COVID-19 L·OVE REPOSITORY IS HIGHLY COMPREHENSIVE AND CAN BE USED AS A SINGLE SOURCE FOR COVID-19 STUDIES
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Abstract
Objective
COVID-19 Living OVerview of Evidence (COVID-19 L·OVE) is a public repository and classification platform for COVID-19 articles. The repository contains over 430,000 articles as of 20 September 2021 and intends to provide a one-stop shop for COVID-19 evidence. Considering that systematic reviews conduct high-quality searches, this study assesses the comprehensiveness and currency of the repository against the total number of studies in a representative sample of COVID-19 systematic reviews.
Methods
Our sample was generated from all the studies included in the systematic reviews of COVID-19 published during April 2021. We estimated the comprehensiveness of COVID-19 L·OVE repository by determining how many of the individual studies in the sample were included in the COVID-19 L·OVE repository. We estimated the currency as the percentage of studies that were available in the COVID-19 L·OVE repository at the time the systematic reviews conducted their own search.
Results
We identified 83 eligible systematic reviews that included 2132 studies. COVID-19 L·OVE had an overall comprehensiveness of 99.67% (2125/2132). The overall currency of the repository, that is, the proportion of articles that would have been obtained if the search of the reviews was conducted in COVID-19 L·OVE instead of searching the original sources, was 96.48% (2057/2132). Both the comprehensiveness and the currency were 100% for randomised trials (82/82).
Conclusion
The COVID-19 L·OVE repository is highly comprehensive and current. Using this repository instead of traditional manual searches in multiple databases can save a great amount of work to people conducting systematic reviews and would improve the comprehensiveness and timeliness of evidence syntheses. This tool is particularly important for supporting living evidence synthesis processes
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SciScore for 10.1101/2021.09.21.21263849: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization As randomised trials are particularly relevant for decision-making, we also run a regular search for randomised trials on Twitter using the terms #COVID19 OR #COVID-19 OR #COVID_19 OR #COVID randomized OR randomised, and scan relevant scientific conferences, press release websites and the websites of the main trials or companies relevant to COVID-19. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources The sources include PubMed, EMBASE, CINAHL (the Cumulative Index to Nursing and Allied Health Literature), PsycINFO, LILACS (Latin American & Caribbean Health Sciences … SciScore for 10.1101/2021.09.21.21263849: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization As randomised trials are particularly relevant for decision-making, we also run a regular search for randomised trials on Twitter using the terms #COVID19 OR #COVID-19 OR #COVID_19 OR #COVID randomized OR randomised, and scan relevant scientific conferences, press release websites and the websites of the main trials or companies relevant to COVID-19. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources The sources include PubMed, EMBASE, CINAHL (the Cumulative Index to Nursing and Allied Health Literature), PsycINFO, LILACS (Latin American & Caribbean Health Sciences Literature), Wanfang Database, CBM (Chinese Biomedical Literature Database), CNKI (Chinese National Knowledge Infrastructure), VIP (Chinese Scientific Journal Database), IRIS (WHO Institutional Repository for Information Sharing), IRIS PAHO (PAHO Institutional Repository for Information Sharing), IBECS (Spanish Bibliographic Index on Health Sciences), Microsoft Academic, ICTRP Search Portal, Clinicaltrials.gov, ISRCTN registry, Chinese Clinical Trial Registry, IRCT (Iranian Registry of Clinical Trials), EU Clinical Trials Register, Japan NIPH Clinical Trials Search, JPRN (Japan Primary Registries Network - includes JapicCTI, JMACCT CTR, jRCT, UMIN CTR), CRiS (Clinical Research Information Service), ANZCTR (Australian New Zealand Clinical Trials Registry), ReBec (Brazilian Clinical Trials Registry), CTRI (Clinical Trials Registry - India), RPCEC (Cuban Public Registry of Clinical Trials), DRKS (German Clinical Trials Register), LBCTR (Lebanese Clinical Trials Registry), TCTR (Thai Clinical Trials Registry), NTR (The Netherlands National Trial Register), PACTR (Pan African Clinical Trial Registry), REPEC (Peruvian Clinical Trial Registry), SLCTR (Sri Lanka Clinical Trials Registry), MedRxiv, BioRxiv, SSRN Preprints, Research Square, ChinaXiv and SciELO Preprints. PubMedsuggested: (PubMed, RRID:SCR_004846)EMBASEsuggested: (EMBASE, RRID:SCR_001650)PsycINFOsuggested: (PsycINFO, RRID:SCR_014799)BioRxivsuggested: (bioRxiv, RRID:SCR_003933)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:One limitation of our study is that a sample obtained by the relative recall method might not be representative of the total number of existing studies [11]. Considering the high level of standardisation of systematic reviews it is possible they all cover much the same territory. An evaluation against a sample derived from a manual review of journals and other sources might provide a more reliable estimate [19]. However, this approach may not be suitable in the context of the deluge of scientific information about COVID-19. Another limitation of our evaluation is the scope of the assessment. We addressed only primary studies and not the other types of scientific articles that are contained in the COVID-19 L·OVE repository, which includes any type of scientific article. Considering the inclusive nature of the methods used to maintain the COVID-19 L·OVE repository, we can expect similar results for the other types of articles, but a formal evaluation would provide a definitive answer. Our study is not designed to assess the specificity of the repository nor any of the components of the COVID-19 classification platform. We believe the latter has enormous potential to increase the reliability of search processes and to reduce the amount of work involved. However, it is yet to be tested. Implications: Accessing all the available studies for a particular topic is key to avoiding being misled by research [20]. Unfortunately, substantial time and resources are needed to comprehensive...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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