Preliminary establishment and verification of Nomgram model for individualized prediction of the risk of bleeding in patients with acute cerebral infarction and thrombolysis with alteplase
Objective To analyze the risk factors of bleeding in patients with acute cerebral infarction and thrombolysis with alteplase and to establish corresponding Nomgram risk prediction model.Methods Totally 108 patients with acute cerebral infarction treated with intravenous thrombolysis of alteplase in our hospital from January 2020 to January 2022 were retrospectively analyzed.The clinical data of the patients were collected.Univariate analysis was performed on age,gender,hypertension,hyperlipidemia,baseline of blood glucose,baseline of NIHSS score,smoking history,drinking history etc and whether there were adverse reactions of bleeding after the thrombolysis.Subsequently,Logistic regression model was established to screen the independent risk factors for bleeding after the thrombolysis.Finally,Nomgram risk prediction model was established based on the screened independent risk factors,and the model was verified internally.Results Bleeding occurred in 40 patients after the thrombolysis,old age(OR=2.083,95％CI:1.216～2.950),hypertension(OR=4.402,95％CI:2.001～9.652),high baseline ofNIHSS score(OR=1.615,95％CI:1.150～2.080),and high baseline of blood glucose level(OR=2.561,95％CI:1.440～4.517)were independent risk factors of bleeding after the thrombolysis.According to the four independent risk factors screened,a Nomgram model for individualized prediction of the risk of bleeding in patients with acute cerebral infarction and thrombolysis with alteplase was established.The C-index of the model was 0.738,indicating that the Nomgram model had a good discrimination.After verification of the model,the predicted value and the observed value were basically consistent,showing a good consistency of the prediction model.Conclusion The independent risk factors for bleeding in patients with acute cerebral infarction and thrombolysis with alteplase were screened out to establish a Nomgram model that predicts the risk of adverse reactions of bleeding.This prediction model has good discrimination and consistency,which has important guiding significance for rapid screening of the high-risk population of bleeding in patients with acute cerebral infarction and thrombolysis with alteplase and taking effective measures against possible risk factors.
acute cerebral infarctionalteplaseintravenous thrombolysisrisk factorNomgram model
NETL
NSTL
万方数据
