Csók István, Grauvogel Jürgen, Scheiwe Christian, Bardutzky Jürgen, Wehrum Thomas, Beck Jürgen, Reinacher Peter C, Roelz Roland
Department of Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Department of Neurology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Front Neurol. 2022 Mar 2;13:774720. doi: 10.3389/fneur.2022.774720. eCollection 2022.
To establish a practical risk chart for prediction of delayed cerebral infarction (DCI) after aneurysmal subarachnoid hemorrhage (aSAH) by using information that is available until day 5 after ictus.
We assessed all consecutive patients with aSAH admitted to our service between September 2008 and September 2015 ( = 417). The data set was randomly split into thirds. Two-thirds were used for model development and one-third was used for validation. Characteristics that were present between the bleeding event and day 5 (i.e., prior to >95% of DCI diagnoses) were assessed to predict DCI by using logistic regression models. A simple risk chart was established and validated.
The amount of cisternal and ventricular blood on admission CT (), early (i.e., mean flow velocity of either intracranial artery >160 cm/s until day 5), and a simplified binary score until day 5 were the strongest predictors of DCI. A model combining these predictors delivered a high predictive accuracy [the area under the receiver operating characteristic (AUC) curve of 0.82, Nagelkerke's 0.34 in the development cohort]. Validation of the model demonstrated a high discriminative capacity with the AUC of 0.82, Nagelkerke's 0.30 in the validation cohort.
Adding level of consciousness and sonographic vasospasm between admission and postbleed day 5 to the initial blood amount allows for simple and precise prediction of DCI. The suggested risk chart may prove useful for selection of appropriate candidates for interventions to prevent DCI.
利用发病后5天内可获取的信息，建立一个实用的风险图表，用于预测动脉瘤性蛛网膜下腔出血（aSAH）后迟发性脑梗死（DCI）。
我们评估了2008年9月至2015年9月期间收治的所有连续性aSAH患者（n = 417）。数据集被随机分为三分之一。三分之二用于模型开发，三分之一用于验证。评估出血事件与第5天之间（即超过95%的DCI诊断之前）存在的特征，以使用逻辑回归模型预测DCI。建立并验证了一个简单的风险图表。
入院CT上脑池和脑室积血的量（）、早期血管痉挛（即至第5天颅内动脉平均流速>160 cm/s）以及至第5天的简化二元Fisher评分是DCI的最强预测因素。结合这些预测因素的模型具有较高的预测准确性[受试者操作特征（AUC）曲线下面积为0.82，在开发队列中Nagelkerke's R²为0.34]。模型验证显示具有较高的判别能力，在验证队列中AUC为0.82，Nagelkerke's R²为0.30。
在初始出血量的基础上，加入意识水平和出血后第5天内的超声血管痉挛情况，可对DCI进行简单而精确的预测。所建议的风险图表可能对选择合适的预防DCI干预候选者有用。
