Tcm Syndromes Of Rheumatoid Arthritis Computer Pattern Recognition Method Applied Research

Objective: Rheumatic arthritis (RA) is a repeatedly paroxysmal disease which caused by many etiological factors. The superiority and soul of Traditional Chinese Medicine (TCM) are diagnosis and treatment on the basis of an overall analysis of the illness and the patient's condition, which is in terms of syndrome of the patient. Syndrome is a dynamic process. It is complicated in clinic and can easily be affected by the outside environment or by the doctor's subjectivity, which restrict the improvement of the differentiation technique and the clinical curative effect. In order to establish an effective system based on the modern science, directing the clinical diagnosis and treatment, we apply the computer pattern recognition to develop predictive models that can differentiate the syndrome of mixed cold and heat, obstructed channel by cold and dampness, deficiency of qi and yin etc, illuminating the relations between the syndromes through observing the clinical symptom, laboratory detection index of the RA patient. This may promote the measurement standard of the syndrome of RA. We hope we could, through this study, find an appropriate way of measuring the five syndromes of RA.Setting: the second hospital affiliated to Guangzhou University of Traditional Chinese Medicine.Patients/participants: All the patients involved in the study were the successive outpatients and inpatients of the department of rheumatic disease of the second hospital affiliated to Guangzhou University of Traditional Chinese Medicine from July, 1997 to Octomber, 1999. The selected cases were those meeting the revised ARA criteria for rheumatoid arthritis, 1987,30:17 and the revised criteria based on the clinical golden rule of Traditional Chinese Medicine.Main Outcome Measures: We apply computer pattern recognition to analyze the clinical symptom, physical sign and laboratory detection index of 202 RA patients,establishing a predictive model thai, can differentiate* I he syndrome of RA, illuminating the relations between the syndromes.Result: The computer pattern recognition shows that tve can't use one parameter to differentiate the syndrome of RA hut the ififonniilioM supplied by many parameters. Allergic to cold(冷), self-sensitivity of heat in joint (自觉发热), swelling of' joint (肿) were important variables to develop the model. Mahalanobis distance method shows the distinguishing accuracy of mixed cold and heat; is 96. the obstruction of dampness and heat in vessels and channels is 9(i. .'J%; the deficiency of <|i and yin is , which is the lowest: the obstruction of dampness and cold in vessels and channels is 97. 73%; the obstruction of phlegm and blond stasis in vessels and channels is 100%, which is the highest. The general accuracy of the 202 cases is 9. 5?, the predicting accuracy is 92.5%, and the general accuracy of 242 cases is 95.87%,, So we considered thai, the predictive models could be used to predict the syndrome of RA.Conclusions: The present study shows that the computer pattern recognition can be used to predict the differentiation of RA avoiding the subjective and hypotheses of the doctors, reducing the disturbance of subjective factors, turning the macroscopic differentiation into microcosmic differentiation, normal mng the RA diagnostic. So it can be broadly used in the clinic.