| ObjectiveThe objective of this study was to explore factors that affect ischemic stroke(AIS)patients who ischemic ischemic stroke(ischemic stroke)from intravenous thrombolysis after 3 months of disease.The prognosis prediction model of intravenous thrombolysis was established to provide guidance for clinical prognosis.MethodsA total of 420 patients with AIS who received intravenous thrombolysis in the Department of Neurology,Affiliated Hospital of Nantong University,Jiangsu Province from January 2020 to December 2021 were retrospectively included in this study.Patients with thrombolysis were followed up with modified Rankin Scale(m RS)scores at 3 months after onset and divided into good prognosis group(m RS Score 0-2)and poor prognosis group(m RS Score 3-6).General data,past history and laboratory data were collected at admission and compared with baseline data of the two groups.Meaningful correlation factors in univariate analysis were incorporated into multivariate binary unconditioned Logistic regression analysis to determine the independent influencing factors of poor prognosis in patients with AIS.The area under curve(AUC)was used to evaluate the differentiation of each influencing factor.AUC < 0.60 indicated low differentiation,AUC 0.60-0.75 indicated medium differentiation,and AUC > 0.75 indicated high differentiation.Hosmer-Lemeshow method was used to calculate the goodness of fit,and the test level α=0.05.The statistical tests were all two-sided tests,and p > 0.05 indicated that the model had a good fitting effect.According to the weight of each independent factor,a linear graph model was constructed to predict the risk of poor prognosis of thrombolysis.Calibration curves,DCA and CIC were drawn respectively to verify the differentiation,calibration and clinical applicability of the model.Results1.A total of 420 patients with AIS intravenous thrombolysis were included in this study,including 258 patients in the good prognosis group and 162 patients in the poor prognosis group.Compared with the good prognosis group,the poor prognosis group had a higher proportion of older patients,a higher proportion of males,and a higher proportion of patients with a history of atrial fibrillation.In the poor prognosis group,the heart rate was faster,the NIHSS score before thrombolysis was higher,the proportion of mechanical thrombectomy was higher,and the proportion of large-area cerebral infarction was higher.The main responsible vessel for cerebral infarction was middle cerebral artery occlusion,the most common type was cardiogenic embolization,and the proportion of lacunar infarction was higher in the OCSP classification.The average white blood cell count,neutrophil count,glucose,aspartate aminotransferase and serum potassium ionized water in poor prognosis group were significantly higher than those in good prognosis group,while the average hemoglobin,glycosylated hemoglobin,serum sodium ion and magnesium ionized water in poor prognosis group were significantly lower than those in good prognosis group,with statistical significance(p < 0.05).2.Variables with p < 0.05 in univariate analysis were included in multivariate Logistic regression analysis,and age(OR=1.094,95%CI1.053-1.136,p < 0.001),NIHSS score before thrombolysis(OR=1.137,95% CI1.072-1.205,p < 0.001),serum magnesium ion(OR=0.950,95%CI 0.908-0.994,p = 0.026),large cerebral infarction(OR=2.593,95%CI1.217-5.522,p =0.014)was an independent factor affecting the occurrence of poor prognosis in AIS patients after 3 months of intravenous thrombolysis.3.The risk prediction model was established based on age,pre-thrombolysis NIHSS score,serum magnesium ion and large cerebral infarction.The areas under ROC curve of these four independent factors were(0.703,p < 0.001)(0.828,p < 0.001)(0.576,p = 0.026)(0.690,p = 0.014),indicating good predictive ability.Hosmer-Lemeshow method was used to calculate the goodness of fit(χ2=9.957,df=8,p = 0.268),indicating that the model had a good fitting effect.After calibration curve,clinical decision curve and CIC test,this model has good differentiation,calibration and clinical applicability.This indicates that the constructed linear diagram model has good clinical application value in predicting the poor prognosis of AIS patients after thrombolysis.Conclusion1.Age,NIHSS score before thrombolysis,serum magnesium ion,and large cerebral infarction were independent factors influencing poor prognosis in patients with AIS intravenous thrombolysis at 3 months.Age,pre-thrombolysis NIHSS score and large cerebral infarction were risk factors for the prognosis of intravenous thrombolysis,while serum magnesium ion level was a protective factor for the prognosis of intravenous thrombolysis.2.The risk prediction model constructed by age,NIHSS score before thrombolysis,serum magnesium ion and large cerebral infarction can better predict the risk of poor prognosis after 3 months of AIS intravenous thrombolysis,which has certain clinical practical value. |
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