高齢者の健康管理におけるウェアラブルデバイスと中国伝統医学の役割

早大学位記番号:新8258早稲田大

Investigation into the Influence of Physician for Treatment Based on Syndrome Differentiation

Background. The characteristics of treatment based on syndrome differentiation (TBSD) cause great challenges to evaluate the effectiveness of the clinical methods. Objectives. This paper aims to evaluate the influence of physician to personalized medicine in the process of TBSD. Methods. We performed a randomized, triple-blind trial involving patients of primary insomnia treated by 3 physicians individually and independently. The patients (n=30) were randomly assigned to receive treatments by the 3 physicians for every visit. However, they always received the treatment, respectively, prescribed by the physician at the first visit. The primary outcome was evaluated, respectively, by the Pittsburgh Sleep Quality Index (PSQI) and the TCM symptoms measuring scale. The clinical practices of the physicians were recorded at every visit including diagnostic information, syndrome differentiation, treating principles, and prescriptions. Results. All patients in the 3 groups (30 patients) showed significant improvements (>66%) according to the PSQI and TCM symptoms measuring scale. Conclusion. The results indicate that although with comparable effectiveness, there exist significant differences in syndrome differentiation, the treating principles, and the prescriptions of the approaches used by the 3 physicians. This means that the physician should be considered as an important factor for individualized medicine and the related TCM clinical research

Application of Multilabel Learning Using the Relevant Feature for Each Label in Chronic Gastritis Syndrome Diagnosis

Background. In Traditional Chinese Medicine (TCM), most of the algorithms are used to solve problems of syndrome diagnosis that only focus on one syndrome, that is, single label learning. However, in clinical practice, patients may simultaneously have more than one syndrome, which has its own symptoms (signs). Methods. We employed a multilabel learning using the relevant feature for each label (REAL) algorithm to construct a syndrome diagnostic model for chronic gastritis (CG) in TCM. REAL combines feature selection methods to select the significant symptoms (signs) of CG. The method was tested on 919 patients using the standard scale. Results. The highest prediction accuracy was achieved when 20 features were selected. The features selected with the information gain were more consistent with the TCM theory. The lowest average accuracy was 54% using multi-label neural networks (BP-MLL), whereas the highest was 82% using REAL for constructing the diagnostic model. For coverage, hamming loss, and ranking loss, the values obtained using the REAL algorithm were the lowest at 0.160, 0.142, and 0.177, respectively. Conclusion. REAL extracts the relevant symptoms (signs) for each syndrome and improves its recognition accuracy. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice

Traditional Chinese medicine physicians’ insights into inter-professional tensions between traditional Chinese medicine and biomedicine: a critical perspective

In Singapore, the institutional preference for biomedicine and the cultural importance of traditional Chinese medicine (TCM) have created tensions between the two medical systems and erected barriers to a more collaborative healthcare system. This study foregrounds TCM physicians’ voice to reveal ideological struggles and power imbalances that underlie the inter-professional tensions and accompanying marginalization of TCM. Through in-depth interviews with 22 TCM physicians in Singapore, this study reveals the incongruences in ideological underpinnings between biomedicine and TCM, reflected in their different worldviews and epistemological approaches to knowledge formation and evaluation. Power differentials between the two medical systems are manifest in TCM physicians’ inferior position in relation to their biomedical peers, the patients’ internalization of biomedical standards to question the TCM profession and their own interest in seeking TCM treatments, and the state’s limited support for TCM research, subsidies, and service provision in hospital settings. The results suggest that more open dialogue about the dichotomous framings of biomedicine and TCM is key to disrupting the mutual reinforcement of ideology and power, as well as to creating increased mutual understanding between the two medical systems

Applying latent tree analysis to classify Traditional Chinese Medicine syndromes (Zheng) in patients with psoriasis vulgari

OBJECTIVE To treat patients with psoriasis vulgaris using Traditional Chinese Medicine (TCM), one must stratify patients into subtypes (known as TCM syndromes or Zheng) and apply appropriate TCM treatments to different subtypes. However, no unified symptom-based classification scheme of subtypes (Zheng) exists for psoriasis vulgaris. The present paper aims to classify patients with psoriasis vulgaris into different subtypes via the analysis of clinical TCM symptom and sign data. METHODS A cross-sectional survey was carried out in Beijing from 2005-2008, collecting clinical TCM symptom and sign data from 2764 patients with psoriasis vulgaris. Roughly 108 symptoms and signs were initially analyzed using latent tree analysis, with a selection of the resulting latent variables then used as features to cluster patients into subtypes. RESULTS The initial latent tree analysis yielded a model with 43 latent variables. The second phase of the analysis divided patients into three subtype groups with clear TCM Zheng connotations: 'blood deficiency and wind dryness'; 'blood heat'; and 'blood stasis'. CONCLUSIONS Via two-phase analysis of clinic symptom and sign data, three different Zheng subtypes were identified for psoriasis vulgaris. Statistical characteristics of the three subtypes are presented. This constitutes an evidence-based solution to the syndromedifferentiation problem that exists with psoriasis vulgaris

Exploration of Macro-Micro Biomarkers for Dampness-Heat Syndrome Differentiation in Different Diseases

Increased attention is being paid to traditional Chinese medicine (TCM) as a complementary and alternative medicine to provide an effective approach for personalized diagnosis and clinical treatment. TMC performs treatment based on differentiation of TCM syndrome (ZHENG), which may identify special phenotypes by symptoms and signs of patients even if they are in different diseases. There has, however, been skepticism and criticism because syndrome classification only depends on observation, knowledge, and clinical experience of TCM practitioners, which lacks objectivity and repeatability. In order to transform syndrome classification into mainstream medicine, we introduce a macro-micro approach that combines symptoms, clinical indicators, and metabolites. The present paper explores the macro-micro biomarkers of dampness-heat syndrome in chronic hepatitis B and nonalcoholic fatty liver patients, which could provide the basis for developing a possible population-screening tool for selecting target individuals and creating an evaluation index for personalized treatment

Metabolic Profiling Study of Yang Deficiency Syndrome in Hepatocellular Carcinoma by H

This study proposes a 1H NMR-based metabonomic approach to explore the biochemical characteristics of Yang deficiency syndrome in hepatocellular carcinoma (HCC) based on serum metabolic profiling. Serum samples from 21 cases of Yang deficiency syndrome HCC patients (YDS-HCC) and 21 cases of non-Yang deficiency syndrome HCC patients (NYDS-HCC) were analyzed using 1H NMR spectroscopy and partial least squares discriminant analysis (PLS-DA) was applied to visualize the variation patterns in metabolic profiling of sera from different groups. The differential metabolites were identified and the biochemical characteristics were analyzed. We found that the intensities of six metabolites (LDL/VLDL, isoleucine, lactate, lipids, choline, and glucose/sugars) in serum of Yang deficiency syndrome patients were lower than those of non-Yang deficiency syndrome patients. It implies that multiple metabolisms, mainly including lipid, amino acid, and energy metabolisms, are unbalanced or weakened in Yang deficiency syndrome patients with HCC. The decreased intensities of metabolites including LDL/VLDL, isoleucine, lactate, lipids, choline, and glucose/sugars in serum may be the distinctive metabolic variations of Yang deficiency syndrome patients with HCC. And these metabolites may be potential biomarkers for diagnosis of Yang deficiency syndrome in HCC