Symptom network topological features predict the effectiveness of herbal treatment for pediatric cough.
10.1007/s11684-019-0699-3
- Author:
Mengxue HUANG
1
;
Jingjing WANG
2
;
Runshun ZHANG
3
;
Zhuying NI
4
;
Xiaoying LIU
4
;
Wenwen LIU
2
;
Weilian KONG
2
;
Yao CHEN
4
;
Tiantian HUANG
5
;
Guihua LI
5
;
Dan WEI
6
;
Jianzhong LIU
7
;
Xuezhong ZHOU
8
Author Information
1. Shanghai Traditional Chinese Medicine-Integrated Hospital, Shanghai, 200082, China.
2. Institute of Medical Intelligence, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China.
3. Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.
4. Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan, 430061, China.
5. School of the Clinical Medicine College of Traditional Chinese Medicine, Hubei University of Chinese Medicine, Wuhan, 430061, China.
6. Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan, 430061, China. 150529862@qq.com.
7. Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan, 430061, China. ljzwd@163.com.
8. Institute of Medical Intelligence, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China. xzzhou@bjtu.edu.cn.
- Publication Type:Journal Article
- Keywords:
complex network;
electronic medical records;
pediatric cough;
symptoms;
traditional Chinese medicine
- From:
Frontiers of Medicine
2020;14(3):357-367
- CountryChina
- Language:English
-
Abstract:
Pediatric cough is a heterogeneous condition in terms of symptoms and the underlying disease mechanisms. Symptom phenotypes hold complicated interactions between each other to form an intricate network structure. This study aims to investigate whether the network structure of pediatric cough symptoms is associated with the prognosis and outcome of patients. A total of 384 cases were derived from the electronic medical records of a highly experienced traditional Chinese medicine (TCM) physician. The data were divided into two groups according to the therapeutic effect, namely, an invalid group (group A with 40 cases of poor efficacy) and a valid group (group B with 344 cases of good efficacy). Several well-established analysis methods, namely, statistical test, correlation analysis, and complex network analysis, were used to analyze the data. This study reports that symptom networks of patients with pediatric cough are related to the effectiveness of treatment: a dense network of symptoms is associated with great difficulty in treatment. Interventions with the most different symptoms in the symptom network may have improved therapeutic effects.
