Simple treadmill score to diagnose coronary disease

Objective: Our aim was to derive and validate a simplified treadmill score for predicting the probability of angiographically confirmed coronary artery disease (CAD). Background: The American College of Cardiology/American Heart Association guidelines for exercise testing recommend the use of multivariable equations to enhance the diagnostic characteristics of the standard treadmill test. Most of these equations use complicated statistical techniques to provide diagnostic estimates of CAD. Simplified scores derived from such equations that require physicians only to add points have been developed for pretest estimates of disease and for prognosis. However, no simplified score has been developed specifically for the diagnosis of CAD using exercise test results. Methods: Consecutive patients referred for evaluation of chest pain who underwent standard treadmill testing followed by coronary angiography were studied. A logistic regression model was used to predict clinically significant (≥ 50% stenosis) CAD and then the variables and coefficients were used to derive a simplified score. The simplified score was calculated as follows: (6 × maximal heart rate code) + (5 × ST-segment depression code) + (4 × age code) + angina pectoris code + hypercholesterolemia code + diabetes code + treadmill angina index code. The simplified score had a range from 6 to 95, with < 40 designated as low probability, between 40 and 60 was intermediate probability, and > 60 was high probability for CAD. Results: A total of 1,282 male patients without a prior myocardial infarction underwent exercise treadmill testing and coronary angiography in the derivation group, and there were 476 male patients in the validation group from another institution. The area under the receiver operating characteristic curve (± SE) for the ST-segment response alone was 0.67 as compared to 0.79 ± 0.01 for the diagnostic score (p > 0.001). The prevalence of significant disease for the men was 27% in the low-probability group, 62% in the intermediate-probability group, and 92% in the high-probability group, which was similar to the prevalence in the validation group, with 22%, 58%, and 92% in low-, intermediate-, and high-probability groups, respectively. The low-probability group had < 4% prevalence of severe disease. In both populations, 7 more patients out of 100 were correctly classified than with the use of ST-segment criteria. When used as a clinical management strategy, the score has a sensitivity of 88% and a specificity of 96%. Conclusion: This simplified exercise score that estimates the probability of CAD can be easily applied without a calculator and is a useful and valid tool that can help physicians manage patients presenting with chest pain.