The Mean Corrected TIMI Frame Count Could Predict Major Adverse Cardiovascular Events in Patients with Coronary Slow-Flow Phenomenon.

Abstract

The aim of the present study was to investigate the association between the mean corrected thrombolysis in myocardial frame count and major adverse cardiovascular events in patients with the coronary slow-flow phenomenon. A total of 98 patients with coronary slow-flow phenomenon who met inclusion cri- teria from 2015 to 2020 were retrospectively included in the analysis. The patients were ranked according to their mean corrected thrombolysis in myocardial frame count values and were divided into quartiles based on those. Group 1 consisted of patients who had a mean corrected thrombolysis in myocardial frame count value >36.68 (third quartile), while group 2 consisted of patients who had a mean corrected thrombolysis in myocardial frame count value ≤36.68 (first quartile+second quartile). Mortality and non-fatal cardiovascular complications were compared between the groups. Mean follow-up duration was 3.93 ± 1.50 years. Recurrent chest pain and major adverse cardiovascular events increased in group 1 compared to group 2 (P ≤ .001, P ≤ .001, respectively). Hypertension (odds ratio 2.627, P=.033), hyperlipidemia (odds ratio 2.469, P = .028) and mean corrected thrombolysis in myocardial frame count (odds ratio 1.106, P = .002) were independent predictors of recurrent chest pain according to Cox regression analysis. Although older age (odds ratio 1.125, P=.011), hypertension (odds ratio 6.081, P=.026), hyperlipidemia (odds ratio 12.308, P = 0.019), and mean corrected thrombolysis in myocardial frame count (odds ratio 1.476, P = .001) were found to be significantly related with major adverse cardiovascular events in patients with coronary slow-flow phenomenon, only mean corrected thrombolysis in myocardial frame count (odds ratio 1.161, P = .021) was an indepen- dent predictor of major adverse cardiovascular events in Cox regression analysis. Higher mean corrected thrombolysis in myocardial frame count could predict major adverse cardiovascular events in patients with the coronary slow-flow phenomenon.