Review article: Diagnostic accuracy of risk stratification tools for patients with chest pain in the rural emergency department: A systematic review

Emerg Med Australas. 2016 Oct;28(5):511-24. doi: 10.1111/1742-6723.12622. Epub 2016 Jul 28.

Abstract

Risk stratification tools for patients presenting to rural EDs with undifferentiated chest pain enable early definitive treatment in high-risk patients. This systematic review compares the most commonly used risk stratification tools used to predict the risk of major adverse cardiac event (MACE) for patients presenting to rural EDs with chest pain. A comprehensive search of MEDLINE and Embase for studies published between January 2011 and January 2015 was undertaken. Study quality was assessed using QUADAS-2 criteria and the PRISMA guidelines.Eleven studies using eight risk stratification tools met the inclusion criteria. The percentage of MACE in the patients stratified as suitable for discharge, and the percentage of patients whose scores would have recommended admission that did not experience a MACE event were used as comparisons. Using the findings of a survey of emergency physicians that found a 1% MACE rate acceptable in discharged patients, the EDACS-ADP was considered the best performer. EDACS-ADP had one of the lowest rates of MACE in those discharged (3/1148, 0.3%) and discharged one of the highest percentage of patients (44.5%). Only the GRACE tool discharged more patients (69% - all patients with scores <100) but had a MACE rate of 0.3% in discharged patients. The HFA/CSANZ guidelines achieved zero cases of MACE but discharged only 1.3% of patients.EDACS-ADP can potentially increase diagnostic efficiency of patients presenting at ED with chest pain. Further assessment of tool in a rural context is recommended.

Keywords: chest pain; diagnostic accuracy; emergency service; risk score; systematic review.

Publication types

  • Review
  • Systematic Review

MeSH terms

  • Chest Pain / diagnosis
  • Emergency Service, Hospital*
  • Hospitals, Rural*
  • Humans
  • Risk Assessment*