Sarwal Aarti, Robba Chiara, Venegas Carla, Ziai Wendy, Czosnyka Marek, Sharma Deepak
Atrium Wake Forest School of Medicine, Winston-Salem, NC, USA.
IRCCS Policlinico San martino, Genova, Italy.
Neurocrit Care. 2023 Oct;39(2):269-283. doi: 10.1007/s12028-023-01741-1. Epub 2023 May 10.
Cerebral autoregulation (CA) is a physiological mechanism that maintains constant cerebral blood flow regardless of changes in cerebral perfusion pressure and prevents brain damage caused by hypoperfusion or hyperperfusion. In recent decades, researchers have investigated the range of systemic blood pressures and clinical management strategies over which cerebral vasculature modifies intracranial hemodynamics to maintain cerebral perfusion. However, proposed clinical interventions to optimize autoregulation status have not demonstrated clear clinical benefit. As future trials are designed, it is crucial to comprehend the underlying cause of our inability to produce robust clinical evidence supporting the concept of CA-targeted management. This article examines the technological advances in monitoring techniques and the accuracy of continuous assessment of autoregulation techniques used in intraoperative and intensive care settings today. It also examines how increasing knowledge of CA from recent clinical trials contributes to a greater understanding of secondary brain injury in many disease processes, despite the fact that the lack of robust evidence influencing outcomes has prevented the translation of CA-guided algorithms into clinical practice.
脑自动调节(CA)是一种生理机制,可维持恒定的脑血流量,而不受脑灌注压变化的影响,并防止因灌注不足或灌注过多引起的脑损伤。近几十年来,研究人员研究了全身血压范围以及临床管理策略,在此范围内脑血管会改变颅内血流动力学以维持脑灌注。然而,为优化自动调节状态而提出的临床干预措施尚未显示出明确的临床益处。在设计未来试验时,至关重要的是要理解我们无法产生有力临床证据支持以CA为靶点的管理概念的根本原因。本文探讨了监测技术的技术进步以及当今术中及重症监护环境中使用的自动调节技术连续评估的准确性。它还探讨了尽管缺乏影响结果的有力证据阻碍了CA指导算法转化为临床实践,但最近的临床试验中对CA的了解增加如何有助于更好地理解许多疾病过程中的继发性脑损伤。