Association between color value of tongue and T2DM based on dose-response analyses using restricted cubic splines in China: A cross-sectional study.

This study aimed to explore the relationship between international commission on illumination (CIE) L*a*b* color value of tongue and type 2 diabetes mellitus (T2DM). We used restricted cubic spline method and logistic regression method to assess the relationship between CIE L*a*b* color value of tongue and T2DM. A total of 2439 participants (991 T2DM and 1448 healthy) were included. A questionnaire survey and tongue images obtained with tongue diagnosis analysis-1 were analyzed. As required, chi-square and t tests were applied to compare the T2DM and healthy categories. Our findings suggest the 95% confidence interval and odds ratio for body mass index, hypertension, and age were 0.670 (0.531-0.845), 13.461 (10.663-16.993), and 2.595 (2.324-2.897), respectively, when compared to the healthy group. A linear dose-response relationship with an inverse U-shape was determined between CIE L* and CIE a* values and T2DM (P < .001 for overall and P < .001 for nonlinear). Furthermore, U-shaped and linear dose-response associations were identified between T2DM and CIE b* values (P = .0160 for nonlinear). Additionally, in adults, the CIE L*a*b* color value had a correlation with T2DM. This novel perspective provides a multidimensional understanding of traditional Chinese medicine tongue color, elucidating the potential of CIE L*a*b* color values of tongue in the diagnosis of T2DM.

Research Status and Trends of Traditional Chinese Medicine Therapeutic Formulae for Coronary Heart Disease Scientometrics Research.

Aim of the Study: This study analyzes research on TCM formulae in CHD over the past 30 years, using VOSviewer and CiteSpace. It aims to highlight key trends and hotspots in the field. Materials and Methods: The core database of Web of Science was collected, and the search time range was from the establishment of the database to the present (August 2023) for the literature related to the study of TCM prescriptions in CHD, and the information on the number of literature, countries, journals, authors, institutions, keywords were summarized by applying the software VOSviewer and CiteSpace. Results: A total of 135 kinds of literature were included. The number of published journal papers on research on TCM therapeutic formulae for CHD showed an upward trend; China was the most prolific country in this field; the largest number of papers were published in Evid Based Complement Alternat Med, MEDICINE; the average number of citations for authors and institutional analysis revealed that Xu Hao of China Academy of Traditional Chinese Medicine, Mao Jingyuan of Tianjin University of Traditional Chinese Medicine, and Shang Hongcai of Beijing University of Traditional Chinese Medicine constituted the core team of researchers studying the study of TCM formulae for CHD; the keyword analysis suggests that there are mainly 42 specifically named TCM formulae for the treatment of CHD, which are classified into a total of 7 major categories, and the research direction is mainly in the clinical efficacy study of different TCM therapeutic formulae and other aspects. Conclusion: This study shows that there are more types of TCM therapeutic formulae for CHD, and the related research has a good prospect. It is foreseeable that more relevant research results will rely on the study of network pharmacology, signalling pathways, and action targets of TCM therapeutic formulae.

Predictive value of TCM clinical index for diabetic peripheral neuropathy among the type 2 diabetes mellitus population: A new observation and insight.

