RESUMO
BACKGROUND: Thrombin, a key enzyme of the clotting system, is involved in thrombus formation, platelet activation, and atherosclerosis, thereby possessing a central role in the pathogenesis of ischemic heart disease. Studies have shown an association between thrombin generation (TG) and cardiovascular morbidity and mortality, but results have been equivocal. Our aim was to study the predictive ability of TG assay in evaluating coronary stenosis severity. METHODS: In this prospective study we recruited patients with acute coronary syndrome (ACS) or acute chest pain (without evidence of myocardial injury) planned for coronary angiography. Thrombin generation was evaluated by Calibrated Automated Thrombogram (CAT) prior to angiography. Primary end points were significant coronary stenosis and the Syntax I score evaluated by coronary angiography. RESULTS: From April 2018 through September 2019, we recruited 128 patients. In the primary analysis there was no significant association between TG and significant coronary stenosis nor between TG and syntax I score, however, there was a positive correlation between peak height and troponin peak (Spearman correlation coefficient 0.194, P-value = 0.035). In sub-group analysis, the chest pain group bare no association between TG and coronary stenosis. In unstable angina group there was an association between peak height and significant coronary stenosis (P-value = 0.029), and in non ST-elevation myocardial infarction group, TG values possessed a relatively good predictive ability of significant coronary stenosis (area under the receiver operating characteristic curve of ~65%) and a positive correlation between both lag time and ttpeak with the syntax I score was noticed (Spearman correlation coefficient 0.31, P-value = 0.099 and Spearman correlation coefficient 0.37, P-value = 0.045 respectively). CONCLUSION: In patients with acute chest pain, TG values, evaluated by CAT, do not predict severity of coronary stenosis, nor do they possess prognostic value. Yet, in ACS patients, TG may have the ability to predict coronary disease severity.
