Abstract:
Objective To investigate the influencing factors of poor prognosis after intravenous thrombolytic therapy with recombinant tissue plasminogen activator(rt-PA) in patients with acute ischemic stroke(AIS), and construct a nomogram risk prediction model.
Methods A total of 123 AIS patients treated with intravenous thrombolytic therapy with rt-PA were selected as the study subjects, and were followed up for 3 months after treatment.According to the mRS scores, the patients were divided into the good prognosis group and poor prognosis group.The influencing factors of poor prognosis were analyzed by univariate and multivariate logistic models.The statistically significant variables in regression analysis were used as predictors, and the R language was used to construct a nematic risk prediction model for poor prognosis of AIS patients after rt-PA intravenous thrombolytic therapy, and the model was verified.
Results After 3 months of rt-PA intravenous thrombolytic therapy, 97 patients(78.86%) had a good prognosis, and 26 patients(21.14%) had a poor prognosis.The results of multivariate analysis showed that high GCS score, high NIHSS score before thrombolysis and high NLR value at admission were all risk factors of poor prognosis of AIS patients after rt-PA intravenous thrombolysis(P < 0.05 to P < 0.01).The results of model predicted that the area under the curve of AIS patients with poor prognosis after rt-PA intravenous thrombolysis was 0.897 (95%CI: 0.827-0.968), the sensitivity was 84.6%, and the specificity was 90.7%.The Bootstrap method repeated sampling 1 000 times to verify the column diagram, and which showed that the average absolute error before and after the internal verification of the prediction model in this column was 0.032.
Conclusions The high pre-thrombolytic GCS score, NIHSS score and NLR level elevating are the risk factors of poor prognosis of AIS patients treated with rt-PA intravenous thrombolysis.The nomogram risk prediction model based on the above risk factors has high clinical accuracy in predicting the prognosis of the AIS patients treated with rt-PA thrombolysis.