Establishment and verification of a Normograph prediction model for early neurological deterioration(END)after intravenous thrombolysis(IVT)in stroke
Objective To explore the risk factors of early neurologic deterioration(END)after intravenous thrombolysis(IVT)in stroke and establish a Normo diagram prediction model for verification.Methods Clinical data of 182 stroke patients admitted to the hospital from May 2020 to May 2023 were retrospectively ana-lyzed.All patients received thrombolytic therapy with recombinant tissue plasminogen activator(rt-PA).According to the occurrence of END after thrombolysis,patients could be divided into END group(n=52)and non-End group(n=130).The clinical data of the 2 groups were compared,and the risk factors of END were identified by binary Logistic regression analysis.The independent risk factors were introduced into R software to build the risk nomogram,and the model differentiation was verified by Bootstrap meth-od.Calibration curve and receiver operating characteristic(ROC)curve were drawn to evaluate the fit and prediction efficiency.Results The proportion of previous cerebral infarction,National Institutes of Health Stroke Scale(NIHSS)score at admission,the time from onset to thrombolysis,the time of thrombolysis,the proportion of severe stenosis of responsible vessels,the levels of HbA1c,white blood cell count(WBC)and neutrophil/lymphocyte ratio(NLR)in the END group were higher than those in the non-END group.Hemoglobin(Hb)and prognostic Nutritional Index(PNI)levels were lower than those in non-END group(P＜0.05).Binary Logistic regression model showed that high NIHSS score,high HbA1c,severe stenosis of responsible vessels,high NLR and low PNI on admission were independent risk factors for END after IVT stroke(P＜0.05).The prediction model equation of the END of stroke after IVT was established based on independent risk factors.Bootstrap method was used to verify the prediction model internally.The results showed that the model had good differentiation and calibration curve showed that the model had good fit.The AUC of Nomograph prediction model with independent risk factors was 0.928(95％CI:0.880～0.961,P＜0.05),and the prediction efficiency was better than that of PNI and NLR prediction alone(P＜0.05).Conclusion NIHSS score on admission,HbA1c,degree of responsible ves-sel stenosis,NLR and PNI are the influencing factors leading to the occurrence of END after IVT of stroke.The Nomograph prediction model built on this basis has good differentiation and fit,and it has high predictive value for the occurrence of END.
strokeneurological deteriorationprognostic nutritional indexneutrophil/lymphocyte ratioprediction model
万方数据
维普
