主 办:北 京 中 医 药 大 学
ISSN 1006-2157 CN 11-3574/R

JOURNAL OF BEIJING UNIVERSITY OF TRADITIONAL CHINESE MEDICINE ›› 2021, Vol. 44 ›› Issue (6): 527-537.doi: 10.3969/j.issn.1006-2157.2021.06.007

• TCM Informatics • Previous Articles     Next Articles

Study on the pattern-treatment-medicinal correspondence and its evolution in 2,826 patients with type 2 diabetes*

Xing Ying1, Pi Min2, Zhang Runshun3, He Xiong4, Yang Jie5, Wen Tiancai1,5#   

  1. 1 Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China;
    2 Shenzhen Traditional Chinese Medicine Hospital, Guangdong 518033, China;
    3 Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China;
    4 School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China;
    5 Traditional Chinese Medicine Data Center, China Academy of Chinese Medical Sciences, Beijing 100700, China
  • Received:2020-12-08 Online:2021-06-30 Published:2021-06-25
  • Contact: Wen Tiancai, Senior Engineer, Master’s Supervisor. Data Center of Traditional Chinese Medicine, Chinese Academy of Traditional Chinese Medicine. No.16 Dongzhimenneinan Street, Dongcheng District, Beijing 100700. E-mail: wtcsnake@163.com
  • Supported by:
    National Natural Science Foundation of China (No. 81774158)

Abstract: Objective To analyze the pattern-treatment-medicinal correspondence and its evolution over time in patients with type 2 diabetes (T2DM) to provide reference for the clinical treatment of type 2 diabetes. Methods Complex network community discovery algorithm, directed weighted complex network, Sankey graph and core network analysis were used to conduct data mining on the electronic case data of 2,826 patients with T2DM to identify the temporal evolution of patterns and the core combination of Chinese herbal medicinals corresponding to different treatment plans. Results 49.5% of the patients were male and 50.5% female. 51.59% were aged from 41 to 60. 92.75% visited the clinic twice to 10 times. The complex network of pattern and treatment of T2DM were divided into 7 core pattern communities and 5 treatment communities. The top two communities that occupy the largest proportion were the qi-deficiency blood-stasis yin-yang-deficiency pattern community (26.84%) and the yin-enriching heat-clearing dampness-dispelling phlegm-dissolving treatment community (33.33%). The results showed that the sum of the number of visits by T2DM patients receiving yin-enriching heat-clearing dampness-dispelling phlegm-dissolving treatment and qi-moving blood-invigorating stasis-dissolving collateral-unblocking treatment in any pattern community before and after treatment accounted for more than 50% of the total. No matter what treatment method was adopted for any type of pattern, the pattern did not change in short term in about 50% patient visits, followed by those with patterns turning into the qi-deficiency blood-stasis yin-yang-deficiency pattern. The long-term evolution of the pattern-treatment relationship in patients with T2DM showed that most patterns remained the same after long-term treatment while a considerable amount turned into qi-deficiency blood-stasis yin-yang-deficiency pattern, spleen-deficiency stomach-heat liver-qi-stagnation pattern, and yin-deficiency effulgent-fire phlegm-heat-binding pattern. The medicinals used corresponded perfectly to the treatment communities. The commonly used combination of Chinese medicinal herbs included Huangqin (Scutellaria Root, Radix Scutellariae)-Huanglian (Golden Thread, Rhizoma Coptidis), Huanglian-Huangbai (Amur Cork-tree Bark, Cortex Phellodendri Chinensis), Huangqi (Milk-vetch Root, Radix Astragali)-Baishao (White Peony Root, Radix Paeoniae Alba), and Huanglian-Ganjiang (Dried Ginger Rhizome, Rhizoma Zingiberis). Conclusion The yin-enriching heat-clearing dampness-dispelling phlegm-dissolving treatment and qi-moving blood-invigorating stasis-dissolving collateral-unblocking treatment and Chinese herbal medicinals with the above mentioned functions are commonly used in the clinical treatment of T2DM. Although most patterns would fail to change significantly in the short term, over the long term, the patterns of a considerable proportion patients may turn into spleen-deficiency stomach-heat liver-qi-stagnation pattern, yin-deficiency effulgent-fire phlegm-heat-binding pattern, and qi-deficiency blood-stasis yin-yang-deficiency pattern.

Key words: type 2 diabetes, real world studies, data mining, complex networks, complex network community discovery algorithm, Sankey diagram, pattern, treatment, evolution

CLC Number: 

  • R259