Clinical scoring model based on age, NIHSS, and stroke-history predicts outcome 3 months after acute ischemic stroke

作者：Gang-yu Ding, Jianhua Xu, Ji-hong He, Zhiyu Nie · 发表于：Frontiers in Neurology · 年份：2022 · DOI：10.3389/fneur.2022.935150 · 被引用次数：30 · 研究领域：Acute Ischemic Stroke Management、Intracerebral and Subarachnoid Hemorrhage Research、Statistical Methods in Epidemiology

Background The clinical nomogram is a popular decision-making tool that can be used to predict patient outcomes, bringing benefits to clinicians and patients in clinical decision-making. This study established a simple and effective clinical prediction model to predict the 3-month prognosis of acute ischemic stroke (AIS), and based on the predicted results, improved clinical decision-making and improved patient outcomes. Methods From 18 December 2021 to 8 January 2022, a total of 146 hospitalized patients with AIS confirmed by brain MR were collected, of which 132 eligible participants constituted a prospective study cohort. The least absolute shrinkage and selection operator (LASSO) regression was applied to a nomogram model development dataset to select features associated with poor prognosis in AIS for inclusion in the logistic regression of our risk scoring system. On this basis, the nomogram was drawn, evaluated for discriminative power, calibration, and clinical benefit, and validated internally by bootstrap. Finally, the optimal cutoff point for each independent risk factor and nomogram was calculated using the Youden index. Results A total of 132 patients were included in this study, including 85 men and 47 women. Good outcome was found in 94 (71.212%) patients and bad outcome in 38 (28.788%) patients during the follow-up period. A total of eight (6.061%) deaths were reported over this period, of whom five (3.788%) died during hospitalization. Five factors affecting t...