Background: Postmenopausal osteoporosis (PMOP) is the focus and difficult problem in the world at present, and we found that Chinese patent medicine(CPM) shown a more miraculous effect. Many kinds of Chinese patent medicine have been proved to be effective in the treatment of this disease, but it is still unclear which kind of Chinese patent medicine has the best effect. Therefore, we propose a network meta-analysis (NMA) protocol to observe the efficacy of various CPM for this disease and provide guidance for clinical practice. Methods: We will use the NMA method to complete this study. First, all the randomized controlled trials of CPM or CPM combined with western medicine in the treatment of PMOP were collected by searching all online Chinese and English databases. The information time limit is from the establishment of the database to August 30, 2020. Then 2 staff members will sift through all the literature and analyze the data using Stata and Winbugs. Results: Through this analysis, we will observe and rank the clinical effects of different CPM for PMOP. The main evaluation indexes include: New fracture, Quality of life, Severe side effects, Death from all causes. Secondary outcome indicators include Bone Mineral density, clinical efficiency, and some laboratory indicators, such as estradiol, serum calcium, serum, etc. Conclusion: This study will rank the therapeutic effects of various proprietary Chinese medicines in the treatment of PMOP, which will be helpful in improving the PMOP treatment regimen. INPLASY registration number: INPLASY202090047.
Background: Sciatica is one of the common clinical diseases. Studies have proved the efficacy of Chinese patent medicine (CPM) in the treatment of sciatica, so far, there has not been a complete systematic review of its effectiveness and safety, and the comparative efficacy and safety of CPM have not been ranked. Therefore, it is necessary to evaluate the efficacy and safety of these CPM by means of systematic review and network meta-analysis (NMA), and to compare them in order. Methods: We will search PubMed, Cochrane Library, EMbase, Web of Science, CNKI, Wanfang, VIP, CBM and other databases for RCTs of CPM in the treatment of sciatica, (database established until December 30, 2020). In addition, we will manually search the “Pharmaceutical Information”, “National Essential Drug List”, “Chinese Pharmacopoeia”, etc. to inquire about drug instructions, and screen the market circulation and clinically commonly used CPM. We will use RevMan software, gemtc package, GeMTC software for statistical analysis, and draw the surface under cumulative ranking area (SUCRA) to predict the order of curative effect of treatment measures. Results: Our study will compare and evaluate the effectiveness of CPM in the treatment of sciatica, and rank different CPM. The outcome indicators will include clinical efficacy, pain degree, lumbar spine function and adverse events. Conclusion: Our research will provide support for clinical practice. INPLASY registration number: INPLASY2020110073.
Background: In recent years, the incidence of insomnia is increasing. However, the existing therapy methods for cannot fundamentally treat the disease. Meanwhile, Chinese patent medicine (CPM) plays an active role in the treatment of insomnia. However, there is no comparison and ranking of the efficacy of every CPM. Therefore, our study will use network meta-analysis to compare the efficacy of different CPM on insomnia, in order to provide evidence-based medical evidence for clinical treatment. Methods: We will search CNKI, Wanfang, VIP, CBM, Pubmed, Cochrane Library, Embase for the randomized controlled trials of CPM in the treatment of insomnia (up to December 31, 2020). We will use RevMan5.3, Stata15.1 and ADDIS software for statistical analysis. We will draw the surface under cumulative ranking area to predict the order of efficacy. Results: We aim to rank the efficacy and safety of different CPM for the treatment of insomnia. Conclusion: CPM plays a positive role in the treatment of insomnia and can provide evidence support for clinicians and patients INPLASY registration number: INPLASY2020120121
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