基于复杂系统熵的高血压病证候相关理化指标文献研究

Literature research of essential hypertension syndromes associated physicochemical indexes based on complex system entropy

目的:通过对高血压病证候及相关理化指标文献的系统分析,并结合数据挖掘方法,探寻高血压病证候诊断的客观依据,为深入研究高血压病证候生物学基础提供依据。方法:检索现有高血压病证候及相关理化指标文献,采用复杂系统熵统计分析方法,对高血压病证候与理化指标的复杂相关性进行分析。结果:高血压病常见证候中以肝火亢盛证、痰湿壅盛证、阴虚阳亢证、阴阳两虚证等4种证型为主,通过统计分析证候与理化指标之间的关联度,得到与高血压常见证候相关性排名前15位的理化指标。结论:采用复杂系统熵数据挖掘技术探索中医证候与理化指标的复杂联系,既能反映高血压各证型共性的病理改变,又能通过不同证候间理化指标的改变程度及组合模式反映不同证候突出的病理特征,为证候诊断的客观化提供依据。

Objective： Based on system analysis and data mining of essential hypertension（EH） syndromes associated physicochemical indexes in literature to investigate the objective basis of EH syndrome differentiation and provide evidence for further research on biological basis of EH syndromes.Methods： Retrieve literature pertaining to syndromes and physicochemical indexes of EH,then complex system entropy was used to analyze the complicated correlations of EH syndromes associated with physicochemical indexes.Results： The most common syndromes of EH are hyperactivity of liver fire syndrome,excessive accumulation of phlegm-dampness syndrome,yin deficiency with yang hyperactivity syndrome and yin-yang concurrent deficiency syndrome.By analysis and calculation of the incidence coefficient among syndromes and physicochemical indexes,the top 15 physicochemical indexes of each syndrome were ranked.Conclusion： Data mining technology based on the complex system entropy data mining method to investigate the complex relationships of TCM syndromes with physical and chemical indexes can not only indicate the common pathogeneses of the disease,but also reflex the characteristics of each syndrome,which paves evidence for objective syndrome diagnosis.