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Emerg Med J ; 32(10): 764-8, 2015 Oct.
Article in English | MEDLINE | ID: mdl-25560250

ABSTRACT

BACKGROUND: Acute coronary syndrome (ACS) represents a difficult diagnostic challenge in patients with undifferentiated chest pain. There is a need for a valid clinical score to improve diagnostic accuracy. OBJECTIVES: To compare the performance of a model combining the Thrombolysis in Myocardial Infarction (TIMI) score and a score describing chest pain (ACS diagnostic score: ACSD score) with that of both scores alone in the diagnosis of ACS in ED patients with chest pain associated with a non-diagnostic ECG and normal troponin. METHODS: In this observational cohort study, we enrolled 809 patients admitted to a chest pain unit with normal ECG and normal troponin. They were prospectively evaluated in order to calculate TIMI score, chest pain characteristics score and ACSD score. Diagnosis of ACS was the primary outcome and defined on the basis of 2 cardiologists after reviewing the patient medical records and follow-up data. Mortality and major cardiovascular events were followed for 1 month for patients discharged directly from ED. Discriminative power of scores was evaluated by the area under the ROC curve. RESULTS: ACS was confirmed in 90 patients (11.1%). The area under the ROC curve for ACSD score was 0.85 (95% CI 0.80 to 0.90) compared with 0.74 (95% CI 0.67 to 0.81) for TIMI and 0.79 (95% CI 0.74 to 0.84) for chest pain characteristics score. A threshold value of 9 appeared to optimise sensitivity (92%) and negative predictive value (99%) without excessively compromising specificity (62%) and positive predictive value (23%). CONCLUSIONS: The ACSD score showed a good discrimination performance and an excellent negative predictive value which allows safely ruling out ACS in ED patients with undifferentiated chest pain. Our findings should be validated in a larger multicentre study.


Subject(s)
Acute Coronary Syndrome/diagnosis , Chest Pain/diagnosis , Electrocardiography , Troponin/blood , Acute Coronary Syndrome/blood , Adult , Aged , Biomarkers/blood , Emergency Service, Hospital/statistics & numerical data , Female , Humans , Male , Middle Aged , Myocardial Infarction/diagnosis , Prospective Studies , ROC Curve , Risk Assessment , Risk Factors , Sensitivity and Specificity
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