A Novel Nomogram to Predict Symptomatic Intracranial Hemorrhage in Ischemic Stroke Patients After Intravenous Thrombolysis

一种预测缺血性卒中患者静脉溶栓后症状性颅内出血的新型列线图

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Abstract

OBJECTIVE: This study aimed to create and validate a novel nomogram to predict the risk of symptomatic intracranial hemorrhage (sICH) in patients with acute ischemic stroke (AIS) who underwent intravenous thrombolysis (IVT). METHODS: In this retrospective study, 784 patients with AIS who received IVT were enrolled. The patients were randomly divided into two groups: a training set (n=550, 70%) and a testing set (n=234, 30%). Utilizing multivariable logistic regression analysis, relevant factors for the predictive nomogram were selected. The performance of the nomogram was evaluated using various metrics, including the area under the receiver operating characteristic curve (AUC-ROC), the Hosmer-Lemeshow goodness-of-fit test, calibration plots, and decision curve analysis (DCA). RESULTS: Multivariable logistic regression analysis showed that specific factors, including National Institutes of Health Stroke Scale (NIHSS) scores, Early infarct signs (EIS), and serum sodium, were identified as independent predictors of sICH. Subsequently, a nomogram was constructed using these predictors. The AUC-ROC values of the nomogram were 0.864 (95% CI: 0.810-0.919) and 0.831 (95% CI: 0.770-0.891) in the training and the validation sets, respectively. Both the calibration plots and the Hosmer-Lemeshow goodness-of-fit test showed favorable agreement in both the training and the validation sets. Additionally, the DCA indicated the practical clinical utility of the nomogram. CONCLUSION: The novel nomogram, which included NIHSS, EIS and serum sodium as variables, had the potential for predicting the risk of sICH in patients with AIS after IVT.

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