Résumé
Objective To study the correlation between the changes of matrix metalloproteinase-9(MMP-9)and neutrophil/lymphocyte ratio(NLR)before and after the revascularization of acute ischemic stroke(AIS),so as to find biomarkers to predict the bleeding transformation risk of AIS patients.Methods From February 2022 to December 2022,161 patients admitted to the Stroke Center of Qujing Hospital Affiliated to Kunming Medical University with AIS werre divided in to the hemorrhagic transformation group and the non-hemorrhagic transfor-mation groupand treated with revascularization(intravenous thrombolysis,endovascular treatment,combined the intravenous thrombolysis with endovascular treatment).Among them,there were 46 cases in the hemorrhagic transformation group and 115 cases in the non hemorrhagic transformation group.And the general data,NLR value and MMP-9 before and after the revascularization were compared between the two groups.Results There was no statistical difference in general data between the two groups(all P>0.05)except for C-reactive protein in hemorrhagic transformation group and in non-hemorrhagic transformation group(P<0.001).The white blood cells,neutrophils,neutrophil percentage,neutrophil absolute value,lymphocyte absolute value,NLR and MMP-9 value in hemorrhagic transformation group were significantly higher than those in non-hemorrhagic transformation group before the treatment and there was a statistical significance(P<0.05).After revascularization,the indexes of blood routine and MMP-9 were significantly higher than those before the revascularization,and the increase in hemorrhagic transformation group was more obvious than that in non-hemorrhagic transformation group and there was a statistical significance(P<0.001),The ROC curve showed that the area under the curve(AUC)of NLR and MMP-9 predicting bleeding transformation after AIS revascularization were 0.74 and 0.90.Conclusion NLR,MMP-9 are associated with the risk of bleeding transformation in AIS patients after the revascularization and can they can be used as the predictive factors for bleeding transformation risk.