A new nomogram for predicting 90-day outcomes of intravenous thrombolysis in patients with acute ischaemic stroke - Zhao, Yingjie; Zhang, Rui; Li, Pan; Zhang, Zhen; Yu, Huan; Su, Zhaoya; Xia, Yandong; Meng, Aiguo (Frontiers in Neurology, 2025)
BackgroundThe aim of this study was to construct and validate a new nomogram to predict the risk of poor outcome in patients with acute ischemic stroke (AIS) after intravenous thrombolytic therapy (IVT).MethodsA total of 425 patients who received IVT within 4.5 h of stroke onset were included in a retrospective study. All the patients were divided into training (70%, n = 298) and validation cohorts (30%, n = 127). Poor outcome (defined as a 90-day modified Rankin Scale score 3–5) was the primary outcome. Logistic regression was used for analysis of independent risk factors for poor outcome in patients with AIS. Nomograms of poor outcome in AIS patients were constructed using R software. Discrimination and calibration of the models were assessed using area under the receiver operating characteristic (ROC) curve (AUC) and calibration plots.ResultsMultifactorial logistic regression analysis showed that SII (OR = 1.001, 95% CI: 1.000–1.002, p = 0.008), SIRI (OR = 1.584, 95% CI: 1.122–2.236, p = 0.009), NIHSS (OR = 1.101, 95% CI: 1.044–1.160, p < 0.001), and history of diabetes mellitus (OR = 2.582, 95% CI: 1.285–5.188, p = 0.008) were the independent risk factors for the occurrence of poor outcome in AIS patients. The poor outcome nomogram for AIS patients was constructed based on the above independent risk factors. The training and validation cohort AUCs of the nomogram were 0.854 (95% CI: 0.807–0.901) and 0.855 (95% CI: 0.783–0.927), respectively. The prediction models were well calibrated in both the training and validation cohorts. The net benefit of the nomograms was better when the threshold probability ranges were 4.28–66.4% and 4.01–67.8% for the training and validation cohorts, respectively.ConclusionNew nomogram includes NIHSS, SII, SIRI and diabetes as variables with the potential to predict the risk of 90-day outcomes in patients with AIS following IVT.