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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

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Front. Med.    2020, Vol. 14 Issue (3) : 357-367    https://doi.org/10.1007/s11684-019-0699-3
RESEARCH ARTICLE
Symptom network topological features predict the effectiveness of herbal treatment for pediatric cough
Mengxue Huang1, Jingjing Wang2, Runshun Zhang3, Zhuying Ni4,5, Xiaoying Liu4,5, Wenwen Liu2, Weilian Kong2, Yao Chen4,5, Tiantian Huang6, Guihua Li6, Dan Wei4,5(), Jianzhong Liu4,5(), Xuezhong Zhou2()
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. Hubei Province Academy of Traditional Chinese Medicine, Wuhan 430061, China
6. School of the Clinical Medicine College of Traditional Chinese Medicine, Hubei University of Chinese Medicine, Wuhan 430061, China
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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.
Keywords pediatric cough      complex network      symptoms      traditional Chinese medicine      electronic medical records     
Corresponding Author(s): Dan Wei,Jianzhong Liu,Xuezhong Zhou   
Just Accepted Date: 08 July 2019   Online First Date: 16 September 2019    Issue Date: 08 June 2020
 Cite this article:   
Mengxue Huang,Jingjing Wang,Runshun Zhang, et al. Symptom network topological features predict the effectiveness of herbal treatment for pediatric cough[J]. Front. Med., 2020, 14(3): 357-367.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-019-0699-3
https://academic.hep.com.cn/fmd/EN/Y2020/V14/I3/357
Number of total patients 496
Number of total cases 1640
Number of patients with efficacy evaluation 254
Number of cases with efficacy evaluation 384
Tab.1  Number of patients and cases before and after evaluationa
Interval time Cases
1–7 days 336
8–14 days 44
>14 days 4
Tab.2  Distribution of interval time between two consecutive cases
Symptom Abbreviation Symptom Abbreviation Symptom Abbreviation
White-coated tongue wct Pharyngalgia phg Prickly tongue ptt
Pharyngeal red phr Yellow coated tongue yct Abdominal pain abp
Thin tongue coating thc Constipation con Dark red throat drt
Fingerprint in life pass flp Fingerprint in wind pass fiw Fingerprint in qi pass fqp
Moderate pulse mop Loose stool lst Rapid pulse rpp
Anorexia ano Sneezing snz Yellow sputum ysp
Red tongue rtg Pulmonary rales pmr Fine fingerprints fif
Thready pulse thp Nasal secretions nas White sputum wsp
Expectoration exp Nasal mucus nam Vomiting vom
Slippery pulse slp Thin tongue coating ttc Nasal discharge nsd
Antiadoncus ant Wheeze whz Purulent snot psn
Nasal obstruction nao Sleep disturbed sld Postnasal drip pod
Pink tongue pkt Throat secretions ths Barking cough bcg
Fever fev Poor complexion pcp Deep red tongue dpg
Conjunctival congestion cjc Purple red fingerprint prf Lavender fingerprints lvf
Pulmonary breath sounds rough pbs Inflamed lymph follicles of the throat ilt Swollen lymph follicles of the throat slft
Unconspicuous fingerprint ucf Night crying ncr
Thick coated tongue tct Erythra eth
Tab.3  Full names of the 52 symptoms
Age group Group A (cases) Group B (cases)
Newborn baby (1 day<age≤28 days) 0 2
Infancy (28 days<age≤1 year) 2 37
Toddler period (1 year<age≤3 years) 17 94
Pre-school age (3 years<age≤7 years) 17 176
School age (7 years<age≤13 years) 4 35
Tab.4  Age distribution of groups A and B
Gender Group A (cases) Group B (cases)
Boys 25 209
Girls 15 135
Tab.5  Gender distribution of groups A and B
Symptom Mean SD Statistic P value
Group A Group B Group A Group B
phr 0.85 0.81 0.36 0.40 7188 0.50
wct 0.78 0.79 0.42 0.41 6792 0.85
nsd 0.65 0.61 0.48 0.49 7172 0.60
ahc 0.58 0.52 0.50 0.50 7256 0.51
ano 0.50 0.48 0.51 0.50 7000 0.84
thp 0.23 0.39 0.42 0.49 5748 0.04
rtg 0.43 0.38 0.50 0.49 7204 0.56
mop 0.43 0.37 0.50 0.48 7244 0.51
exp 0.43 0.30 0.50 0.46 7724 0.11
slp 0.15 0.29 0.36 0.46 5892 0.06
