Applying latent tree analysis to classify Traditional Chinese Medicine syndromes (Zheng) in patients with psoriasis vulgaris

doi:10.19852/j.cnki.jtcm.20210425.003

Journal of Traditional Chinese Medicine ›› 2022, Vol. 42 ›› Issue (1): 132-139.DOI: 10.19852/j.cnki.jtcm.20210425.003

• Research Articles • Previous Articles Next Articles

Applying latent tree analysis to classify Traditional Chinese Medicine syndromes (Zheng) in patients with psoriasis vulgaris

Wenjie XU¹^,²(), Nevin L. ZHANG³(), Ping LI⁴, Tianfang WANG⁵, Weiwen CHEN¹, April H. LIU³^,⁶, Meichun MOHLER-KUO⁷

1 Beijing Hospital of Traditional Chinese Medicine, affiliated to Capital Medical University, Beijing 100010, China
2 Institute of Epidemiology, Biostatistics and Prevention, University of Zurich, Zurich 8001, Switzerland
3 Department of Computer Science and Engineering, the Hong Kong University of Science and Technology, Kowloon, Hong Kong, China
4 Beijing Research Institute of Chinese Medicine, Beijing 100010, China
5 Department of TCM Diagnostics, Preclinical School, Beijing University of Traditional Chinese Medicine, Beijing 100029, China
6 Department of Computer Science, Shanghai University of Finance and Economics, Shanghai 200433, China
7 Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, 8032, Switzerland; La Source, School of Nursing Sciences, HES-SO University of Applied Sciences and Arts of Western Switzerland, 1004, Lausanne, Switzerland

Received:2020-12-12 Accepted:2021-03-03 Online:2022-02-15 Published:2021-04-25
Contact: Wenjie XU,Nevin L. ZHANG
About author:Dr. ZHANG Nevin L., Department of Computer Science and Engineering, the Hong Kong University of Science and Technology, Kowloon, Hong Kong, China. lzhang@cse.ust.hk
Dr. XU Wenjie, Beijing Hospital of Traditional Chinese Medicine, affiliated to Capital Medical University, Beijing, 100010, China. xuwj123@sina.com;
Supported by:
Foundation for Establishing Psoriasis Vulgaris Syndrome Diagnostic Criterion by Latent Structure(QN2009-14);Scientific Project of Beijing Municipal Science Technology Commission: Study on the Composition Rules of Syndrome Elements on Psoriasis Vulgaris and Standardized Treatments of TCM(D09050703550901)

Abstract

Abstract:

OBJECTIVE: To treat patients with psoriasis vulgaris using Traditional Chinese Medicine (TCM), one must stratify patients into subtypes (known as TCM syndromes or Zheng) and apply appropriate TCM treatments to different subtypes. However, no unified symptom-based classification scheme of subtypes (Zheng) exists for psoriasis vulgaris. The present paper aims to classify patients with psoriasis vulgaris into different subtypes via the analysis of clinical TCM symptom and sign data.

METHODS: A cross-sectional survey was carried out in Beijing from 2005-2008, collecting clinical TCM symptom and sign data from 2764 patients with psoriasis vulgaris. Roughly 108 symptoms and signs were initially analyzed using latent tree analysis, with a selection of the resulting latent variables then used as features to cluster patients into subtypes.

RESULTS: The initial latent tree analysis yielded a model with 43 latent variables. The second phase of the analysis divided patients into three subtype groups with clear TCM Zheng connotations: ‘blood deficiency and wind dryness’; ‘blood heat’; and ‘blood stasis’.

CONCLUSIONS: Via two-phase analysis of clinic symptom and sign data, three different Zheng subtypes were identified for psoriasis vulgaris. Statistical characteristics of the three subtypes are presented. This constitutes an evidence-based solution to the syndrome-differentiation problem that exists with psoriasis vulgaris.

Key words: psoriasis vulgaris, syndrome differentiation, cluster analysis, Latent tree analysis

Wenjie XU, Nevin L. ZHANG, Ping LI, Tianfang WANG, Weiwen CHEN, April H. LIU, Meichun MOHLER-KUO. Applying latent tree analysis to classify Traditional Chinese Medicine syndromes (Zheng) in patients with psoriasis vulgaris[J]. Journal of Traditional Chinese Medicine, 2022, 42(1): 132-139.

