Key result
A diagnostic probability function using a <2% cut-off to rule out acute coronary syndrome demonstrated a sensitivity of 87% and a specificity of 17% in emergency room patients.
Why the study?
Does a diagnostic probability function accurately rule out acute coronary syndrome in patients presenting with chest pain and/or dyspnea?
Observational (n=186)
Yes
Does a diagnostic probability function accurately rule out acute coronary syndrome in patients presenting with chest pain and/or dyspnea?
A diagnostic probability function for ACS showed a sensitivity of 87% and specificity of 17% at a 2% rule-out threshold, but its reliability depends on similarity to the derivation cohort.
Low sensitivity at <2% threshold risks missing ACS cases; leaves open prospective validation before any clinical consideration.
BACKGROUND: We recently reported about the derivation of a diagnostic probability function for acute coronary syndrome (ACS). The present study aims to validate the probability function as a rule-out criterion in a new sample of patients. METHODS: 186 patients presenting with chest pain and/or dyspnea at one of the three participating hospitals' emergency rooms in Switzerland were included in the study. In these patients, information on a set of pre-specified variables was collected and a predicted probability of ACS was calculated for each patient. Approximately two weeks after the initial visit in the emergency room, patients were contacted by phone to assess whether a diagnosis of ACS was established. RESULTS: Of the 186 patients included in the study, 31 (17%) had an acute coronary syndrome. A risk probability for ACS below 2% was considered a rule-out criterion for ACS, leading to a sensitivity of 87% and a specificity of 17% of the rule. The characteristics of the study patients were compared to the cases from which the probability function was derived, and considerable deviations were found in some of the variables. CONCLUSIONS: The proposed probability function, with a 2% cut-off for ruling out ACS works quite well if the patient data lie within the ranges of values of the original vignettes. If the observations deviate too much from these ranges, the predicted probabilities for ACS should be seen with caution.
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Zimmerli et al. (2014) conducted an observational in Acute coronary syndrome (n=186). Diagnostic probability function for acute coronary syndrome vs. Clinical diagnosis of ACS (reference standard) was evaluated on Diagnostic accuracy (sensitivity and specificity) of a <2% predicted probability cut-off for ruling out ACS (Sensitivity 87%, Specificity 17%, 95% CI 70-96 (Sensitivity), 12-24 (Specificity)). A diagnostic probability function using a <2% cut-off to rule out acute coronary syndrome demonstrated a sensitivity of 87% and a specificity of 17% in emergency room patients.
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