Aims: The objectives of this study were to identify clinical predictors of the Traditional Chinese medicine (TCM) clinical index for diabetic peripheral neuropathy (DPN) in type 2 diabetes mellitus (T2DM) patients, develop a clinical prediction model, and construct a nomogram. Methods: We collected the TCM clinical index from 3590 T2DM recruited at the Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine from January 2019 to October 2020. The participants were randomly assigned to either the training group (n = 3297) or the validation group (n = 1426). TCM symptoms and tongue characteristics were used to assess the risk of developing DPN in T2DM patients. Through 5-fold cross-validation in the training group, the least absolute shrinkage and selection operator (LASSO) regression analysis method was used to optimize variable selection. In addition, using multifactor logistic regression analysis, a predictive model and nomogram were developed. Results: A total of eight independent predictors were found to be associated with the DPN in multivariate logistic regression analyses: advanced age of grading (odds ratio/OR 1.575), smoke (OR 2.815), insomnia (OR 0.557), sweating (OR 0.535), loose teeth (OR 1.713), dry skin (OR 1.831), purple tongue (OR 2.278). And dark red tongue (OR 0.139). The model was constructed using these eight predictor's medium discriminative capabilities. The area under the curve (AUC) of the training set is 0.727, and the AUC of the validation set is 0.744 on the ROC curve. The calibration plot revealed that the model's goodness-of-fit is satisfactory. Conclusions: We established a TCM prediction model for DPN in patients with T2DM based on the TCM clinical index.

Current status and trends of artificial intelligence research on the four traditional Chinese medicine diagnostic methods: a scientometric study.

Background: With the development of technology and the renewal of traditional Chinese medicine (TCM) diagnostic equipment, artificial intelligence (AI) has been widely applied in TCM. Numerous articles employing this technology have been published. This study aimed to outline the knowledge and themes trends of the four TCM diagnostic methods to help researchers quickly master the hotspots and trends in this field. Four TCM diagnostic methods is a TCM diagnostic method through inspection, listening, smelling, inquiring and palpation, the purpose of which is to collect the patient's medical history, symptoms and signs. Then, it provides an analytical basis for later disease diagnosis and treatment plans. Methods: Publications related to AI-based research on the four TCM diagnostic methods were selected from the Web of Science Core Collection, without any restriction on the year of publication. VOSviewer and Citespace were primarily used to create graphical bibliometric maps in this field. Results: China was the most productive country in this field, and Evidence-Based Complementary and Alternative Medicine published the largest number of related papers, and the Shanghai University of Traditional Chinese Medicine is the dominant research organization. The Chengdu University of Traditional Chinese Medicine had the highest average number of citations. Jinhong Guo was the most influential author and Artificial Intelligence in Medicine was the most authoritative journal. Six clusters separated by keywords association showed the range of AI-based research on the four TCM diagnostic methods. The hotspots of AI-based research on the four TCM diagnostic methods included the classification and diagnosis of tongue images in patients with diabetes and machine learning for TCM symptom differentiation. Conclusions: This study demonstrated that AI-based research on the four TCM diagnostic methods is currently in the initial stage of rapid development and has bright prospects. Cross-country and regional cooperation should be strengthened in the future. It is foreseeable that more related research outputs will rely on the interdisciplinarity of TCM and the development of neural networks models.

An Overview of Systematic Reviews: Acupuncture in the Treatment of Essential Hypertension.

Objective: Acupuncture treatment is widely used for essential hypertension (EH), and numerous systematic reviews on acupuncture for EH have been published. This article provides an overview of the effectiveness and safety of acupuncture for EH and assesses the quality of reports, methodological bias, quality of evidence and risk of bias for inclusion in the evaluation. Methods: Two researchers independently computer searched Pubmed, EMbase, The Cochrane library, WOS, CBM, CNKI, Wangfang Data, VIP and other Chinese and English databases with a search time frame from the date of creation to 13th October 2022; and independently screened systematic reviews of acupuncture therapy for EH; and finally The Report Quality Assessment Tool (PRISMA 2020), Methodological Quality Assessment Tool (AMSTAR2), Grading of Evidence Assessment Tool (GRADE), and Bias Assessment Tool (ROBIS) were used independently to assess the bias of the included literature. Results: A total of 11 systematic reviews were included. The included studies mainly reported on outcome indicators such as efficiency rate, end SBP, end DBP, SBP change value, DBP change value, etc. Deficiencies in the quality of PRISMA 2020 reporting were mainly in the areas of independent screening by multiple researchers, use of GRADE for analysis, early registration, description of conflict of interest, and public access to information; the results of the AMSTAR 2 tool evaluation were mostly were very low, and of the 16 entries affecting the methodological quality of the systematic evaluation, entries 2/3/4/5/12/16 had the greatest methodological bias; GRADE assessed the quality of evidence for key outcome indicators, with a few being low and all others being very low; and ROBIS reported a high level of bias in the literature. Conclusion: Current acupuncture has some efficacy in the treatment of essential hypertension, but its quality of evidence is low. It is hoped that the quality of relevant literature reporting, methodological quality, quality of evidence, and bias will improve.

