An alternative tool for triaging patients with possible acute coronary symptoms before admission to a chest pain unit

This study aimed to develop a triage tool to more effectively triage possible ACS patients presenting to the emergency department (ED) before admission to a protocol-driven chest pain unit (CPU).

Seven hundred ninety-three clinical cases, randomly selected from 7962 possible ACS cases, were used to develop and test an ACS triage model using cluster analysis and stepwise logistic regression.

The ACS triage model, logit (suspected ACS patient)=-5.283+1.894×chest pain+1.612×age+1.222×male+0.958×proximal radiation pain+0.962×shock+0.519×acute heart failure, with a threshold value set at 2.5, was developed to triage patients. Compared to four existing methods, the chest-pain strategy, the Zarich's strategy, the flowchart, and the heart broken index (HBI), the ACS triage model had better performance.

This study developed an ACS triage model for triaging possible ACS patients. The model could be used as a rapid tool in EDs to reduce the workloads of ED nurses and physicians in relation to admissions to the CPU.