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.

[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.

Study of TCM Syndrome Identification Modes for Patients with Type 2 Diabetes Mellitus Based on Data Mining.

OBJECTIVE: To establish the diagnosis model for syndromes of type 2 diabetes mellitus (T2-DM) and explore symptoms, the pulse and tongue signs, and laboratory indexes related to syndromes of T2-DM. METHODS: A syndromatologic and laboratory investigation was conducted in 554 T2-DM patients with 58 symptoms, 14 tongue signs, 6 pulse signs, and 12 laboratory indexes. The clinical data on the syndrome were collected and analyzed by using logistic regression analysis, decision tree, and K-nearest neighbor to establish a diagnostic model for effectively distinguishing the typical syndromes in T2-DM patients. RESULTS: The most typical syndromes revealed in T2-DM were stomach heat flourishing (SHF) syndrome (261 patients, accounting for 47.1%) and Qi-Yin deficiency (QYD) syndrome (293 patients, 52.9%). According to the clinical data of the patients with these two syndromes, variables including 6 symptoms and signs, 2 pulse signs, 1 tongue sign, and 2 laboratory indicators were introduced into the logistic regression model. All of them were statistically significant. Then, a diagnostic model constructed by QUEST and CHAID algorithms of the decision tree for identifying the two syndromes was proved to have an accurate diagnostic rate of 85.2%. It was found that the following sign and symptoms were effective to differentiate these two syndromes: odor in the mouth, polyphagia, vulnerability to starvation, burning sensation in the stomach, fatigue, limb weakness, slippery and replete pulse, weak pulse, pink tongue, oral glucose tolerance test, and hemoglobin A1C. A classification model constructed by the K-nearest neighbor method to identify the two syndromes showed an accurate diagnostic rate of 88.3%. Three major statistically significant predictors included in the model were slippery and replete pulse, polyphagia, and weak pulse (P < 0.05). CONCLUSION: A model for distinguishing the two typical syndromes (SHF syndrome and QYD syndrome) in T2-DM patients was effectively established. This model could help to provide methodological support for the standardization of traditional Chinese medicine (TCM) syndrome differentiation methods.

Uncovering a broad class of fluorescent amine-containing compounds by heat treatment.

Amine-containing compounds including polymers, oligomers and small molecules, without conventional fluorophores, are found to emit strong visible fluorescence after a one-step heat treatment. Furthermore, our results demonstrate for the first time that not only tertiary amine groups but also primary and secondary amine groups can act as fluorescent moieties.