중풍 변증 모델에 의한 진단 정확률과 예측률 비교
Comparison of Diagnostic Accuracy and Prediction Rate for between two Syndrome Differentiation Diagnosis Models
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초록
In spite of abundant clinical resources of stroke patients, the objective and logical data analyses or diagnostic systems were not established in oriental medicine. In the present study we tried to develop the statistical diagnostic tool discriminating the subtypes of oriental medicine diagnostic system, syndrome differentiation (SD).Discriminant analysis was carried out using clinical data collected from 1,478 stroke patients with the same subtypes diagnosed identically by two clinical experts with more than 3 year experiences. Numerical discriminant models were constructed using important 61 symptom and syndrome indices. Diagnostic accuracy and prediction rate of 5 SD subtypes: The overall diagnostic accuracy of 5 SD subtypes using 61 indices was 74.22%. According to subtypes, the diagnostic accuracy of "phlegm-dampness" was highest (82.84%), and followed by "qi-deficiency", "fire/heat", "static blood", and "yin-deficiency". On the other hand, the overall prediction rate was 67.12% and that of qi-deficiency was highest (73.75%). Diagnostic accuracy and prediction rate of 4 SD subtypes: The overall diagnostic accuracy and prediction rate of 4 SD subtypes except "static blood" were 75.06% and 71.63%, respectively. According to subtypes, the diagnostic accuracy and prediction rate was highest in the "phlegm-dampness" (82.84%) and qi-deficiency (81.69%), respectively. The statistical discriminant model of constructed using 4 SD subtypes, and 61 indices can be used in the field of oriental medicine contributing to the objectification of SD.
Abstract
In spite of abundant clinical resources of stroke patients, the objective and logical data analyses or diagnostic systems were not established in oriental medicine. In the present study we tried to develop the statistical diagnostic tool discriminating the subtypes of oriental medicine diagnostic system, syndrome differentiation (SD).Discriminant analysis was carried out using clinical data collected from 1,478 stroke patients with the same subtypes diagnosed identically by two clinical experts with more than 3 year experiences. Numerical discriminant models were constructed using important 61 symptom and syndrome indices. Diagnostic accuracy and prediction rate of 5 SD subtypes: The overall diagnostic accuracy of 5 SD subtypes using 61 indices was 74.22%. According to subtypes, the diagnostic accuracy of "phlegm-dampness" was highest (82.84%), and followed by "qi-deficiency", "fire/heat", "static blood", and "yin-deficiency". On the other hand, the overall prediction rate was 67.12% and that of qi-deficiency was highest (73.75%). Diagnostic accuracy and prediction rate of 4 SD subtypes: The overall diagnostic accuracy and prediction rate of 4 SD subtypes except "static blood" were 75.06% and 71.63%, respectively. According to subtypes, the diagnostic accuracy and prediction rate was highest in the "phlegm-dampness" (82.84%) and qi-deficiency (81.69%), respectively. The statistical discriminant model of constructed using 4 SD subtypes, and 61 indices can be used in the field of oriental medicine contributing to the objectification of SD.
참고문헌 (6)
- 한의진단명과 진단요건의 표준화연구(Ⅰ), "양기상", 한국한의학연구소, ~ (1995)
- 한의진단명과 진단요건의 표준화연구(Ⅱ), "양기상", 한국한의학연구소, ~ (1996)
- 한의진단명과 진단요건의 표준화연구(Ⅲ), "신순식", 한국한의학연구소, ~ (1997)
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- 강병갑, "중풍의 변증 진단을 위한 판별모형", 한국한의학연구원논문집, 13(2), pp.59~64 (2007)
- 신양규, "중풍의 중형 진단을 위한 판별모형", Journal of Statistical Theory & Methods, (7), pp.283~287 (1996)