Background: A considerable proportion of acute noncardiogenic ischemic stroke patients continue to experience recurrent ischemic events after standard therapy.
Aim: We aimed to identify risk factors for recurrent ischemic event prediction at an early stage. Methods: 286 non-cardioembolic ischemic stroke patients with the onset of symptoms within 24 hours were enrolled. Vascular risk factors, routine laboratory data on admission, thromboelastography test seven days after clopidogrel therapy and any recurrent events within one year were assessed. Patients were divided into case group (patients with clinical adverse events, including ischemic stokes, transient ischemic attack, myocardial infarction and vascular related mortality) and control group (events-free patients). The risk of the recurrent ischemic events was determined by the receiver operating characteristic curve and multivariable logistic regression analysis. Results: Clinical adverse events were observed in 43 patients (case group). The mean levels of Mean Platelet Volume (MPV), Platelet/Lymphocyte Ratio (PLR), Lymphocyte Count (LY) and Fibrinogen (Fib) on admission were significantly higher in the case group as compared to the control group (P<0.001). Seven days after clopidogrel therapy, the ADP-induced platelet inhibition rate (ADP%) level was lower in the case group, while the Maximum Amplitude (MA) level was higher in the case group as compared to the control group (P<0.01). The Area Under the Curve (AUC) of receiver operating characteristic(ROC) curve of LY, PLR, , Fib, MA, ADP% and MPV were 0.602, 0.614, 0.629, 0.770, 0.800 and 0.808, respectively. The logistic regression analysis showed that MPV, ADP% and MA were indeed predictive factors. Conclusion: MPV, ADP% and MA were risk factors of recurrent ischemic events after acute noncardiogenic ischemic stroke. Urgent assessment and individual drug therapy should be offered to these patients as soon as possible.Keywords: Ischemic stroke, ischemic event, receiver operating characteristic curve, logistic regression analysis, risk factors, prediction.