• Ji Hoon Kim, Yun Ho Roh, Yoo Seok Park, Joon Min Park, Bo Young Joung, In Cheol Park, Sung Phil Chung, and Min Joung Kim.
• Department of Emergency Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722, Seoul, Republic of Korea.
• Scand J Trauma Resus. 2017 Jun 30; 25 (1): 61.

BackgroundThe best treatment approach for ST-segment elevation myocardial infarction (STEMI) is prompt primary percutaneous coronary intervention (PCI). However, some patients show ST elevation on electrocardiography (ECG), but do not have myocardial infarction. We sought to identify the frequency of and to develop a prediction model for false-positive STEMI.MethodsThis study was conducted in the emergency departments (EDs) of two hospitals using the same critical pathway (CP) protocol to treat STEMI patients with primary PCI. The prediction model was developed in a derivation cohort and validated in internal and external validation cohorts.ResultsOf the CP-activated patients, those for whom ST elevation did not meet the ECG criteria were excluded. Among the patients with appropriate ECG patterns, the incidence of false-positive STEMI in the entire cohort was 16.3%. Independent predictors extracted from the derivation cohort for false-positive STEMI were age < 65 years (odds ratio [OR], 2.54; 95% confidence interval [CI], 1.35-4.89), no chest pain (OR, 12.04; 95% CI, 5.92-25.63), atypical chest pain (OR, 7.40; 95% CI, 3.27-17.14), no reciprocal change (OR, 4.80; 95% CI, 2.54-9.51), and concave-morphology ST elevation (OR, 14.54; 95% CI, 6.87-34.37). Based on the regression coefficients, we established a simplified risk score. In the internal and external validation cohorts, the areas under the receiver operating characteristic curves for our risk score were 0.839 (95% CI, 0.724-0.954) and 0.820 (95% CI, 0.727-0.913), respectively; the positive predictive values were 40.9% and 22.0%, respectively; and the negative predictive values were 94.9% and 96.7%, respectively.DiscussionOur prediction model would help them make rapid decisions with better rationale.ConclusionWe devised a model to predict false-positive STEMI. Larger-scale validation studies are needed to validate our model, and a prospective study to determine whether this model is effective in reducing improper primary PCI in actual clinical practice should be performed.

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