Department of Neurology, the Second Affiliated Hospital of Soochow University and Clinical Research Center of Neurological Disease, Suzhou, China.
Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China.
J Stroke Cerebrovasc Dis. 2023 Apr;32(4):107037. doi: 10.1016/j.jstrokecerebrovasdis.2023.107037. Epub 2023 Feb 4.
We aimed to develop and validate a clinical score to identify the factors which contribute to variation in, and influence clinician's decision-making about treating acute ischemic stroke (AIS) patients with Intravenous thrombolysis (IVT).
We retrospectively included consecutive AIS patients within 4.5 hours after onset in the emergency department (ED), who were admitted to a comprehensive stroke center in Jiangsu province, China. The patients were randomly divided into derivation (60%) and validation data sets (40%) to develop and validate the clinical score. Multivariable stepwise forward logistic regression was performed to identify the independent predictors of IVT offering in the derivation data.
Out of 526 included patients, 418 patients received thrombolytic therapy. Nine patient factors were associated with the likelihood of thrombolysis (age, time to hospital, National Institute of Health stroke scale (NIHSS) score, great vessel, facial paralysis, dizziness, headache, history of stroke, and neutrophil ratio). The c-statistics of the Intravenous Thrombolysis Score in the derivation cohort (n= 316) and validation cohort(n = 210) were 0.795 and 0.751, respectively. The performance of the scoring model was validated with a calibration plot showing good predictive accuracy for the scores in the derivation data (calibrated P = 0.861) and validation data (calibrated P = 0.876).
The Intravenous Thrombolysis Score for predicting the possibility of offering IVT to AIS patients indicates that clinicians differ in their thresholds for the treatment across a number of patient-related factors, which will be linked to training professional development programmes and address the impact of non-medical influences on decision-making using evidence-based strategies.
我们旨在开发和验证一种临床评分,以确定影响急性缺血性卒中(AIS)患者接受静脉溶栓治疗(IVT)的因素及其变化,并影响临床医生的决策。
我们回顾性纳入了发病后 4.5 小时内在急诊科(ED)就诊的连续 AIS 患者,这些患者被收入中国江苏省的一家综合卒中中心。将患者随机分为推导(60%)和验证数据集(40%),以开发和验证临床评分。多元逐步向前逻辑回归用于确定推导数据中提供 IVT 的独立预测因子。
在 526 例纳入患者中,有 418 例接受了溶栓治疗。9 个患者因素与溶栓可能性相关(年龄、到医院的时间、国立卫生研究院卒中量表(NIHSS)评分、大血管、面瘫、头晕、头痛、卒中史和中性粒细胞比率)。推导队列(n=316)和验证队列(n=210)的静脉溶栓评分的 c 统计量分别为 0.795 和 0.751。评分模型的性能通过校准图进行验证,显示出对推导数据中分数的良好预测准确性(校准 P=0.861)和验证数据(校准 P=0.876)。
用于预测向 AIS 患者提供 IVT 可能性的静脉溶栓评分表明,临床医生在许多与患者相关的因素方面,在治疗阈值上存在差异,这将与专业发展计划的培训相关联,并使用基于证据的策略解决非医疗影响对决策的影响。