Maternal folic acid supplementation to prevent preeclampsia: a systematic review and meta-analysis.

OBJECTIVE: The purpose of this systematic review was to examine the association between folic acid supplementation during pregnancy and the risk of preeclampsia. METHODS: Relevant studies were included by searching Embase, PubMed, Scope, Web of science, Cochrane Library databases. Studies were reviewed according to prespecified inclusion and exclusion criteria. Study characteristics were summarized, and study quality was assessed. Risk ratios (RR) and 95% confidence intervals (CI) were used as indicators of effect to assess the relationship between folic acid supplementation and risk of preeclampsia. RESULTS: The protocol of this study was prospectively registered with the PROSPERO (registration No. CRD42022380636). A total of nine studies were included, divided into three groups according to the type of study, containing a total of 107 051 and 105 222 women who were supplemented and not supplemented with folic acid during pregnancy. The results showed that folic acid supplementation during pregnancy could not be proven to reduce the risk of preeclampsia. CONCLUSION: The results of the study suggest that folic acid supplementation alone is not associated with a decreased risk of pre-eclampsia,but the inferences are somewhat limited by the low methodological quality of the included literature, and therefore higher quality studies are needed to prove this point.

Effects of Tai chi in knee osteoarthritis patients: An overview of systematic reviews and meta-analyses.

OBJECTIVE: Tai Chi (TC) is a complementary therapy for knee osteoarthritis (KOA). Although systematic reviews (SRs) and meta-analyses (Mas) of efficacy studies have been published, the results remain uncertain, and their quality has not yet been fully evaluated. Here, we summarize the existing SRs/Mas, evaluate their quality and level of evidence, and provide a reference for the effectiveness of TC. METHODS: SRs/Mas of TC therapy for KOA published before February 2023 were retrieved from eight databases in Chinese and English. The Assessing the Methodological Quality of Systematic Reviews 2 (AMSTAR-2), the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020, and the Risk of Bias in Systematic (ROBIS) scale were used to assess methodological quality, reporting quality, and risk of bias. RESULTS: Seven SRs/Mas were finally included. One was deemed high quality by AMASTAR-2, while the rest were of critically low quality. In the PRISMA2020 assessment, the response rate of "Yes" for Q7, Q15, Q22, Q24, and Q27 was less than 50%. In the ROBIS assessment, three reports in Phase 3 were high risk and four were low risk. In the efficacy assessment, TC has shown varying degrees of improvement in physical function, pain, stiffness, 6-minute walk test, mental quality of life, TUG, and balance in patients with KOA. CONCLUSION: TC effectively treats KOA-associated pain, stiffness, body function, and mental quality of life. However, the low methodological quality of the studies and the high risk of migration reduced their reliability. Therefore, these conclusions should be taken with caution. High-quality, large-sample research is needed to provide stronger and more scientific evidence.

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.