Logistic regression analysis of damp-heat and cold-damp impeding syndrome of rheumatoid arthritis: a perspective in Chinese medicine.
- Author:
Zhi-Zhong WANG
1
;
Yong-Fei FANG
;
Yong WANG
;
Fang-Xiang MU
;
Jun CHEN
;
Qing-Hua ZOU
;
Bing ZHONG
;
Jing-Yi LI
;
Gan-Ping BO
;
Rong-Hua ZHANG
Author Information
- Publication Type:Journal Article
- MeSH: Arthritis, Rheumatoid; pathology; therapy; Cytokines; metabolism; Demography; Female; Hot Temperature; Humans; Logistic Models; Male; Medicine, Chinese Traditional; Middle Aged; Syndrome
- From: Chinese journal of integrative medicine 2012;18(8):575-581
- CountryChina
- Language:English
-
Abstract:
OBJECTIVETo investigate a method for quantitative differential diagnosis of damp-heat and cold-damp impeding syndrome of rheumatoid arthritis (RA) in Chinese medicine (CM).
METHODSLaboratory parameters were collected from 306 patients with RA. The clinical symptoms and laboratory parameters were compared between patients with these two syndromes (158 with RA of damp-heat impeding syndrome, and 148 with RA of cold-damp impeding syndrome), and a regression equation was established to facilitate discrimination of the two RA syndromes.
RESULTSThere were significant differences in disease activity score in 28 joints [DAS28 (4)], erythrocyte sedimentation rate (ESR), white blood cell count (WBC), C-reactive protein (CRP), platelet count (PLT), albumin (ALB) and globulin (GLB) between the two syndrome of RA (P<0.05). Logistic regression analysis showed that the parameters ESR, WBC, CRP, joint pyrexia, joint cold, thirst, sweating, aversion to wind and cold, and cold extremities were statistically useful to discriminate damp-heat from cold-damp impeding syndrome. The regression equation was as follows: P=1/{1+exp[-(3.0-0.021X (1)-0.196X (2)-0.163X (3)-1.559X (4)+1.504X (5)-0.927X (6)-1.039X (7)+1.070X (8)+1.330X (9))]}. The independent variables X (1)-X (9) were ESR, WBC, CRP, hot joint, cold joint, thirst, sweating, aversion to wind and cold, and cold limbs. A P value > 0.5 signified cold-damp impeding syndrome, and a P value < 0.5 signified damp-heat impeding syndrome. The accuracy was 90.2%.
CONCLUSIONThe regression equation may be useful for discriminating damp-heat from cold-damp impeding syndrome of RA.