Objective To evaluate the quality of randomized controlled trials (RCTs) of traditional Chinese medicine published inChinese Journal of Integrated Traditional and Western Medicine, and to analyze changes. Methods We searched CNKI to collect RCTs published inChinese Journal of Integrated Traditional and Western Medicine (CJITWM) in 2014. Reporting quality of RCTs was evaluated by using CONSORT 2010 checklist, the methodological quality and ethics requirements were also analyzed. The changes of quality was also analyzed by comparing with those of 2004. Results A total of 80 RCTs were included. The top three interventions were Chinese patent medicine, decoction, acupuncture. Items with high reporting rate (>80%) included abstract, participants, randomization sequences and informed consent. Items with reporting rate of 50% to 80% including introduction, interventions, harms and funding, and others were all less than 50%. Among them, the reporting quality of title, trial design, outcomes, sample size, type of randomization, allocation concealment, blinding, numbers analyzed, outcomes and estimation, generalizability, interpretation, registration and protocol was less than 10%. Compared with those of 2004, the quality of reporting, methodology, and ethics has all increased. Significant progress was made in items of structured summary, background and objectives, collecting participants, adverse reactions, quality control standards of TCM interventions, diagnostic evaluation criteria of TCM, follow-up, funding, ethical approval and informed consent. But small progress was made in randomization, allocation concealment and implementation, sample size, blinding and ITT. There has been no participant flow. Conclusion The quality of reporting, methodology, and ethics of RCTs published inChinese Journal of Integrated Traditional and Western Medicine have made some progress, however, trial design, outcomes selection, estimation of sample size, randomization, blinding, registration and participant flow are still needed to be further improved.
Different from modern medicine, traditional Chinese medicine (TCM) has its unique thought patterns and decision methods. In the process of developing TCM clinical practice guidelines, not only the modern clinical researches should be included, but also the TCM ancient books which had influenced TCM for thousands of years should be included. As an important carrier of TCM, the characteristics of researches in TCM ancient books are different from modern clinical researches. In this paper, we introduced the present situation of the TCM guidelines and how to use TCM ancient books for developing TCM clinical guideline with the guidance of evidence-based method. We used the example of developing of headache TCM guideline to explain how to use TCM ancient books as evidence source for guideline development and explored the application of evidence-based research of TCM ancient books to promote TCM clinical guidelines development.
Clinical efficacy evaluation is important for the development of traditional Chinese medicine (TCM). In view of the existing accumulation and current situation of the TCM clinical efficacy evaluation, based on the international perspective, and taking the rational and objective evaluation of TCM clinical efficacy and safety as the foundation, in order to enhance TCM evidence level to support clinical decision-making and promote TCM industry and TCM internationalization development, the State Administration of TCM entrusted China Academy of Chinese Medical Sciences to establish China Center for Evidence Based Traditional Chinese Medicine (CCEBTCM). CCEBTCM is expected to optimize the allocation of evidence-based research resources in TCM field to further integrate advantages of evidence-based TCM research teams, promote consensus on evidence-based TCM standards, share evidence-based TCM data or information and lead cultural exchanges between Chinese and overseas. In this way, the status and influence of TCM in the world will be enhanced so that it can better serve global health.
Since the concept of core outcome set (COS) was introduced into clinical trials of traditional Chinese medicine (TCM), researchers have paid much more attention to develop COS for specific diseases. Although researchers believe that the characteristics of TCM, such as syndromes, should be considered in the COS of TCM, it was insufficiently addressed. In addition, the naming of TCM syndromes has not been standardized, and the classification and diagnostic criteria for specific diseases have been inconsistent. Thus, it is difficult to include TCM syndromes in the COS. Different diseases may show similar TCM syndromes which makes research difficult. Based on previous studies, this paper provided methods of developing core TCM syndromes set according to the model of combination of disease and syndrome and the model of syndrome dominating disease to provide references for future researches.
Objective This study aimed to analyze the differences between the distribution of Traditional Chinese Medicine (TCM) syndrome elements and salivary microbiota between the individuals with pulmonary nodules and those without. Additionally, it seeked to explore the potential correlation between the distribution of Traditional Chinese Medicine (TCM) syndrome elements and salivary microbiota in patients with pulmonary nodules. Methods We retrospectively recruited 173 patients with pulmonary nodules (PN) and 40 healthy controls (HC). The four diagnostic information was collected from all participants, and syndrome differentiation method was used to analyze the distribution of Traditional Chinese Medicine (TCM) syndrome elements in both groups. Saliva samples were obtained from the subjects for 16S rRNA high-throughput sequencing to obtain differential microbiota and to explore the correlation between Traditional Chinese Medicine (TCM) syndrome elements and salivary microbiota in the evolution of the pulmonary nodule disease. Results The study found that in the PN group, the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease location were the lung and liver, and the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease nature were yin deficiency and phlegm. In the HC group, the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease location were the lung and spleen, and the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease nature were dampness and qi deficiency. There were differences between the two groups in the distribution of Traditional Chinese Medicine (TCM) syndrome elements related to disease location (lung, liver, kidney, exterior, heart) and disease nature (yin deficiency, phlegm, qi stagnation, qi deficiency, dampness, blood deficiency, heat, blood stasis) (P<0.05). The species abundance of the salivary microbiota was higher in the PN group than that in the HC group (P<0.05), and there were significant differences in community composition between the two groups (P<0.05). Correlation analysis using multiple methods, including Mantel test network heatmap analysis and Spearman correlation analysis and so on, showed that in the PN group, Prevotella and Porphyromonas were positively correlated with disease location in the lung, and Porphyromonas and Granulicatella were positively correlated with disease nature in yin deficiency (P<0.05). Conclusion The study concludes that there are notable differences in the distribution of Traditional Chinese Medicine (TCM) syndrome elements and the species abundance and composition of salivary microbiota between patients with pulmonary nodules and healthy individuals. The distinct external syndrome manifestations in patients with pulmonary nodules, compared to healthy individuals, may be a cascade event triggered by changes in the salivary microbiota. The dual correlation of Porphyromonas with both disease location and nature suggests that changes in its abundance may serve as an objective indicator for the improvement of symptoms in patients with yin deficiency-type pulmonary nodules.
Purpose To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. MethodsThe study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the department of cardiothoracic surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including Random Forest (RF), k-Nearest Neighbor (KNN), logistic Regression (LR), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results(1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%. Conclusion Electronic nose combined with machine learning not only has the potential to differentiate the benign and malignant pulmonary nodules but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.