Complex Networks Approach for Analyzing the Correlation of Traditional Chinese Medicine Syndrome Evolvement and Cardiovascular Events in Patients with Stable Coronary Heart Disease

This is a multicenter prospective cohort study to analyze the correlation of traditional Chinese medicine (TCM) syndrome evolvement and cardiovascular events in patients with stable coronary heart disease (CHD). The impact of syndrome evolvement on cardiovascular events during the 6-month and 12-month follow-up was analyzed using complex networks approach. Results of verification using Chi-square test showed that the occurrence of cardiovascular events was positively correlated with syndrome evolvement when it evolved from toxic syndrome to Qi deficiency, blood stasis, or sustained toxic syndrome, when it evolved from Qi deficiency to blood stasis, toxic syndrome, or sustained Qi deficiency, and when it evolved from blood stasis to Qi deficiency. Blood stasis, Qi deficiency, and toxic syndrome are important syndrome factors for stable CHD. There are positive correlations between cardiovascular events and syndrome evolution from toxic syndrome to Qi deficiency or blood stasis, from Qi deficiency to blood stasis, or toxic syndrome and from blood stasis to Qi deficiency. These results indicate that stable CHD patients with pathogenesis of toxin consuming Qi, toxin leading to blood stasis, and mutual transformation of Qi deficiency and blood stasis are prone to recurrent cardiovascular events

ZHENG-Omics Application in ZHENG Classification and Treatment: Chinese Personalized Medicine

With the hope to provide an effective approach for personalized diagnosis and treatment clinically, traditional chinese medicine (TCM) is being paid increasing attention as a complementary and alternative medicine. It performs treatment based on ZHENG (TCM syndrome) classification, which could be identified clinical special phenotypes by symptoms and signs of patients even if they have a different disease. However, it caused controversy because ZHENG classification only depends on observation, knowledge, and clinical experience of TCM practitioners, which lacks objectivity and repeatability. Although researchers and scientists of TCM have done some work with a lot of beneficial methods, the results could not reach satisfactory with the shortcomings of generalizing the entire state of the body or ignoring the patients' feelings. By total summary, mining, and integration of existing researches, the present paper attempts to introduce a novel macro-microconcept of ZHENG-omics, with the prospect of bright future in providing an objective and repeatable approach for Chinese personalized medicine in an effective way. In this paper, we give the brief introduction and preliminary validation, and discuss strategies and system-oriented technologies for achieving this goal

Application of Metabolomics in Traditional Chinese Medicine Differentiation of Deficiency and Excess Syndromes in Patients with Diabetes Mellitus

Metabolic profiling is widely used as a probe in diagnosing diseases. In this study, the metabolic profiling of urinary carbohydrates was investigated using gas chromatography/mass spectrometry (GC/MS) and multivariate statistical analysis. The kernel-based orthogonal projections to latent structures (K-OPLS) model were established and validated to distinguish between subjects with and without diabetes mellitus (DM). The model was combined with subwindow permutation analysis (SPA) in order to extract novel biomarker information. Furthermore, the K-OPLS model visually represented the alterations in urinary carbohydrate profiles of excess and deficiency syndromes in patients with diabetes. The combination of GC/MS and K-OPLS/SPA analysis allowed the urinary carbohydrate metabolic characterization of DM patients with different traditional Chinese medicine (TCM) syndromes, including biomarkers different from non-DM patients. The method presented in this study might be a complement or an alternative to TCM syndrome research

