AIM To test accuracy and reproducibility of gestalt to predict obstructive coronary artery disease(CAD)in patients with acute chest pain.METHODS We studied individuals who were consecutively admitted to our Chest Pain Unit.At admission,investigators performed a standardized interview and recorded14 chest pain features.Based on these features,a cardiologist who was blind to other clinical characteristics made unstructured judgment of CAD probability,both numerically and categorically.As the reference standard for testing the accuracy of gestalt,angiography was required to rule-in CAD,while either angiography or non-invasive test could be used to rule-out.In order to assess reproducibility,a second cardiologist did the same procedure.RESULTS In a sample of 330 patients,the prevalence of obstructive CAD was 48%.Gestalt’s numerical probability was associated with CAD,but the area under the curve of0.61(95%CI:0.55-0.67)indicated low level of accuracy.Accordingly,categorical definition of typical chest pain had a sensitivity of 48%(95%CI:40%-55%)and specificity of 66%(95%CI:59%-73%),yielding a negligible positive likelihood ratio of 1.4(95%CI:0.65-2.0)and negative likelihood ratio of 0.79(95%CI:0.62-1.02).Agreement between the two cardiologists was poor in the numerical classification(95%limits of agreement=-71%to 51%)and categorical definition of typical pain(Kappa=0.29;95%CI:0.21-0.37).CONCLUSION Clinical judgment based on a combination of chest pain features is neither accurate nor reproducible in predicting obstructive CAD in the acute setting. AIM To test accuracy and reproducibility of gestalt to predict obstructive coronary artery disease (CAD) in patients with acute chest pain. METHODS: study in a patient who were consecutively admitted to our Chest Pain Unit. Admission, investigators performed a standardized interview and recorded 14 chest pain features.Based on these features, a cardiologist who was blind to other clinical characteristics made unstructured judgment of CAD probability, both numerically and categorically. As the reference standard for testing the accuracy of gestalt, angiography was required to rule-in CAD, while angiography or non-invasive test could be used to rule- out. In order to assess reproducibility, a second cardiologist did the same procedure. RESULTS In a sample of 330 patients, the prevalence of obstructive CAD was 48% .Gestalt’s numerical probability was associated with CAD, but the area under the curve of 0.61 (95% CI: 0.55-0.67) indicated low level of accuracy. Accreditedly, categorical definition of The typical chest pain had a sensitivity of 48% (95% CI: 40% -55%) and specificity of 66% (95% CI: 59% -73% 0.65-2.0) and negative likelihood ratio of 0.79 (95% CI: 0.62-1.02) .Agreement between the two cardiologists was poor in the numerical classification (95% limits of agreement = -71% to 51%) and categorical definition of typical pain (Kappa = 0.29; 95% CI: 0.21-0.37) .CONCLUSION Clinical judgment based on a combination of chest pain features is not accurate nor reproducible in predicting obstructive CAD in the acute setting.