A novel nomogram to predict hemorrhagic transformation in ischemic stroke patients after intravenous thrombolysis - Yang, Miaomiao; Zhong, Wei; Zou, Wenhui; Peng, Jingzi; Tang, Xiangqi (Frontiers in Neurology, 2022)
Background Hemorrhagic transformation (HT) is the most serious complication of ischemic stroke patients after intravenous thrombolysis and leads to a poor clinical prognosis. This study aimed to determine the independent predictors associated with HT in stroke patients with intravenous thrombolysis and to establish and validate a nomogram that combines with predictors to predict the probability of HT after intravenous thrombolysis in patients with ischemic stroke. Method This study enrolled ischemic stroke patients with intravenous thrombolysis from December 2016 to June 2022. All the patients were divided into training and validation cohorts. The nomogram was composed of the significant predictors for HT in the training cohort obtained by the multivariate logistic regression analysis. The area under the receiver operating characteristic curve was used to assess the discriminative performance of the nomogram. The calibration performance of the nomogram was assessed by Hosmer-Lemeshow goodness-of-fit test and calibration plots. Decision curve analysis was used to test the clinical validity of the nomogram. Results A total of 394 patients with intravenous thrombolysis were enrolled in the study. In the training cohort (n=257), 45 patients have HT after intravenous thrombolysis. Multivariate logistic regression analysis demonstrated early infarct signs (OR, 7.954; 95% CI, 3.553-17.803; P < 0.001), NIHSS scores (OR, 1.110; 95% CI, 1.054-1.168; P < 0.001), uric acid (OR, 0.993; 95% CI, 0.989-0.997; P = 0.001), and albumin-to-globulin ratio (OR, 0.109; 95% CI, 0.023-0.508; P = 0.005) were independent predictors for HT and constructed the nomogram. In the training and validation cohorts, the AUC of the nomogram was 0.859 and 0.839, respectively. The Hosmer-Lemeshow goodness-of-fit test and calibration plot showed good concordance between predicted and observed probability in the training and validation cohort. Decision curve analysis indicated that the nomogram was significantly useful for predicting HT in the training and further confirmed in the validation cohort. Conclusion This study proposes a novel and practical nomogram based on early infarct signs, NIHSS scores, uric acid, and albumin-to-globulin ratio that can well predict the probability of HT after intravenous thrombolysis in patients with ischemic stroke.