Helgason Cathy M
University of Illinois at Chicago, Neurology and Rehabilitation, MC796, 912 South Wood Street, Room 855N, Chicago, IL 60612, USA.
Curr Treat Options Cardiovasc Med. 2007 Jun;9(3):213-20. doi: 10.1007/s11936-007-0015-4.
The current classification of stroke is based on causation, also called pathogenesis, and relies on binary logic faithful to the Aristotelian tradition. Accordingly, a pathology is or is not the cause of the stroke, is considered independent of others, and is the target for treatment. It is the subject for large double-blind randomized clinical therapeutic trials. The scientific view behind clinical trials is the fundamental concept that information is statistical, and causation is determined by probabilities. Therefore, the cause and effect relation will be determined by probability-theory-based statistics. This is the basis of evidence-based medicine, which calls for the results of such trials to be the basis for physician decisions regarding diagnosis and treatment. However, there are problems with the methodology behind evidence-based medicine. Calculations using probability-theory-based statistics regarding cause and effect are performed within an automatic system where there are known inputs and outputs. This method of research provides a framework of certainty with no surprise elements or outcomes. However, it is not a system or method that will come up with previously unknown variables, concepts, or universal principles; it is not a method that will give a new outcome; and it is not a method that allows for creativity, expertise, or new insight for problem solving.
目前中风的分类基于病因，也称为发病机制，并且依赖于忠实于亚里士多德传统的二元逻辑。因此，一种病理状态要么是中风的病因，要么不是，被认为独立于其他因素，并且是治疗的靶点。它是大型双盲随机临床治疗试验的研究对象。临床试验背后的科学观点是一个基本概念，即信息是统计学的，病因是由概率决定的。因此，因果关系将由基于概率论的统计学来确定。这是循证医学的基础，循证医学要求此类试验的结果作为医生诊断和治疗决策的依据。然而，循证医学背后的方法存在问题。使用基于概率论的统计学对因果关系进行计算是在一个有已知输入和输出的自动系统内进行的。这种研究方法提供了一个确定性的框架，没有意外因素或结果。然而，它不是一种能够提出先前未知的变量、概念或普遍原则的系统或方法；它不是一种能给出新结果的方法；它也不是一种允许发挥创造力、专业知识或解决问题新见解的方法。
