2019年冠状病毒病(COVID-19)
透明度(行为)
完备性(序理论)
系统回顾
2019-20冠状病毒爆发
医学
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)
梅德林
数据科学
计算机科学
疾病
病毒学
政治学
传染病(医学专业)
数学
病理
爆发
数学分析
计算机安全
法学
作者
Persefoni Talimtzi,Antonios Ntolkeras,Georgios Kostopoulos,Konstantinos I. Bougioukas,Eirini Pagkalidou,Andreas Ouranidis,Athanasia Pataka,Anna‐Bettina Haidich
标识
DOI:10.1016/j.jclinepi.2024.111264
摘要
Abstract
Objectives
To conduct a methodological overview of reviews to evaluate the reporting completeness and transparency of systematic reviews (SRs) of prognostic prediction models (PPMs) for COVID-19. Study Design and Setting
MEDLINE, Scopus, Cochrane Database of Systematic Reviews, and Epistemonikos (epistemonikos.org) were searched for SRs of PPMs for COVID-19 until December 31, 2022. The risk of bias in systematic reviews tool was used to assess the risk of bias. The protocol for this overview was uploaded in the Open Science Framework (https://osf.io/7y94c). Results
Ten SRs were retrieved; none of them synthesized the results in a meta-analysis. For most of the studies, there was absence of a predefined protocol and missing information on study selection, data collection process, and reporting of primary studies and models included, while only one SR had its data publicly available. In addition, for the majority of the SRs, the overall risk of bias was judged as being high. The overall corrected covered area was 6.3% showing a small amount of overlapping among the SRs. Conclusion
The reporting completeness and transparency of SRs of PPMs for COVID-19 was poor. Guidance is urgently required, with increased awareness and education of minimum reporting standards and quality criteria. Specific focus is needed in predefined protocol, information on study selection and data collection process, and in the reporting of findings to improve the quality of SRs of PPMs for COVID-19.
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