Assessment of Admission Time Cell Blood Count (CBC) Parameters in Predicting Post-primary Percutaneous Coronary Intervention TIMI Frame Count in Patients with ST-segment Elevation Myocardial Infarction

Objectives: In this study, we aimed to assess the value of admission time CBC parameters in predicting post-primary PCI corrected TIMI frame count. Background: Recent years have witnessed a large series of studies evaluating different laboratory variables to predict no-reflow phenomenon following primary PCI (PPCI) in patients with STEMI. However, a general agreement about the most reliable predictor of the no-reflow phenomenon is challenging and also intriguing. Methods: The current study concluded 208 consecutive patients who underwent primary PCI for ST-Elevation Myocardial Infarction (STEMI) from January 2014 to February 2016. Blood samples were obtained after taking ECG. Complete blood samples were collected and analyzed within 5 minutes from sampling. Post-PCI corrected Thrombolysis in Myocardial Infarction (TIMI) frame count was determined by one interventional cardiologist blinded to patients’ clinical data. The correlation between admission time blood parameters and post-primary PCI corrected TIMI frame count in patients with STEMI were assessed. Results: Corrected TIMI frame count was positively correlated with WBC count (R: 0.18, P-value: <0.01), neutrophil count (R: 0.34, P-value: <0.01), and platelet count (R: 0.23, P-value: <0.01) and negatively correlated with lymphocyte count (R: -0.2, P-value: <0.01). Multiple linear regression results demonstrated that corrected TIMI frame count was positively correlated with neutrophil count (P < 0·001) and platelet count (P < 0·001) and negatively correlated with lymphocyte count (p=0.004). Conclusion: High counts of WBC, neutrophil, and platelet and low count of lymphocyte may be predictors of no-reflow in STEMI patients undergoing PPCI. The clinical significance of such predictive parameters becomes clear as we consider the treatment approach in STEMI patients. Appropriate risk stratification leads to better treatment planning and allocation of resources.