Epistemological issues in the theory of Chinese medicine

Traditional Chinese Medicine (TCM) has been criticized for being unscientific because the theory on which it is based involves entities like qi and ’meridians’ that appear ambiguous and because the internal ‘organs’ like the kidney and the spleen are very different from those of modern anatomy and physiology. Even more so, TCM methods of therapy based on the yin-yang principle, the model of the five elements, and the classification of illnesses according to standard constellations of symptoms (TCM “syndromes”) are largely unproven by the protocols of modern evidence-based medicine. This dissertation attempts to reconstruct TCM theory by: (a) providing explanations of TCM entities as abstractions and constructs that relate to observable body functions and illness symptoms and (b) interpreting TCM theory as comprising heuristic models that were constructed from clinical experience to fit empirical observations of illnesses and their treatments with herbal medications and acupuncture. It suggests that scientists should be less concerned with the ontological status of TCM entities and the epistemic credentials of TCM models than with the ability of these concepts and models to guide physicians in therapy. More importantly, it makes the argument that these models are testable using the methods of evidence-based medicine. There are methodological difficulties associated with randomized controlled trials partly because TCM treatments tend to be individualized and syndromes are dynamic in nature; observational trials may be more appropriate in some situations. It is also possible that, for patients who are more culturally attuned to TCM, the placebo effect is strongly at play and may render the real effects of TCM treatments harder to tease out in clinical trials. The dissertation concludes that the main postulates of TCM should be put to rigorous test. The result may be a leaner but more robust theory, with parts that do not stand up to the test being rejected or modified, and a possible acceptance of its more modest therapeutic claims for a limited range of pathological conditions like pain and chronic illnesses

Non-communicable Diseases, Big Data and Artificial Intelligence

This reprint includes 15 articles in the field of non-communicable Diseases, big data, and artificial intelligence, overviewing the most recent advances in the field of AI and their application potential in 3P medicine

CARDIOVASCULAR RISK REDUCTION, MEDICATION ADHERENCE AND SOCIO-ECONOMIC STATUS (SES)

Profound advances in cardiovascular disease (CVD) treatments have been made over the last two decades. However, poor adherence to preventative therapies remains a critical problem in the health of Canadians. Despite decades of research, contemporary knowledge about adherence is often based on theory that has not been confirmed with quantitative research findings. For example, adherence to preventative medications is widely considered to reduce risks for major health outcomes. However, major differences in the estimation of medication adherence benefits exist. Thus, a study was conducted to determine if the association between poor adherence and the risk of death was influenced by the method used to identify optimal adherence. The impact of adherence to statin medications on mortality was assessed among a cohort of 9,051 individuals who received a statin medication following discharge from a hospitalization for acute coronary syndrome (ACS). Using a fixed-summary measure, optimal adherence to statins was not associated with mortality benefits (adjusted HR 0.97, 95%CI 0.86 to 1.09, p=0.60). In contrast, the repeated measures approach resulted in a significant 25% reduction in the risk of death among adherent individuals (adjusted HR 0.75, 95%CI 0.67 to 0.85, p<0.01). However, neither estimate could be regarded as the most robust. Thus, until a gold standard method is established, researchers should report the estimates resulting from both methods. Among all adherence predictors, socioeconomic status (SES) is widely considered to be prominent because of its associations with many factors theoretically affecting adherence such as economic, social, and education-related features. However, published studies have reported inconsistent results about the impact of SES on adherence. A systematic review of published studies examining predictors of antihypertensive medications adherence was performed. Almost half of studies reviewed neglected to measure SES; and in studies where SES was measured, income assessment was typically the only measure. Overall, only a minor association between SES and adherence was observed after pooling all available data (pooled adjusted risk estimate for non-adherence according to SES (high versus low) 0.89, 95% CI 0.87 to 0.92; p<0.001). It was hypothesized that the performance of adherence prediction models would improve if SES was represented using more comprehensive measures. A retrospective cohort of individuals who received a statin medication following discharge from a hospitalization for coronary heart disease was identified and followed for one year. Multi-domain measures did not improve the prediction performance of the population adherence model compared to single-domain measures. Overall, all SES measures examined had a very limited impact on prediction adherence. Supporting patients to adhere to their medications is a vital goal health care providers strive to achieve. Non-adherence to preventative medications is highly prevalent among patients surviving acute coronary syndrome (ACS). However, only few patients receive appropriate care after their ACS through support programs such as cardiac rehabilitation (CR). Because pharmacist’s interventions were shown to have beneficial impact on medication adherence in various settings, a streamlined pharmacist’s intervention in CR setting was investigated through a randomized clinical trial. The impact of this intervention was assessed through the proportion of patients who achieved optimal adherence. Although this proportion did not improve among the intervention group in comparison to the control group, an unexpected high prevalence of optimal adherence was obtained. A selection bias of highly motivated individuals in this study may explain this extraordinary adherence level. Results of the four independent research studies included in this dissertation provide novel insight relating to the factors, outcomes, and possible modalities to mitigate non-adherence in Canada. Further research is essential to help in relieving this major population health problem