Medline ® Abstract for Reference 17
of 'Evaluation of the adult with chest pain in the emergency department'
How useful are clinical features in the diagnosis of acute, undifferentiated chest pain?
Goodacre S, Locker T, Morris F, Campbell S
Acad Emerg Med. 2002;9(3):203.
OBJECTIVES: To measure the predictive value and diagnostic performance of clinical features used to diagnose coronary syndromes in patients presenting with acute, undifferentiated chest pain.
METHODS: The clinical features of patients presenting to the authors' chest pain unit with acute, undifferentiated chest pain were prospectively recorded on a standard form. Admitted patients were followed up by case note review. Discharged patients were followed up as outpatients three days later. Six months after the emergency department visit, evidence of adverse events was searched for from the hospital computer database, case notes, and the patient's primary care physician. The authors tested the power of each feature to predict: 1) acute myocardial infarction (AMI) by World Health Organization criteria, and 2) any acute coronary syndrome (ACS), evidenced by cardiac testing, AMI, arrhythmia, death, or revascularization procedure within six months.
RESULTS: Eight hundred ninety-three patients were assessed, 34 (3.8%) with AMI and 81 (9.1%) with ACS. Features useful in the diagnosis of AMI were exertional pain [likelihood ratio (LR) = 2.35], pain radiating to the shoulder or both arms (LR = 4.07), and chest wall tenderness (LR = 0.3). Features useful in the diagnosis of ACS were exertional pain (LR = 2.06) and pain radiating to the shoulder, the left arm, or both arms (LR = 1.62). The site or nature of pain and the presence of nausea, vomiting, or diaphoresis were not predictive of AMI or ACS.
CONCLUSIONS: Important differences exist when clinical features are specifically investigated in patients with acute chest pain and a nondiagnostic electrocardiogram. Clinical features have a limited role to play in triage decision making.
Medical Care Research Unit, University of Sheffield, Sheffield, United Kingdom. email@example.com