Abnormal bile acid metabolism is an important feature of gut microbiota and fecal metabolites in patients with slow transit constipation.

Destructions in the intestinal ecosystem are implicated with changes in slow transit constipation (STC), which is a kind of intractable constipation characterized by colonic motility disorder. In order to deepen the understanding of the structure of the STC gut microbiota and the relationship between the gut microbiota and fecal metabolites, we first used 16S rRNA amplicon sequencing to evaluate the gut microbiota in 30 STC patients and 30 healthy subjects. The α-diversity of the STC group was changed to a certain degree, and the ß-diversity was significantly different, which indicated that the composition of the gut microbiota of STC patients was inconsistent with healthy subjects. Among them, Bacteroides, Parabacteroides, Desulfovibrionaceae, and Ruminiclostridium were significantly upregulated, while Subdoligranulum was significantly downregulated. The metabolomics showed that different metabolites between the STC and the control group were involved in the process of bile acids and lipid metabolism, including taurocholate, taurochenodeoxycholate, taurine, deoxycholic acid, cyclohexylsulfamate, cholic acid, chenodeoxycholate, arachidonic acid, and 4-pyridoxic acid. We found that the colon histomorphology of STC patients was significantly disrupted, and TGR5 and FXR were significantly downregulated. The differences in metabolites were related to changes in the abundance of specific bacteria and patients' intestinal dysfunction. Analysis of the fecal genomics and metabolomics enabled separation of the STC from controls based on random forest model prediction [STC vs. control (14 gut microbiota and metabolite biomarkers)-Sensitivity: 1, Specificity: 0.877]. This study provided a perspective for the diagnosis and intervention of STC related with abnormal bile acid metabolism.

[Evaluation of methodological and reporting quality of domestic clinical guidelines for hyperuricemia].

This study aims to evaluate the methodological and reporting quality of diagnosis and treatment guidelines for hyperuricemia as well as the expert consensuses and promote the understanding and application of the diagnosis and treatment guidelines for hyperuricemia. With "hyperuricemia" "guidelines" "consensus" "recommendations" as the key words in titles, the authors searched for the published clinical guidelines on hyperuricemia in Chinese against CNKI, Wanfang, VIP, Medlive and the official website of the industry association. The retrieval time limit was until May 31, 2021. The appraisal of guidelines for research and evaluation Ⅱ(AGREEⅡ) and the reporting items for practice guidelines in health care(RIGHT) were employed to evaluate the methodological quality and reporting quality of 14 guidelines/consensuses included. The average scores of the guidelines/consensuses were 80.85%(48.61%-98.61%) for the domain of scope and purpose, 34.52%(0-69.44%) for the domain of stakeholder involvement, 35.53%(6.25%-92.19%) for the domain of rigor of development, 55.85%(23.61%-86.11%) for the domain of clarity of presentation, 26.19%(0-76.04%) for the domain of applicability, and 21.42%(0-50.00%) for the domain of editorial independence. Nine guidelines/consensuses were of medium overall quality with grade B recommendation, and five guidelines/consensuses were of poor quality with grade C recommendation. The RIGHT classified the fourteen guidelines/consensuses into one of high reporting quality, three of medium reporting quality, and ten of low reporting quality. The results of this study indicate that the standardization and rigor of the methodological quality and the reporting quality of the clinical guidelines/consensuses for hyperuricemia in China remain to be strengthened.