Dataset Information

Current Status and Evaluation of Randomized Clinical Trials of Traditional Chinese Medicine in the Treatment of Cardiovascular Diseases.

ABSTRACT: Traditional Chinese medicine has long been applied to various diseases in China for a few thousand years. In recent years, its market has gradually developed from Asian countries to Western countries. At present, due to the lack of evidence-based medicine research, the effect of traditional Chinese medicine on the prevention and treatment of cardiovascular disease remains unclear. In evaluating the efficacy and safety of drugs, randomized controlled clinical trials (RCTs) are recognized as the gold standard for testing the effectiveness and safety of treatments and could offer the best evidence for the formulation of clinical treatment guidelines. Although traditional Chinese medicine has long been used to treat cardiovascular diseases, the research on the application of RCT to test the combination of traditional Chinese and Western medicine therapy or single traditional Chinese medicine therapy started late, and the number is comparably small. In order to summarize and objectively evaluate the research results of integrated traditional Chinese and Western medicine in intervention of cardiovascular diseases, we reviewed the literature of RCTs in this field by searching some Chinese and English databases and put forward some suggestions for the future development and research of traditional Chinese medicine.

SUBMITTER: Guo X

PROVIDER: S-EPMC8769817 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Traditional Chinese medicine (TCM) prescriptions lack standardization due to the complex composition of the prescribed herbs, the unclear mechanism of the formulas, and a lack of scientific data to support the dose-response relationship. Here, we proposed a new clinical strategy of dosage modification for TCM prescriptions to evaluate the clinical efficacy and guide the clinical medication. This study used two TCM prescriptions for the treatment of newly diagnosed type 2 diabetes mellitus (T2DM) to explore the key indications and the most appropriate critical values of dosage modification by analyzing two randomized controlled trials (RCTs). In this study, the indications refer to a change in the indicators from baseline at a certain time point (week 4, week 8, week 12), which could predict the change in outcome indicators, and the critical values refer to the change ranges closely related to the decrease in HbA1c at week 12. In Study 1, the correlation analysis between the change range of indicators at three time points (weeks 4, 8, and 12) from baseline and the decrease in HbA1c at week 12 from baseline (HbA1c 012) was carried out to screen the related indications. Next, we evaluate the related indications and the respective critical values to determine the key indicators, indications, and the most appropriate critical value. We conducted a correlation between the change range of key indicators (obtained from the result of Study 1) at three time points from baseline and HbA1c 012 to screen the key indications in the drug group, high-dose group, and low-dose group in Study 2. Key indications with critical values were determined to investigate the most appropriate critical value in the three groups separately. In Study 1, the key indicator was FBG, the key indication was FBG 04, and the most appropriate critical value was 0.5 mmol/L. In Study 2, the key indication was FBG 04 and the most appropriate critical value was 0.6 mmol/L in the drug group. In the high-dose group, the key indication was FBG 04, and the most appropriate critical value was 0.3 mmol/L. In the low-dose group, the key indication was FBG08, and the most appropriate critical value was 0.1 mmol/L. In addition, we summarized a verification strategy for dosage modification.

Dataset Information

Current Status and Evaluation of Randomized Clinical Trials of Traditional Chinese Medicine in the Treatment of Cardiovascular Diseases.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets