Predictive potential of noninvasive methods, inclusive of exercise SPECT Tc99m MIBI imaging, in recognition of high-risk patients with left main coronary artery stenosis.

The aim of the present study was to determine which clinical, exercise and perfusion variables can be instrumental in the identification of left main coronary artery. A multivariate model for prediction of left main disease was developed, based on a number of clinical, exercise and MIBI perfusion variables in two groups of patients. Group I consisted of 38 patients (30 men and eight women) with angiographically proven left main stenosis, while group II consisted of 41 patients (27 men and 14 women) with multivessel coronary artery diseases. A multivariate logistic regression analysis demonstrated that clinical variables including diabetes, hypertension, together with history of typical angina were the only independent predictors of left main stenosis. It was found that p value was 0.05 for hypertension, 0.01 for diabetes as well as 0.01 for the history of typical angina in clinical examination. No exercise or perfusion variables may be instrumental in prediction of left main stenosis, when considered in isolation. Myocardial perfusion by itself is therefore not deemed sufficiently specific to attempt its positive identification. High-risk patients with left main disease can be identified noninvasively by exercise perfusion imaging using a model based on the proposed logistic regression analysis with clinical variables.