Department of Neurology, University of Colorado Denver, Aurora, USA.
Neurology. 2013 Jan 22;80(4):409-16. doi: 10.1212/WNL.0b013e31827f07be.
Fatigue is commonly reported in many neurologic illnesses, including multiple sclerosis, Parkinson disease, myasthenia gravis, traumatic brain injury, and stroke. Fatigue contributes substantially to decrements in quality of life and disability in these illnesses. Despite the clear impact of fatigue as a disabling symptom, our understanding of fatigue pathophysiology is limited and current treatment options rarely lead to meaningful improvements in fatigue. Progress continues to be hampered by issues related to terminology and assessment. In this article, we propose a unified taxonomy and a novel assessment approach to addressing distinct aspects of fatigue and fatigability in clinical and research settings. This taxonomy is based on our current knowledge of the pathophysiology and phenomenology of fatigue and fatigability. Application of our approach indicates that the assessment and reporting of fatigue can be clarified and improved by utilizing this taxonomy and creating measures to address distinct aspects of fatigue and fatigability. We review the strengths and weaknesses of several common measures of fatigue and suggest, based on our model, that many research questions may be better addressed by using multiple measures. We also provide examples of how to apply and validate the taxonomy and suggest directions for future research.
疲劳在许多神经疾病中都有报道，包括多发性硬化症、帕金森病、重症肌无力、创伤性脑损伤和中风。疲劳对这些疾病的生活质量和残疾有很大的影响。尽管疲劳作为一种致残症状的影响是显而易见的，但我们对疲劳病理生理学的理解是有限的，目前的治疗方法很少能显著改善疲劳。术语和评估方面的问题继续阻碍着进展。在本文中，我们提出了一个统一的分类法和一种新的评估方法，以解决临床和研究环境中疲劳和易疲劳的不同方面。该分类法基于我们对疲劳和易疲劳的病理生理学和现象学的现有认识。应用我们的方法表明，通过利用这种分类法和创建针对疲劳和易疲劳不同方面的措施，可以澄清和改进疲劳的评估和报告。我们回顾了几种常见疲劳测量方法的优缺点，并根据我们的模型建议，使用多种测量方法可能会更好地解决许多研究问题。我们还提供了如何应用和验证分类法的示例，并为未来的研究提供了方向。
