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基于逐分钟监测数据的重型颅脑损伤患者压力自动调节监测及脑灌注压目标推荐

Pressure autoregulation monitoring and cerebral perfusion pressure target recommendation in patients with severe traumatic brain injury based on minute-by-minute monitoring data.

作者信息

Depreitere Bart, Güiza Fabian, Van den Berghe Greet, Schuhmann Martin U, Maier Gottlieb, Piper Ian, Meyfroidt Geert

机构信息

Neurosurgery and.

出版信息

J Neurosurg. 2014 Jun;120(6):1451-7. doi: 10.3171/2014.3.JNS131500. Epub 2014 Apr 18.

Abstract

OBJECT

In severe traumatic brain injury, a universal target for cerebral perfusion pressure (CPP) has been abandoned. Attempts to identify a dynamic CPP target based on the patient's cerebrovascular autoregulatory capacity have been promising so far. Bedside monitoring of pressure autoregulatory capacity has become possible by a number of methods, Czosnyka's pressure reactivity index (PRx) being the most frequently used. The PRx is calculated as the moving correlation coefficient between 40 consecutive 5-second averages of intracranial pressure (ICP) and mean arterial blood pressure (MABP) values. Plotting PRx against CPP produces a U-shaped curve in roughly two-thirds of monitoring time, with the bottom of this curve representing a CPP range corresponding with optimal autoregulatory capacity (CPPopt). In retrospective series, keeping CPP close to CPPopt corresponded with better outcomes. Monitoring of PRx requires high-frequency signal processing. The aim of the present study is to investigate how the processing of the information on cerebrovascular pressure reactivity that can be obtained from routine minute-by-minute ICP and MABP data can be enhanced to enable CPPopt recommendations that do not differ from those obtained by the PRx method, show the same associations with outcome, and can be generated in more than two-thirds of monitoring time.

METHODS

The low-frequency autoregulation index (LAx) was defined as the moving minute-by-minute ICP/MABP correlation coefficient calculated over time intervals varying from 3 to 120 minutes. The CPPopt calculation was based on LAx-CPP plots and done for time windows between 1 and 24 hours and for each LAx type. The resulting matrix of CPPopts were then averaged in a weighted manner, with the weight based on the goodness of fit of a U-shape and the lower value of the LAx corresponding to the U-bottom, to result in a final CPPopt recommendation. The association between actual CPP/CPPopt and outcome was assessed in the multicenter Brain Monitoring with Information Technology Research Group (BrainIT) database (n = 180). In the Leuven-Tübingen database (60-Hz waveform data, n = 21), LAx- and PRx-based CPPopts were compared.

RESULTS

In the BrainIT database, CPPopt recommendations were generated in 95% of monitoring time. Actual CPP being close to LAx-based CPPopt was associated with increased survival. In a multivariate model using the Corticosteroid Randomization After Significant Head Injury (CRASH) model as covariates, the average absolute difference between actual CPP and CPPopt was independently associated with increased mortality. In the high-frequency data set no significant difference was observed between PRx-based and LAx-based CPPopts. The new method issued a CPPopt recommendation in 97% of monitoring time, as opposed to 44% for PRx-based CPPopt.

CONCLUSIONS

Minute-by-minute ICP/MABP data contain relevant information for autoregulation monitoring. In this study, the authors' new method based on minute-by-minute data resolution allowed for CPPopt calculation in nearly the entire monitoring time. This will facilitate the use of pressure reactivity monitoring in all ICUs.

摘要

目的

在重度创伤性脑损伤中,已摒弃了脑灌注压(CPP)的通用目标。基于患者脑血管自动调节能力来确定动态CPP目标的尝试至今颇具前景。通过多种方法已能够在床边监测压力自动调节能力,其中乔斯尼卡的压力反应性指数(PRx)是最常用的。PRx计算为颅内压(ICP)和平均动脉血压(MABP)值的40个连续5秒平均值之间的移动相关系数。将PRx与CPP作图,在大约三分之二的监测时间内会产生一条U形曲线,该曲线的底部代表与最佳自动调节能力相对应的CPP范围(CPPopt)。在回顾性系列研究中,使CPP接近CPPopt与更好的预后相关。PRx监测需要高频信号处理。本研究的目的是探讨如何增强从常规逐分钟的ICP和MABP数据中获取的脑血管压力反应性信息的处理,以实现与PRx方法得出的CPPopt建议无差异、与预后显示相同关联且能在三分之二以上的监测时间内生成的CPPopt建议。

方法

低频自动调节指数(LAx)定义为在3至120分钟的时间间隔内计算的逐分钟ICP/MABP移动相关系数。CPPopt计算基于LAx-CPP图,并针对1至24小时的时间窗以及每种LAx类型进行。然后以加权方式对所得的CPPopt矩阵进行平均,权重基于U形的拟合优度以及对应于U形底部的较低LAx值,以得出最终的CPPopt建议。在多中心信息技术脑监测研究组(BrainIT)数据库(n = 180)中评估实际CPP/CPPopt与预后之间的关联。在鲁汶 - 图宾根数据库(60赫兹波形数据,n = 21)中,比较基于LAx和PRx的CPPopt。

结果

在BrainIT数据库中,95%的监测时间内生成了CPPopt建议。实际CPP接近基于LAx的CPPopt与生存率增加相关。在使用重度颅脑损伤后皮质类固醇随机化(CRASH)模型作为协变量的多变量模型中,实际CPP与CPPopt之间的平均绝对差异与死亡率增加独立相关。在高频数据集中,基于PRx和基于LAx的CPPopt之间未观察到显著差异。新方法在监测时间的97%内发出了CPPopt建议,而基于PRx的CPPopt为44%。

结论

逐分钟的ICP/MABP数据包含用于自动调节监测的相关信息。在本研究中,作者基于逐分钟数据分辨率的新方法允许在几乎整个监测时间内计算CPPopt。这将促进压力反应性监测在所有重症监护病房中的应用。

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