This paper introduces the process of design and implementation on the clinical evidence database of acupuncture (ACU-CED), including establishing expert groups on the basis of demands to formulate top-design, project implementation plans and standard, comprehensively searching publications of clinical randomized controlled trials (RCTs) of acupuncture and moxibustion, conducting strictly data extraction and evaluation, and eventually achieve automatic utilization of clinical evidence. ACU-CED will become the first structural data platform with the function of searching-screening-result, analysis-data, and statistics-evidence extraction, which fills in gapes in database of clinical evidence sources, increases efficiency of evidence transformation, and reduces waste of resources. It will also achieve auto-completion of systematic review/meta-analysis as well as visualization of clinical evidence, so as to provide evidence for clinical decision, guidelines and disease spectrum of acupuncture therapy.
The complete, transparent, and standardized reporting of the outcome of a clinical trial is a key factor in ensuring the practicality, reproducibility, and transparency of the trial, and reducing bias in selective reporting. The Consolidated Standards of Reporting Trials (CONSORT) 2010 statement provides normative guidelines for the reporting of clinical trials. In December 2022, JAMA released the Guidelines for Reporting Outcomes in Trial Reports (CONSORT-Outcomes) 2022 Extension, aiming to explain the entries related to trial outcomes, sample size, statistical methods, and auxiliary analysis in the CONSORT 2010 statement, to further improve the standards for outcome reporting in clinical trial reports. This article combines research examples to interpret the CONSORT-Outcomes 2022 Extension, in order to provide normative references for domestic scholars to report clinical research results.
To describe the construction and application of clinical evidence database of traditional Chinese medicine (TCM-CED) so as to provide evidence for TCM research. The construction process primarily includes: expert team building, TCM-CED function module design, evidence collection and quality control. The applications of TCM-CED primarily include the following aspects: automatic generation of systematic review/meta-analysis in TCM, automatic generation of evidence reports on dominant diseases of TCM, automatic generation of evidence index of Chinese patent medicine, optimizing the selection of outcomes in TCM research, tracking methodological and reporting quality of TCM research, and promoting international dissemination of TCM evidence. With the rapid development of information technology and artificial intelligence, TCM-CED will be combined with artificial intelligence to achieve the construction of all-dimensional TCM evidence chain and the automation of the whole process.
To promote the accessibility and application of guidelines, it is necessary to establish a professional guideline database to adapt to the rapid growth of TCM clinical practice guidelines. This study described the framework design, technology module, information management, and quality control of the clinical practice guideline database of traditional Chinese medicine (G-TCM). G-TCM had included 658 TCM clinical practice guidelines, which would provide a platform for clinicians, researchers, guideline makers (revision), and evaluators to quickly query and obtain clinical guideline information, and play a supporting role in promoting the standardization and accessibility of TCM clinical practice guidelines and better guiding clinical practice.