Traditional Chinese Medicine (TCM) standardization is an important carrier for TCM inheriting and innovating. As an important content of TCM standardization system, TCM clinical practice guidelines' designation and revision play an important role for medical staff to regulate medical behavior, and improve the quality of health services. This paper expounds the significance and function of the TCM guidelines, analyzes the present situation, opportunities and challenges, and puts forward the strategies and suggestions to promote the development of evidence-based TCM guidelines.
Through summarizing the definition, concept, and development of patient registry, and also retrieving ClinicalTrials.gov, we introduce its application areas, application range, disease, research number. Based on the application situation, we present the challenges faced now and future development of direction.
Accurately assessing the risk of bias is a critical challenge in network meta-analysis (NMA). By integrating direct and indirect evidence, NMA enables the comparison of multiple interventions, but its outcomes are often influenced by bias risks, particularly the propagation of bias within complex evidence networks. This paper systematically reviews commonly used bias risk assessment tools in NMA, highlighting their applications, limitations, and challenges across interventional trials, observational studies, diagnostic tests, and animal experiments. Addressing the issues of tool misapplication, mixed usage, and the lack of comprehensive tools for overall bias assessment in NMA, we propose strategies such as simplifying tool operation, enhancing usability, and standardizing evaluation processes. Furthermore, advancements in artificial intelligence (AI) and large language models (LLMs) offer promising opportunities to streamline bias risk assessments and reduce human interference. The development of specialized tools and the integration of intelligent technologies will enhance the rigor and reliability of NMA studies, providing robust evidence to support medical research and clinical decision-making.