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PP23 Accuracy of emergency medical services (EMS) telephone triage in identifying acute coronary syndrome (ACS) for chest pain patients. A systematic review abstract
  1. Ahmed Alotaibi1,2,
  2. Abdulrhman Alghamdi1,2,
  3. Charles Reynard1,3,
  4. Richard Body1,3
  1. 1Division of Cardiovascular Sciences, University of Manchester, UK
  2. 2College of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
  3. 3Emergency Department, Manchester University NHS Foundation Trust, UK

Abstract

Introduction Chest pain is one of the most common reasons for ambulance callouts and presentation to Emergency Departments (EDs). Differentiating patients with serious conditions (e.g. acute coronary syndrome [ACS]) from the majority, who have self-limiting, non-cardiac conditions is extremely challenging. This causes over-triage and over-use of healthcare resources. We aimed to systematically review existing evidence on the accuracy of emergency telephone triage to detect ACS or life-threatening conditions associated with chest pain.

Methods We conducted a systematic review in accordance with PRISMA guidelines. Two independent investigators searched the Embase, Medline, and Cinahl databases for relevant papers. We included retrospective and prospective cohort studies written in English and investigating EMS telephone triage for chest pain patients linked with final diagnosis of ACS. Studies were summarised in a narrative format as the data were not suitable for meta-analysis.

Result In total, 553 studies were identified from the literature search and cross-referencing. After excluding 550 studies, three were eligible for inclusion. Among those 3 studies, there are different prediction models developed by authors with variation in variables to detect ACS. The result showed that dispatch triage tools have good sensitivity to detect ACS and life-threatening conditions although they are used to triage sign and symptoms rather than diagnosing the patients. On the other hand, prediction models were built to detect ACS and life-threatening conditions and therefore it showed better sensitivity and NPV.

Conclusion EMS dispatch systems accuracy for ACS and life-threatening conditions associated with chest pain is good. Since the dispatch tools were built to triage ambulance response priority based on sign and symptoms, this led to over triage among non-life-threatening chest pain patients. Over triage were slightly reduced by deriving prediction models and showed better sensitivity.

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