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1000 Titel
  • The optimal approach for retrieving systematic reviews was achieved when searching MEDLINE and Epistemonikos in addition to reference checking: a methodological validation study
1000 Autor/in
  1. Heinen, Lena |
  2. Goossen, Käthe |
  3. Lunny, Carole |
  4. Hirt, Julian |
  5. Puljak, Livia |
  6. Pieper, Dawid |
1000 Verlag
  • BioMed Central
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-11-09
1000 Erschienen in
1000 Quellenangabe
  • 24(1):271
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s12874-024-02384-2 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11549827/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>Systematic reviews (SRs) are used to inform clinical practice guidelines and healthcare decision making by synthesising the results of primary studies. Efficiently retrieving as many relevant SRs as possible is challenging with a minimum number of databases, as there is currently no guidance on how to do this optimally. In a previous study, we determined which individual databases contain the most SRs, and which combination of databases retrieved the most SRs. In this study, we aimed to validate those previous results by using a different, larger, and more recent set of SRs.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>We obtained a set of 100 Overviews of Reviews that included a total of 2276 SRs. SR inclusion was assessed in MEDLINE, Embase, and Epistemonikos. The mean inclusion rates (% of included SRs) and corresponding 95% confidence intervals were calculated for each database individually, as well as for combinations of MEDLINE with each other database and reference checking. Features of SRs not identified by the best database combination were reviewed qualitatively.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>Inclusion rates of SRs were similar in all three databases (mean inclusion rates in % with 95% confidence intervals: 94.3 [93.9–94.8] for MEDLINE, 94.4 [94.0-94.9] for Embase, and 94.4 [93.9–94.9] for Epistemonikos). Adding reference checking to MEDLINE increased the inclusion rate to 95.5 [95.1–96.0]. The best combination of two databases plus reference checking consisted of MEDLINE and Epistemonikos (98.1 [97.7–98.5]). Among the 44/2276 SRs not identified by this combination, 34 were published in journals from China, four were other journal publications, three were health agency reports, two were dissertations, and one was a preprint. When discounting the journal publications from China, the SR inclusion rate in the recommended combination (MEDLINE, Epistemonikos and reference checking) was even higher than in the previous study (99.6 vs. 99.2%).</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>A combination of databases and reference checking was the best approach to searching for biomedical SRs. MEDLINE and Epistemonikos, complemented by checking the references of the included studies, was the most efficient and produced the highest recall. However, our results point to the presence of geographical bias, because some publications in journals from China were not identified.</jats:p> </jats:sec><jats:sec> <jats:title>Study registration</jats:title> <jats:p><jats:ext-link xmlns:xlink='http://www.w3.org/1999/xlink' ext-link-type='doi' xlink:href='10.17605/OSF.IO/R5EAS'>https://doi.org/10.17605/OSF.IO/R5EAS</jats:ext-link> (Open Science Framework).</jats:p> </jats:sec>
1000 Sacherschließung
lokal Databases, Bibliographic/standards [MeSH]
lokal Umbrella review
lokal Databases
lokal Information Storage and Retrieval/standards [MeSH]
lokal MEDLINE [MeSH]
lokal Search strategy
lokal Humans [MeSH]
lokal Review methods
lokal Geographical bias
lokal Information specialist
lokal Information Storage and Retrieval/methods [MeSH]
lokal Research
lokal Overview of review
lokal Systematic reviews
lokal Systematic Reviews as Topic/standards [MeSH]
lokal Evidence synthesis
lokal Systematic Reviews as Topic/methods [MeSH]
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/SGVpbmVuLCBMZW5h|https://orcid.org/0000-0002-1436-1144|https://orcid.org/0000-0002-7825-6765|https://orcid.org/0000-0001-6589-3936|https://orcid.org/0000-0002-8467-6061|https://orcid.org/0000-0002-0715-5182
1000 Hinweis
  • DeepGreen-ID: fb154dc7ec95459ca748d9470a55a8b8 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
1000 Label
1000 Förderer
  1. Private Universität Witten/Herdecke gGmbH |
1000 Fördernummer
  1. -
1000 Förderprogramm
  1. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Private Universität Witten/Herdecke gGmbH |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
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1000 Erstellt am 2025-07-07T04:39:04.637+0200
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1000 Zuletzt bearbeitet 2025-07-30T00:41:42.689+0200
1000 Objekt bearb. Wed Jul 30 00:41:42 CEST 2025
1000 Vgl. frl:6524470
1000 Oai Id
  1. oai:frl.publisso.de:frl:6524470 |
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