Figures/Tables 7

References 20

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Item	Y4 = s0 (.31)	Y4 = s1 (.33)	Y4 = s2 (.36)
Dark_red_plaque	0	1	0
Bright_red_plaque	1	0	0
Pale_red_plaque	0	0	0.97

Item	Y4 = s0 (.31)	Y4 = s1 (.33)	Y4 = s2 (.36)
Dark_red_plaque	0	1	0
Bright_red_plaque	1	0	0
Pale_red_plaque	0	0	0.97

Item	Y26 = s0 (.84)	Y26 = s1 (.16)
Reddened_lips	0.01	0.35
Red_complexion	0.01	0.24
Sonorous_voice	0.00	0.21

Item	Y26 = s0 (.84)	Y26 = s1 (.16)
Reddened_lips	0.01	0.35
Red_complexion	0.01	0.24
Sonorous_voice	0.00	0.21

Characteristic		Number (n = 2764)	Percentage (%)
Gender	Male	1561	56.5
	Female	1203	43.5
Ethnicity	Han	2667	96.5
	Others	97	3.5
	Age in years (mean ± SD)	37±15	-
Onset	New-onset	765	27.7
	Repeated episode	1999	72.3
	Duration of the disease (years) (mean ± SD)	10±10	-
Phase of psoriasis vulgaris	Progressive disease	945	34.2
	Stable disease	1483	53.7
	In remission	244	8.8

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Applying latent tree analysis to classify Traditional Chinese Medicine syndromes (Zheng) in patients with psoriasis vulgaris

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Figures/Tables 7

References 20

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Item	Mutual information with Z1	Z1 = S0 (.26)	Z1 = S1 (.32)	Z1 = S2 (.42)
Drop_like_lesion	0.56	0.00	0.95	0.00
Coin_like_lesion	0.40	0.89	0.00	0.82
Fine_scale	0.16	0.67	0.61	0.10
Severe_infiltration	0.09	0.02	0.06	0.34
Thick_scale	0.07	0.01	0.05	0.29
Pale_red_plaque	0.07	0.55	0.46	0.16
Flaky_scale	0.05	0.29	0.32	0.61
Mild_infiltration	0.04	0.31	0.38	0.63
Dark_red_plaque	0.04	0.29	0.18	0.47
Map_like_lesion	0.03	0.08	0.00	0.12
Abundant_fresh_lesion	0.03	0.06	0.29	0.13
Bright_red_plaque	0.02	0.15	0.35	0.37
Ring_like_lesion	0.01	0.00	0.05	0.00
Auspitz_sign	0.01	0.48	0.66	0.63
Isomorphism	0.01	0.24	0.40	0.29

		Z1 = S0 (n = 660)		Z1 = S1 (n = 901)						Z1 = S2 (n = 1203)
Item		blood deficiency and wind dryness		Blood heat						Blood stasis
		n	%			n		%			n		%
Tongue symptoms	Pink_tongue	187	28.3			226		25.1	238			19.8
	Red_tongue	314	47.6		528		58.6		635			52.8
	Purple_dark_tongue	114	17.3		103		11.4		261			21.7
	Deep_red_tongue	0	0		3		0.3		17			1.4
	Little_tongue_coating	24	3.6		16		1.8		25			2.1
Pulse symptoms	Slippery_pulse	434	65.8		638		70.8		780			64.8
	Rapid_pulse	83	12.6		210		23.3		192			16
	Deep_pulse	91	13.8		77		8.5		122			10.1
	Stringy_pulse	208	31.5		268		29.7		490			40.7
General body symptoms	Pale_complexion	39	5.9		45		5.0		29			2.4
General body symptoms	Hectic_cheek	17	2.6		14		1.6		13			1.1
	Pharyngeal_swelling	183	27.7		377		41.8		313			26
	Reddened_lips	41	6.2		81		9.0		62			5.2
	Pale_lips	27	4.1		32		3.6		16			1.3

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