Chen Zhe, Luo Jiefeng, Li Siyu, Xu Peipei, Zeng Linan, Yu Qin, Zhang Lingli
Department of Pharmacy, West China Second University Hospital, Sichuan University, Chengdu, People's Republic of China.
Evidence-Based Pharmacy Center, West China Second University Hospital, Sichuan University, Chengdu, People's Republic of China.
Clin Epidemiol. 2022 Aug 4;14:925-935. doi: 10.2147/CLEP.S367339. eCollection 2022.
The systematic review aims to analyze and summarize the characteristics of living systematic review (LSR) for coronavirus disease 2019 (COVID-19).
Six databases including Medline, Excerpta Medica (Embase), Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database and China Science, and Technology Journal Database (VIP), were searched as the source of basic information and methodology of LSR. Descriptive analytical methods were used to analyze the included COVID-19 LSRs, and the study characteristics of COVID-19 LSRs were further assessed.
Sixty-four COVID-19 LSRs were included. Eighty-nine point one percent of LSRs were published on Science Citation Index (SCI) journals, and 64.1% publication with an impact factor (IF) >5 and 17.2% with an IF >15 among SCI journals. The first unit of the published LSRs for COVID-19 came from 19 countries, with the largest contribution from the UK (17.2%, 11/64). Forty point six percent of LSRs for COVID-19 were related to therapeutics topic which was considered the most concerned perspective for LSRs for COVID-19. Seventy-six point six percent of LSRs focused on the general population, with less attention to children, pregnant women and the elderly. However, the LSR for COVID-19 was reported incomplete on "living" process, including 40.6% of studies without search frequency, 79.7% of studies without screening frequency, 20.3% of studies without update frequency, and 65.6% of studies without the timing or criteria of transitioning LSR out of living mode.
Although researchers in many countries have applied LSRs to COVID-19, most of the LSRs for COVID-19 were incomplete in reporting on the "living" process and less focused on special populations. This could reduce the confidence of health-care providers and policy makers in the results of COVID-19 LSR, thereby hindering the translation of evidence on COVID-19 LSR into clinical practice. It was necessary to explicitly enact preferred reporting items for systematic reviews and meta-analyses (PRISMA) to improve the reporting quality of LSR and support ongoing efforts of therapeutics research for special patients with COVID-19.
本系统评价旨在分析和总结2019冠状病毒病（COVID-19）的实时系统评价（LSR）的特点。
检索包括Medline、医学文摘数据库（Embase）、Cochrane图书馆、中国知网（CNKI）、万方数据库和中国科技期刊数据库（维普）在内的6个数据库，作为LSR的基础信息和方法来源。采用描述性分析方法对纳入的COVID-19 LSR进行分析，并进一步评估COVID-19 LSR的研究特征。
纳入64篇COVID-19 LSR。89.1%的LSR发表于科学引文索引（SCI）期刊，其中SCI期刊中影响因子（IF）>5的占64.1%，IF>15的占17.2%。已发表的COVID-19 LSR的第一单位来自19个国家，英国贡献最大（17.2%，11/64）。40.6%的COVID-19 LSR与治疗主题相关，这被认为是COVID-19 LSR最受关注的视角。76.6%的LSR关注普通人群，对儿童、孕妇和老年人的关注较少。然而，COVID-19的LSR在“实时”过程方面报告不完整，包括40.6%的研究没有检索频率，79.7%的研究没有筛选频率，20.3%的研究没有更新频率，65.6%的研究没有将LSR从实时模式转换出来的时间或标准。
尽管许多国家的研究人员已将LSR应用于COVID-19，但大多数COVID-19的LSR在“实时”过程的报告中不完整，且对特殊人群的关注较少。这可能会降低医疗保健提供者和政策制定者对COVID-19 LSR结果的信心，从而阻碍将COVID-19 LSR的证据转化为临床实践。有必要明确制定系统评价和Meta分析的首选报告项目（PRISMA），以提高LSR的报告质量，并支持针对COVID-19特殊患者的治疗研究的持续努力。
