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.
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.
Authors: Mei Wang; Robert-Jan A N Lamers; Henrie A A J Korthout; Joop H J van Nesselrooij; Renger F Witkamp; Rob van der Heijden; Peter J Voshol; Louis M Havekes; Rob Verpoorte; Jan van der Greef Journal: Phytother Res Date: 2005-03 Impact factor: 5.878
Authors: F C Arnett; S M Edworthy; D A Bloch; D J McShane; J F Fries; N S Cooper; L A Healey; S R Kaplan; M H Liang; H S Luthra Journal: Arthritis Rheum Date: 1988-03
Authors: M Güler-Yüksel; C F Allaart; I Watt; Y P M Goekoop-Ruiterman; J K de Vries-Bouwstra; D van Schaardenburg; M V van Krugten; B A C Dijkmans; T W J Huizinga; W F Lems; M Kloppenburg Journal: Osteoarthritis Cartilage Date: 2010-08-05 Impact factor: 6.576