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基于颅内压衍生的脑血管反应性指数的最佳脑灌注压:在中/重度创伤性脑损伤中,哪一个更有助于预后预测?

Optimal Cerebral Perfusion Pressure Based on Intracranial Pressure-Derived Indices of Cerebrovascular Reactivity: Which One Is Better for Outcome Prediction in Moderate/Severe Traumatic Brain Injury?

机构信息

Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK.

Department of Neurosurgery, Rigshospitalet, Copenhagen, Denmark.

出版信息

Acta Neurochir Suppl. 2021;131:173-179. doi: 10.1007/978-3-030-59436-7_35.

DOI:10.1007/978-3-030-59436-7_35
PMID:33839841
Abstract

Intracranial pressure (ICP)-derived indices of cerebrovascular reactivity (e.g., PRx, PAx, and RAC) have been developed to improve understanding of brain status from available neuromonitoring variables. These indices are moving correlation coefficients between slow-wave vasogenic fluctuations in ICP and arterial blood pressure. In this retrospective analysis of neuromonitoring data from 200 patients admitted with moderate/severe traumatic brain injury (TBI), we evaluate the predictive value of CPPopt based on these ICP-derived indices of cerebrovascular reactivity. Valid CPPopt values were obtained in 92.3% (PRx), 86.7% (PAX), and 84.6% (RAC) of the monitoring periods, respectively. In multivariate logistic analysis, a baseline model that includes age, sex, and admission Glasgow Coma Score had an area under the receiver operating curve of 0.762 (P < 0.0001) for dichotomous outcome prediction (dead vs. good recovery). When adding time/dose of CPP below CPPopt, all multivariate models (based on PRx, PAx, and RAC) predicted the dichotomous outcome measure, but additional value of the prediction was only significantly added by the PRx-based calculations of time spent with CPP below CPPopt and dose of CPP below CPPopt.

摘要

颅内压(ICP)衍生的脑血管反应性指标(例如 PRx、PAx 和 RAC)的发展,旨在提高对脑状态的理解,这些指标是在可用的神经监测变量之间进行慢波血管源性波动与动脉血压之间的移动相关系数。在对 200 名因中度/重度创伤性脑损伤(TBI)入院的患者的神经监测数据进行的回顾性分析中,我们评估了基于这些 ICP 衍生的脑血管反应性指标的 CPPopt 的预测价值。分别在 92.3%(PRx)、86.7%(PAX)和 84.6%(RAC)的监测期间获得了有效的 CPPopt 值。在多变量逻辑分析中,包括年龄、性别和入院格拉斯哥昏迷评分的基线模型,对二分类结果预测(死亡与良好恢复)的受试者工作特征曲线下面积为 0.762(P<0.0001)。当添加 CPP 低于 CPPopt 的时间/剂量时,所有多变量模型(基于 PRx、PAx 和 RAC)均预测了二分类结果测量值,但仅 PRx 计算的 CPP 低于 CPPopt 的时间和 CPP 低于 CPPopt 的剂量的预测值具有显著附加价值。

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