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Modelling Cerebrovascular Reactivity: A Novel Near-Infrared Biomarker of Cerebral Autoregulation?

机译:模型脑血管反应性:脑自动调节的新型近红外生物标志物?

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摘要

Understanding changes in cerebral oxygenation, haemodynamics and metabolism holds the key to individualised, optimised therapy after acute brain injury. Near-infrared spectroscopy (NIRS) offers the potential for non-invasive, continuous bedside measurement of surrogates for these processes. Interest has grown in applying this technique to interpret cerebrovascular pressure reactivity (CVPR), a surrogate of the brain’s ability to autoregulate blood flow. We describe a physiological model-based approach to NIRS interpretation which predicts autoregulatory efficiency from a model parameter k_aut. Data from three critically brain-injured patients exhibiting a change in CVPR were investigated. An optimal value for k_aut was determined to minimise the difference between measured and simulated outputs. Optimal values for k_aut appropriately tracked changes in CVPR under most circumstances. Further development of this technique could be used to track CVPR providing targets for individualised management of patients with altered vascular reactivity, minimising secondary neurological insults.
机译:了解脑氧合,血流动力学和新陈代谢的变化,是急性脑损伤后个体化,优化治疗的关键。近红外光谱(NIRS)为这些过程的替代物的无创,连续床旁测量提供了潜力。使用这种技术来解释脑血管压力反应性(CVPR)的兴趣已经增长,它是大脑自动调节血流能力的替代品。我们描述了一种基于生理模型的NIRS解释方法,该方法可从模型参数k_aut预测自动调节效率。调查了三名表现出CVPR变化的严重脑损伤患者的数据。确定k_aut的最佳值以最小化测量输出和模拟输出之间的差异。在大多数情况下,k_aut的最佳值可适当跟踪CVPR的变化。该技术的进一步发展可用于追踪CVPR提供的目标,以针对血管反应性改变的患者进行个体化治疗,从而最大程度地减少继发性神经损伤。

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