart surgery, diabetes, or stroke. ACI-TIPI probabilities of ACI were computed on the basis of the prehospital ECGs as interpreted retrospectively and independently by two study investigators blinded to patient outcome, with a specially programmed electrocardiograph, and with a computer algorithm further modified by logistic-regression analysis.

Results: Diagnostic performance on the basis of receiver operating characteristic (ROC) curve areas of the ACI-TIPI was scored, by the two physician readers, .73 and .74; and by ECG, .75. Patients with low ACI-TIPI probability (0% to 9%) had no acute myocardial infarctions, a 2.3% incidence of angina, and no prehospital life-threatening events.

Conclusion: ACI-TIPI probabilities of ACI as generated by a specially programmed electrocardiograph are comparable to those based on physician ECG interpretations and may be useful in the prehospital evaluation of chest pain.

MeSH terms

  • Acute Disease
  • Aged
  • Algorithms
  • Electrocardiography / methods*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Myocardial Ischemia / diagnosis*
  • Predictive Value of Tests
  • Probability
  • ROC Curve
  • Regression Analysis
  • Retrospective Studies
  • Signal Processing, Computer-Assisted
  • Time Factors
  • Triage