Study on Syndrome Distribution and Chinese Medicine Composition of AECOPD Based on Complex Networks
10.11842/wst.2015.06.026
- VernacularTitle:基于复杂网络AECOPD证候分布及中药组合研究＊
- Author:
Jinliang HU
;
Suyun LI
;
Xinghong ZHANG
;
Haibin YU
;
Guorong CUI
;
Zhen LI
- Publication Type:Journal Article
- Keywords:
Clinical research and information-sharing system;
acute exacerbation of chronic obstructive pulmonary disease;
syndrome distribution;
Chinese medicine composition;
complex networks
- From:
World Science and Technology-Modernization of Traditional Chinese Medicine
2015;(6):1268-1273
- CountryChina
- Language:Chinese
-
Abstract:
Based on clinical research and information-sharing system, this article was aimed to study both the syndrome distribution and Chinese medicine composition of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in the COPD base of our hospital using the complex networks. The analysis was made on the common rules of syndrome distribution and features of key Chinese medicine compositions in the diagnosis and treatment of AECOPD. The clinical research and information-sharing system was used on the AECOPD data study (3000 hospital electronic medical records from August 2012 to January 2015). Data was processed by ETL software. The database was constructed. And the complex networks were used in the data mining. The results showed that the distribution of AECOPD common syndromes was heat-phlegm obstructing lung of 41.94%, phlegm-turbid obstructing lung of 22.97%, phlegm-damp obstructing lung of 10.30%,qi-yin deficiency of 6.31%, phlegm-stasis obstructing lung of 5.72%, lung-kidneyqi-deficiency of 4.01%, lung-spleenqi-deficiency of 1.15%, and phlegm obstructing orifices of 1.15%. Chinese medicine compositions were obviously divided into two large groups, which were the core Chinese medicine group and the associated Chinese medicine group. The research results illustrated that the clinical research and information-sharing system had good analysis and classification effects, which not only analyzing the medication laws of senior Chinese medicine experts and single disease treatment by a hospital, but also using in the large data analysis (data collection of single or multiple diseases on Chinese medicine clinical research nationally). It provided a good scientific research platform for Chinese medicine.
