ABSTRACT
Traditional Chinese medicine(TCM) carries the experience and theoretical knowledge of the ancients, and the use of "toxic" Chinese medicines is a major feature and advantage of TCM. "Toxic" Chinese medicines have unique clinical value and certain medication risk under the guidance of TCM theories such as compatibility for detoxification and treatment based on syndrome differentiation. In recent years, the safety events of Chinese medicines have occurred frequently, which has made the safety of Chinese medicine a public concern in China and abroad. However, limited by conventional cognitive laws and technical methods, basic research on toxicity of Chinese medicines fails to be combined with the clinical application. As a result, it is difficult to identify the clinical characteristics of, predict toxic and side effects of, or form a universal precise medication regimen for "toxic" Chinese medicines, which restricts the clinical application of them. In view of the problem that the toxicity of "toxic" Chinese medicines is difficult to be predicted and restricts the clinical application, the evidence-based research concept will provide new ideas for safe applcation of them in clinical practice. The integrated development of multiple disciplines and techniques in the field of big data and artificial intelligence will also promote the renewal and development of the research models for "toxic" Chinese medicines. Our team tried to propose the academic concept of evidence-based Chinese medicine toxicology and establish the data-intelligence research mode for "toxic" Chinese medicines and the intelligent risk prediction method for medicinal combination in the early stage, which provided methodological supports for solving the above problem. Thus, on the basis of summarizing the research status and problems of the clinical medication regimen of "toxic" Chinese medicines, our team took the evidence-based toxicology of TCM as the core concept, and tried to construct the multiple-evidence integrated evaluation and prediction method for "toxic" Chinese medicine, so as to guide the establishment of the non-toxic medication regimen of "toxic" Chinese medicines. Specifically, through the analysis of multivariate data obtained from the basic research, the evidence-based toxicology database of Chinese medicines and the individualized "toxicity-effect" intelligent prediction platform were built based on the disease-syndrome virtual patients, so as to identify the clinical characteristics and risks of "toxic" Chinese medicines and develop individualized medication regime. This study is expected to provide a methodological reference for the establishment of medication regimen and risk prevention strategy for "toxic" Chinese medicines. The method established in this study will bridge clinical research and basic research, enhance the transformation of the scientific connotation of attenuated compatibility, promote the development of evidence-based Chinese medicine toxicology, and ensure the clinical safety of "toxic" Chinese medicines.
Subject(s)
Artificial Intelligence , China , Drugs, Chinese Herbal/pharmacology , Humans , Medicine, Chinese Traditional , Research Design , SyndromeABSTRACT
BACKGROUND@#Traditional Chinese exercises (TCEs) have a positive effect on glycemic control and hemoglobin A1c (HbA1c), but there is no consensus on the benefits of TCEs for patients with prediabetes.@*OBJECTIVE@#The objective of this study was to systematically investigate the effects of TCEs on blood glucose control in patients with prediabetes.@*SEARCH STRATEGY@#Comprehensive retrieval of randomized controlled trials (RCTs) was carried out using PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure, VIP Database for Chinese Technical Periodicals, Wanfang Data Knowledge Service Platform, China Biology Medicine disc, Google Scholar and Baidu academic databases. The retrieval window ranged from the establishment of the database to December 2018, and references related to the included trials were searched without language restrictions.@*INCLUSION CRITERIA@#The study included RCTs with a clinical diagnosis of prediabetes that was also treated with TCEs.@*DATA EXTRACTION AND ANALYSIS@#Literature screening, data extraction and literature quality assessment were performed independently by two researchers. In the case of disagreement, a third party was invited to negotiate and make a decision. Standardized mean difference (SMD) was used to estimate the therapeutic effect. Meta-analysis was performed using Review Manager 5.3.5 and Stata 15.0. Heterogeneity was assessed using Q test and I, and the source of heterogeneity was determined using Galbraith diagram and sensitivity analysis. A Q test resulting in P 50% indicated significant difference and random effect model analysis was performed. Otherwise, a fixed effect model was applied. Begg's and Egger's tests were used to assess publication bias.@*RESULTS@#Nine RCTs involving 485 participants were included in this study. The results showed that TCEs could reduce fasting blood glucose (FBG), 2 h blood glucose (2hPBG) and HbA1c in patients with prediabetes. The treatment subgroup showed that an intervention of 6 months had better results, while the Gongfa subgroup showed that the TCE Baduanjin yielded better results. (1) FBG: SMD = -0.73, 95% confidence interval (CI) [-0.97, -0.50], P < 0.00001; Baduanjin: SMD = -0.83, 95% CI [-1.13, -0.53], P < 0.00001; 6 month treatment: SMD = -0.73, 95% CI [-1.20, -0.26], P = 0.002. (2) 2hPBG: SMD = -0.75, 95% CI [-0.94, -0.57], P < 0.00001; Baduanjin: SMD = -0.62, 95% CI [-0.91, -0.32], P < 0.00001; 6 month treatment: SMD = -0.91, 95% CI [-1.39, -0.44], P = 0.0002. (3) HbA1c: SMD = -0.56, 95% CI [-0.89, -0.23], P = 0.00008; Baduanjin: SMD = -0.46, 95% CI [-0.83, -0.08], P = 0.02; 6 month treatment: SMD = -0.77, 95% CI [-1.24, -0.29], P = 0.002.@*CONCLUSION@#TCEs had positive effects in improving blood glucose levels in patients with prediabetes. Hence, TCEs may be of potential therapeutic value for patients with prediabetes, as an adjuvant therapy along with other treatments. Although the evidence suggests that the intervention is effective for 6 months, the mechanism of TCEs on glycemic control, the minimum exercise dose and their safety remain to be further studied.
ABSTRACT
Diabetes has become a global public health problem that seriously threatens human health. Traditional Chinese medicine, the characteristics of the role of multiple targets, has a unique advantage in the prevention and treatment of diabetes mellitus and its complications. Astragaloside-Ⅳ (AS-Ⅳ), one of the main activities of Astragalus membranaceus, has a series of pharmacological effects including improvement in the function of endothelial cells and neovascularization, anti-inflammatory, antioxidant, regulating energy metabolism, protectionnervous, anti-cancer and so on. In this paper, AS-Ⅳ to prevent and treat diabetes and its complications has been reviewed, which has effect on lowering blood sugar, lowering blood pressure, improving insulin resistance, inhibiting inflammatory reaction and oxidative stress. Additionally, it also can improve the diabetic animal and cell model of diabetic vascular disease, diabetic nephropathy, diabetic retinopathy, diabetic peripheral neuropathy, diabetic cardiomyopathy and other pathological damages. AS-Ⅳ may be a potential active substance for the treatment of diabetes and its complications.