Tenovuo Olli, Diaz-Arrastia Ramon, Goldstein Lee E, Sharp David J, van der Naalt Joukje, Zasler Nathan D
Clinical Neurosciences, University of Turku and Turku Brain Injury Center, Neurocenter, Turku University Hospital, 20521 Turku, Finland.
Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
J Clin Med. 2021 Jan 4;10(1):148. doi: 10.3390/jcm10010148.
Traumatic brain injury (TBI) has been described to be man's most complex disease, in man's most complex organ. Despite this vast complexity, variability, and individuality, we still classify the severity of TBI based on non-specific, often unreliable, and pathophysiologically poorly understood measures. Current classifications are primarily based on clinical evaluations, which are non-specific and poorly predictive of long-term disability. Brain imaging results have also been used, yet there are multiple ways of doing brain imaging, at different timepoints in this very dynamic injury. Severity itself is a vague concept. All prediction models based on combining variables that can be assessed during the acute phase have reached only modest predictive values for later outcome. Yet, these early labels of severity often determine how the patient is treated by the healthcare system at large. This opinion paper examines the problems and provides caveats regarding the use of current severity labels and the many practical and scientific issues that arise from doing so. The objective of this paper is to show the causes and consequences of current practice and propose a new approach based on risk classification. A new approach based on multimodal quantifiable data (including imaging and biomarkers) and risk-labels would be of benefit both for the patients and for TBI clinical research and should be a priority for international efforts in the field.
创伤性脑损伤（TBI）被认为是发生在人体最复杂器官中的最复杂疾病。尽管其具有极大的复杂性、变异性和个体性，但我们仍基于非特异性、通常不可靠且在病理生理学上理解不足的指标来对TBI的严重程度进行分类。目前的分类主要基于临床评估，这些评估是非特异性的，对长期残疾的预测性很差。脑成像结果也被使用过，然而在这种动态损伤的不同时间点，脑成像有多种方式。严重程度本身就是一个模糊的概念。所有基于急性期可评估变量组合的预测模型对后期结果的预测价值都仅为中等。然而，这些早期的严重程度标签往往决定了整个医疗系统对患者的治疗方式。这篇观点论文探讨了相关问题，并对当前严重程度标签的使用以及由此产生的许多实际和科学问题提出了警示。本文的目的是揭示当前做法的原因和后果，并提出一种基于风险分类的新方法。一种基于多模态可量化数据（包括成像和生物标志物）以及风险标签的新方法将对患者以及TBI临床研究都有益处，并且应该成为该领域国际努力的优先事项。
