We aimed to clarify the significance of using Kampo therapy centered on kamishoyosan and tokishakuyakusan together with general infertility treatment. The subjects were 41 women who visited a Kampo outpatient clinic for infertility and received general infertility treatment with Kampo therapy (Kampo group). The control group was 781 women who received only general infertility treatment at the same time (non-Kampo group). In comparing both groups, we conducted a retrospective survey on the pregnancy rate by cycle and the pregnancy rate by prescription. The pregnancy rate in the first cycle was 24.4% in the Kampo group and 8.5% in the non-Kampo group, and the pregnancy rate was higher in the Kampo group (P = 0.003). There was no difference in pregnancy rates after the second cycle. The pregnancy rate by prescription was 26.7% for kamishoyosan, 22.2% for tokishakuyakusan, and 8.5% for the non-Kampo group. In the comparison between the first cycle pregnant group and the non-pregnant group, the qi counter flow score was clearly higher in the first cycle pregnant group (P = 0.012). It is suggested that combined use of Kampo therapy including kamishoyosan and tokishakuyakusan may be effective from an early stage. Meanwhile, if pregnancy does not occur even after the combined use of Kamp therapy, it would be an opportunity to consider stepping up as Western medical therapy.

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.