Study on the distribution and characteristics of Chinese medicine syndrome in patients with nonalcoholic fatty liver disease.
- Author:
Xiao-fen FAN
1
;
Yin-quan DENG
;
Guo-lin WU
Author Information
- Publication Type:Journal Article
- MeSH: Adult; Aged; Cluster Analysis; Factor Analysis, Statistical; Fatty Liver; diagnosis; epidemiology; Female; Humans; Male; Medicine, Chinese Traditional; methods; Middle Aged; Non-alcoholic Fatty Liver Disease
- From: Chinese Journal of Integrated Traditional and Western Medicine 2011;31(10):1332-1336
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo supply evidence for establishing the standard for Chinese medicine (CM) syndrome differentiation by investigating the distribution and characteristics of CM syndromes in patients with nonalcoholic fatty liver disease (NAFLD).
METHODS928 NAFLD patients' symptoms, signs, tongue and pulse parameters were studied by clinical epidemiologic survey. And the results were analyzed by the cluster analysis and factor analysis.
RESULTSThe results of cluster analysis showed that the CM syndrome typings of fatty liver patients were mainly classified as dampness heat accumulation, Pi deficiency with dampness phlegm, Gan-qi stagnation and Pi deficiency, phlegm stasis accumulation, and Gan-Shen insufficiency, which were in accordance with clinical practice. The results of factor analysis indicated that overweight/obesity, abdominal distension, hypochondriac pain, discomfort in the hepatic region were common "condition factors" of fatty liver patients. The 5 "syndrome factors" such as dampness heat accumulation, Pi deficiency with dampness phlegm, Gan-qi stagnation and Pi deficiency, phlegm stasis accumulation, and Gan-Shen insufficiency showed identification significance in syndrome typing.
CONCLUSIONSThe basic CM syndrome typings of NAFLD were dampness heat accumulation, Pi deficiency with dampness phlegm, Gan-qi stagnation and Pi deficiency, phlegm stasis accumulation, and Gan-Shen insufficiency. The four parameters of fatty liver patients could be classified by statistical analysis as condition factors and syndrome factors (which could reflect CM syndrome characteristics), which could provide certain evidence for establishing CM syndrome differentiation standards.