Logistic regression analysis of damp-heat and cold-damp impeding syndrome of rheumatoid arthritis: a perspective in Chinese medicine

Chin J Integr Med. 2012 Aug;18(8):575-81. doi: 10.1007/s11655-012-1172-1. Epub 2012 Aug 2.

Abstract

Objective: To investigate a method for quantitative differential diagnosis of damp-heat and cold-damp impeding syndrome of rheumatoid arthritis (RA) in Chinese medicine (CM).

Methods: Laboratory 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.

Results: There 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%.

Conclusion: The regression equation may be useful for discriminating damp-heat from cold-damp impeding syndrome of RA.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Arthritis, Rheumatoid / pathology*
  • Arthritis, Rheumatoid / therapy*
  • Cytokines / metabolism
  • Demography
  • Female
  • Hot Temperature*
  • Humans
  • Logistic Models
  • Male
  • Medicine, Chinese Traditional*
  • Middle Aged
  • Syndrome

Substances

  • Cytokines