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Diagnostic Indicators for Blood Stasis Syndrome Patients with Gynaecological Diseases 被引量:3
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作者 Jeeyoun Jung Mi Mi Ko +2 位作者 Myeong Soo Lee So Min Lee Ju Ah Lee 《Chinese Journal of Integrative Medicine》 SCIE CAS CSCD 2018年第10期752-757,共6页
Objective: To investigate the important diagnostic indicators for blood stasis syndrome (BSS) in patients of childbearing age with gynaecological diseases. Methods: A partial least squared-discriminant analysis (... Objective: To investigate the important diagnostic indicators for blood stasis syndrome (BSS) in patients of childbearing age with gynaecological diseases. Methods: A partial least squared-discriminant analysis (PLS-DA) were applied to BSS symptoms data of patients with gynaecological diseases, and the diagnostic indicators used by doctors of Korean medicine (DKMs) among BSS patients with gynaecological diseases were also investigated. Results: A total of 103 patients of childbearing age with gynaecological diseases and 40 healthy controls were enrolled. Among the 103 patients, 63 (61.7%) and 40 (38.8%) were diagnosed with BSS and non-BSS, respectively, and BSS patients exhibited a more severe extent of disease. A score plot of PLS-DA showed clearly different patterns among the 3 groups. Based on the variable importance on projection of PLS-DA model, menstrual pains, dark lumps in the menstrual blood, ileocoecal tenderness and resistance, sharp pains, and sublingual varicosities were selected as the top five most important indicators. Moreover, more than 75% of DKMs chose dark lumps in menstrual blood, menstrual pain, and dark menstrual blood as the diagnostic indicators of BSS in patients with gynaecological diseases, and more than 49% of them also considered sharp pains, dark red tongue, sublingual varicosities, and tendency to bruise easily as diagnostic indicators of BSS. Conclusion: DKMs focused on menstrual symptoms and certain gynaecological symptoms to diagnose BSS patients of childbearing age with female diseases. 展开更多
关键词 blood stasis syndrome DIAGNOSIS gynaecological disease pattern identification
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