Predictions DO NOTHING TO GET SURVIVORS RECOVERED! I'd have you all fired!
A new nomogram for predicting 90-day outcomes of intravenous thrombolysis in patients with acute ischaemic stroke
Yingjie Zhao
Rui Zhang- Department of Clinical Laboratory, North China University of Science and Technology Affiliated Hospital, Tangshan, China
Background: The 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).
Methods: A 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.
Results: Multifactorial 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.
Conclusion: New 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.
1 Introduction
Stroke, a sudden neurological disorder, is a leading cause of disability and death in adults (1). Among stroke cases, acute ischemic stroke (AIS) accounts for 60 to 80% (2). Intravenous thrombolysis with recombinant tissue-type plasminogen activator (rt-PA) within 4.5 h of onset of symptoms is the treatment of choice and significantly improves neurological function in patients (3). However, a certain percentage of patients continue to experience poor prognostic outcomes (4). Therefore, the early identification of patients at risk for poor outcome, along with timely and accurate therapeutic interventions, is crucial for improving patient recovery and outcomes (5, 6). A nomogram is a visual scoring model that utilizes biological and clinical variables to accurately calculate the probability of an individual patient’s risk for a specific clinical event (7). The chart is widely used for clinical decision-making in a wide range of conditions (8, 9). Nomograms surpass traditional scoring systems in their ability to more accurately identify patients with poor outcome, assist in selecting optimal treatment options, and enhance the quality of patient survival (10). The aim of this study was to construct a nomogram to predict the risk probability of poor outcome in AIS patients following intravenous thrombolytic therapy.
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