Triage flowchart to rule out acute coronary syndrome

Am J Emerg Med. 2007 Oct;25(8):865-72. doi: 10.1016/j.ajem.2006.12.025.


Aim: The aim of the study was to establish a triage flowchart to rule out acute coronary syndrome (ACS) among patients with chest pain (CP) arriving on an Emergency Department (ED).

Patients and method: This prospective observational study included 1000 consecutive patients with CP arriving on an ED CP unit. Demographic and clinical characteristics along with vital signs were recorded as independent variables. After CP unit protocol completion and 1-month follow-up, patients were classified as (dependent variable) (1) true non-ACS (all noncoronary patients at the first visit that kept this condition when called 1 month later) or (2) true ACS (all the remaining patients). Relationship among variables was assessed by multiple logistic regression analysis. A triage flowchart was obtained from significant variables and applied to patients with CP who were then grouped in "triage non-ACS" and "triage ACS." Validity indexes to exclude ACS for triage flowchart were measured.

Results: Variables significantly associated with non-ACS and included in the triage flowchart were age <40 years (odds ratio 3.61, 95% CI 1.63-7.99), absence of diabetes (2.74, 1.53-4.88), no previously known coronary artery disease (5.46, 3.42-8.71), nonoppressive pain (10.63, 6.04-18.70), and nonretrosternal pain (5.16, 2.82-9.42). For the triage flowchart, both specificity and positive predictive value to rule out ACS were 100%.

Conclusions: The triage flowchart is able to accurately identify patients with CP not having an ACS. It may help triage nurses make quick decisions on who should be immediately seen and who could safely wait when delays in medical attention are unavoidable. Prospective validation is needed.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Algorithms
  • Analysis of Variance
  • Angina, Unstable / diagnosis*
  • Chest Pain / etiology*
  • Cohort Studies
  • Diagnosis, Differential
  • Female
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Myocardial Infarction / diagnosis*
  • Predictive Value of Tests
  • ROC Curve
  • Sensitivity and Specificity
  • Triage / methods*