Prediction Model for Deficiency-Excess Patterns, Including Medium Pattern

Ayako Maeda-minami; Tetsuhiro Yoshino; Kotoe Katayama; Yuko Horiba; Hiroaki Hikiami; Yutaka Shimada; Takao Namiki; Eiichi Tahara; Kiyoshi Minamizawa; Shinichi Muramatsu; Rui Yamaguchi; Seiya Imoto; Satoru Miyano; Hideki Mima; Masaru Mimura; Tomonori Nakamura; Kenji Watanabe

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Prediction Model for Deficiency-Excess Patterns, Including Medium Pattern

VernacularTitle:虚実中間証を含む虚実証の予測モデル
Author: Ayako MAEDA-MINAMI ¹ ; Tetsuhiro YOSHINO ² ; Kotoe KATAYAMA ³ ; Yuko HORIBA ² ; Hiroaki HIKIAMI ⁴ ; Yutaka SHIMADA ⁵ ; Takao NAMIKI ⁶ ; Eiichi TAHARA ⁷ ; Kiyoshi MINAMIZAWA ⁸ ; Shinichi MURAMATSU ⁹ ; Rui YAMAGUCHI ¹⁰ ; Seiya IMOTO ¹¹ ; Satoru MIYANO ¹² ; Hideki MIMA ¹³ ; Masaru MIMURA ² ; Tomonori NAKAMURA ¹ ; Kenji WATANABE ²
Author Information

1. Division of Pharmaceutical Care Sciences, Graduate School of Pharmacy, Keio University
2. Center for Kampo Medicine, Keio University School of Medicine
3. Laboratory of Sequence Analysis, Human Genome Center, the Institute of Medical Science, University of Tokyo
4. Shikino Care Center
5. Department of Japanese Oriental (Kampo) Medicine, School of Medicine, University of Toyama
6. Department of Japanese Oriental (Kampo) Medicine, Graduate School of Medicine, Chiba University
7. Department of Japanese Oriental (Kampo) Medicine, Oriental Medical Center, Iizuka Hospital
8. Department of Oriental Medicine, Kameda Medical Center
9. Division of Oriental Medicine, Center of Community Medicine, Jichi Medical University
10. Division of System Analysis, Aichi Cancer Center Research Institute
11. Division of Health medical Data Science, Health Intelligence Center, The Institute of Medical Science, The University of Tokyo
12. Laboratory of DNA Information Analysis, Human Genome Center, the Institute of Medical Science, University of Tokyo
13. Center for Research and Development of Higher Education, University of Tokyo
Keywords: questionnaire; predictive model for deficiency-excess pattern diagnosis; medium pattern; random forest
From:Kampo Medicine 2020;71(4):315-325
CountryJapan
Language:Japanese
Abstract: We have previously reported on a predictive model for deficiency-excess pattern diagnosis that was unable to predict the medium pattern. In this study, we aimed to develop predictive models for deficiency, medium,and excess pattern diagnosis, and to confirm whether cutoff values for diagnosis differed between the clinics. We collected data from patients' first visit to one of six Kampo clinics in Japan from January 2012 to February 2015. Exclusion criteria included unwillingness to participate in the study, missing data, duplicate data, under 20 years old, 20 or less subjective symptoms, and irrelevant patterns. In total, 1,068 participants were included. Participants were surveyed using a 153-item questionnaire. We constructed a predictive model for deficiency, medium, and excess pattern diagnosis using a random forest algorithm from training data, and extracted the most important items. We calculated predictive values for each participant by applying their data to the predictive model, and created receiver operating characteristic (ROC) curves with excess-medium and medium-deficiency patterns. Furthermore, we calculated the cutoff value for these patterns in each clinic using ROC curves, and compared them. Body mass index and blood pressure were the most important items. In all clinics, the cutoff values for diagnosis of excess-medium and medium-deficiency patterns was > 0.5 and < 0.5, respectively. We created a predictive model for deficiency, medium, and excess pattern diagnosis from the data of six Kampo clinics in Japan. The cutoff values for these patterns fell within a narrow range in the six clinics.