title: Complex networks approach for analyzing the correlation of traditional chinese medicine syndrome evolvement and cardiovascular events in patients with stable coronary heart disease.
abstract: This is a multicenter prospective cohort study to analyze the correlation of traditional Chinese medicine (TCM) syndrome evolvement and cardiovascular events in patients with stable coronary heart disease (CHD). The impact of syndrome evolvement on cardiovascular events during the 6-month and 12-month follow-up was analyzed using complex networks approach. Results of verification using Chi-square test showed that the occurrence of cardiovascular events was positively correlated with syndrome evolvement when it evolved from toxic syndrome to Qi deficiency, blood stasis, or sustained toxic syndrome, when it evolved from Qi deficiency to blood stasis, toxic syndrome, or sustained Qi deficiency, and when it evolved from blood stasis to Qi deficiency. Blood stasis, Qi deficiency, and toxic syndrome are important syndrome factors for stable CHD. There are positive correlations between cardiovascular events and syndrome evolution from toxic syndrome to Qi deficiency or blood stasis, from Qi deficiency to blood stasis, or toxic syndrome and from blood stasis to Qi deficiency. These results indicate that stable CHD patients with pathogenesis of toxin consuming Qi, toxin leading to blood stasis, and mutual transformation of Qi deficiency and blood stasis are prone to recurrent cardiovascular events.
authors.affiliation: China Heart Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100091, China.
authors.forename: Zhuye
authors.initials: Z
authors.lastname: Gao
authors.affiliation: Beijing University of Chinese Medicine, Beijing 100029, China.
authors.forename: Siwei
authors.initials: S
authors.lastname: Li
authors.affiliation: China Heart Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100091, China.
authors.forename: Qinghua
authors.identifier: 0000-0002-5037-0136
authors.initials: Q
authors.lastname: Shang
authors.affiliation: Beijing University of Chinese Medicine, Beijing 100029, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Jiao
authors.affiliation: School of Computer and Information Technology and Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China.
authors.forename: Xuezhong
authors.initials: X
authors.lastname: Zhou
authors.affiliation: China Heart Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100091, China.
authors.forename: Changgeng
authors.initials: C
authors.lastname: Fu
authors.affiliation: China Heart Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100091, China.
authors.forename: Hao
authors.identifier: 0000-0002-3139-4087
authors.initials: H
authors.lastname: Xu
authors.affiliation: China Heart Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100091, China.
authors.forename: Dazhuo
authors.initials: D
authors.lastname: Shi
authors.affiliation: China Heart Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100091, China.
authors.forename: Keji
authors.initials: K
authors.lastname: Chen
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