pkt 0.15 0.22 0.36 0.41 6412 0.32
nao 0.13 0.21 0.33 0.41 6300 0.21
pmr 0.05 0.20 0.22 0.40 5824 0.02
lvf 0.30 0.19 0.46 0.40 7604 0.12
fiw 0.28 0.19 0.45 0.39 7452 0.21
tct 0.13 0.19 0.33 0.39 6420 0.30
con 0.30 0.18 0.46 0.38 7704 0.07
ant 0.18 0.17 0.38 0.38 6884 0.99
pbs 0.15 0.16 0.36 0.37 6792 0.84
fev 0.10 0.16 0.30 0.37 6468 0.32
nam 0.15 0.13 0.36 0.34 7012 0.74
yct 0.10 0.12 0.30 0.32 6748 0.72
snz 0.08 0.10 0.27 0.30 6716 0.63
Lst 0.05 0.09 0.22 0.29 6584 0.37
ucf 0.05 0.09 0.22 0.29 6604 0.39
psn 0.05 0.06 0.22 0.24 6804 0.78
whz 0.05 0.06 0.22 0.23 6824 0.84
prf 0.13 0.05 0.33 0.22 7400 0.05
nas 0.08 0.05 0.27 0.22 7056 0.49
ttc 0.08 0.04 0.27 0.20 7116 0.32
ths 0.05 0.03 0.22 0.18 6984 0.63
cjc 0.03 0.03 0.16 0.17 6852 0.89
pcp 0.05 0.03 0.22 0.17 7024 0.47
drt 0.05 0.02 0.22 0.15 7064 0.32
sld 0.03 0.02 0.16 0.15 6892 0.95
eth 0.03 0.02 0.16 0.15 6892 0.95
ysp 0.03 0.02 0.16 0.14 6912 0.85
rpp 0.03 0.02 0.16 0.14 6912 0.85
phg 0.03 0.02 0.16 0.14 6912 0.85
ptt 0.03 0.02 0.16 0.13 6932 0.74
vom 0.03 0.02 0.16 0.13 6932 0.74
fqp 0.05 0.02 0.22 0.13 7104 0.17
abp 0.03 0.02 0.16 0.13 6932 0.74
ilt 0.03 0.01 0.16 0.12 6952 0.62
slft 0.03 0.01 0.16 0.11 6972 0.48
dpg 0.03 0.01 0.16 0.11 6972 0.48
bcg 0.05 0.01 0.22 0.11 7144 0.06
wsp 0.03 0.01 0.16 0.11 6972 0.48
fif 0.05 0.01 0.22 0.11 7144 0.06
pod 0.03 0.01 0.16 0.08 7012 0.19
ncr 0.03 0.01 0.16 0.08 7012 0.19
flp 0.03 0.00 0.16 0.05 7032 0.07
Tab.6  General difference analysis of symptom of groups A and B
Fig.1  Symptom network structure of groups A and B. (A) Symptom correlation network of group A. (B) Symptom correlation network of group B. The symptom is represented as a node, and the Pearson’s correlation coefficient between two symptoms is represented as an edge. The green edges in (A) represent positive correlations, and the red edges represent negative correlations. The thick edges in (B) represent strong correlations, and the red edges represent negative correlations (positive or negative). Only edges with correlation coefficients larger than 0.24 are shown in the figure.
Group A (cases) Group B (cases)
Positive 395 931
Negative 515 811
Tab.7  Positive/negative correlation coefficient distribution of groups A and B
Invalid group Valid group
Symptom Symptom Weight Symptom Symptom Weight
slft dpg 1.00 fiw lvf 0.67
ths bcg 1.00 prf lvf 0.40
cjc phg 1.00 fqp fif 0.40
ysp flp 1.00 thc wct 0.38
sld ncr 1.00 thp slp 0.35
ths fif 1.00 drt dpg 0.34
bcg fif 1.00 nam nsd 0.31
ptt drt 0.70 tct yct 0.28
ysp fqp 0.70 cjc fev 0.26
fqp flp 0.70 drt pod 0.24
nsd thp −0.36 fiw slp −0.31
rtg pkt −0.36 lvf slp −0.32
ptt phr −0.38 fiw mop −0.38
wct pcp −0.43 mop lvf −0.38
thc tct −0.44 fiw thp −0.39
wct ttc −0.53 lvf thp −0.39
fiw mop −0.53 wct ttc −0.40
drt phr −0.55 rtg pkt −0.41
mop lvf −0.56 thc tct −0.51
wct yct −0.62 wct yct −0.71
Tab.8  Positive correlation and negative correlation values of the symptom network diagram
Fig.2  Overall connectivity measures of groups A and B. The color of columns shows different groups. (A) Global strength of groups A and B. (B) Average shortest path length of groups A and B. (C) Diameter of groups A and B. (D) Density of groups A and B.
Network metric P value
Global strength <0.05
Average shortest path length >0.05
Diameter <0.05
Density <0.05
Tab.9  Results of permutation test with networks
Fig.3  Four node centrality measures of groups A and B: strength, closeness, betweenness, and eigenvector.
Symptom Effect size Symptom Effect size Symptom Effect size
exp 3.21 ths 1.79 ysp 0.97
con 3.03 fev 1.70 vom 0.91
nsd 2.88 pcp 1.60 sld 0.90
pbs 2.81 whz 1.47 ncr 0.88
ano 2.61 psn 1.38 cjc 0.86
ant 2.51 abp 1.16 slft 0.86
phr 2.30 wsp 1.10 ilt 0.85
nao 2.20 drt 1.05 pod 0.84
snz 2.03 lst 1.04 phg 0.80
nas 1.97 eth 1.00
Tab.10  Effect sizes for differences in mean centrality between groups A and Ba
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