Key result
The ACI-TIPI risk stratification tool demonstrated similar overall accuracy for predicting acute coronary syndrome in U.S. and Singapore patients (AUC 0.729 vs. 0.719; p=0.5611).
Why the study?
Does the ACI-TIPI risk stratification tool perform similarly in predicting ACS in U.S. versus Singapore patients with chest pain?
Observational (n=11,991)
Yes
Does the ACI-TIPI risk stratification tool perform similarly in predicting ACS in U.S. versus Singapore patients with chest pain?
Absolute Event Rate: 0.729% vs 0.719%
p-value: p=0.5611
While the ACI-TIPI risk stratification tool showed similar overall accuracy in U.S. and Singapore cohorts, differences in the predictive power of individual factors highlight the need for international validation of cardiac clinical decision rules.
Supports similar ACI-TIPI performance across populations; leaves open refinement of individual predictors for international use.
OBJECTIVES: Most contemporary cardiac risk stratification tools have been derived and validated in mixed-race populations. Their validity in single-race populations has not been tested. The authors sought to compare the performance of a risk stratification tool between a mixed-race U.S. patient population and an Asian patient population. METHODS: This study is an analysis of data from the Internet Tracking Registry for Acute Coronary Syndromes (i(*)trACS) registry of patients with chest pain presenting to the emergency departments of eight U.S. centers and one site in Singapore. The Acute Cardiac Ischemia Time-Insensitive Predictive Instrument (ACI-TIPI) was computed for included patients, and its performance in predicting acute coronary syndrome (ACS) was compared between patients from the United States and Singapore. RESULTS: Of the 11,991 included patients, 1,120 experienced ACS. Although the ACI-TIPI demonstrated similar accuracy among groups (area under the curve, 0.729 [U.S.] vs. 0.719 [Singapore]; p = 0.5611), sensitivity and specificity were different when equal ACI-TIPI thresholds were considered. Recreating the logistic regression models used to create the ACI-TIPI showed similar results between the derived parameters and the parameters estimated for the U.S. group. In contrast, age older than 50 years (log-odds ratio [LOR], 0.107; 95% confidence interval [CI] = 0.518 to 0.713), male gender (LOR, 0.487; 95% CI = 0.149 to 1.122), and chest pain as a primary complaint (LOR, 0.237; 95% CI = 0.139 to 0.613) had little predictive power in patients from Singapore. CONCLUSIONS: Differences exist in presentation and factors associated with ACS among patients from the United States and Singapore that may affect the performance of risk stratification tools. These findings suggest that cardiac clinical decision rules need international validation.
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Miller et al. (2005) conducted an observational in Chest pain (n=11,991). ACI-TIPI in U.S. patients vs. ACI-TIPI in Singapore patients was evaluated on Accuracy in predicting acute coronary syndrome (ACS) measured by area under the curve (p=0.5611). The ACI-TIPI risk stratification tool demonstrated similar overall accuracy for predicting acute coronary syndrome in U.S. and Singapore patients (AUC 0.729 vs. 0.719; p=0.5611).
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