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Evidence-Based Complementary and Alternative Medicine
Volume 2011, Article ID 768492, 7 pages
Research Article

Clinical Approach to the Standardization of Oriental Medical Diagnostic Pattern Identification in Stroke Patients

Department of Cardiovascular & Neurologic Diseases (Stroke Center), College of Oriental Medicine, Kyung-Hee University, Seoul # 130-702, Republic of Korea

Received 9 November 2009; Revised 19 April 2010; Accepted 7 August 2010

Copyright © 2011 Han Jung Kim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In Korea, many stroke patients receive oriental medical care, in which pattern-identification plays a major role. Pattern-identification is Oriental Medicine's unique diagnostic system. This study attempted to standardize oriental medical pattern-identification for stroke patients. This was a community-based multicenter study that enrolled stroke patients within 30 days after their ictus. We assessed the patients' general characteristics and symptoms related to pattern-identification. Each patient's pattern was determined when two doctors had the same opinion. To determine which variables affect the pattern-identification, binary logistic regression analysis was used with the backward method. A total of 806 stroke patients were enrolled. Among 480 patients who were identified as having a certain pattern, 100 patients exhibited the Fire Heat Pattern, 210 patients the Phlegm Dampness Pattern, nine patients the Blood Stasis Pattern, 110 patients the Qi Deficiency Pattern, and 51 patients the Yin Deficiency Pattern. After the regression analysis, the predictive logistic equations for the Fire Heat, Phlegm Dampness, Qi Deficiency, and Yin Deficiency patterns were determined. The Blood Stasis Pattern was omitted because the sample size was too small. Predictive logistic equations were suggested for four of the patterns. These criteria would be useful in determining each stroke patient's pattern in clinics. However, further studies with large samples are necessary to validate and confirm these criteria.