1. Strategies to optimize MEDLINE and EMBASE search strategies for anesthesiology systematic reviews. An experimental study.
- Author
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Volpato ESN, Betini M, Puga ME, Agarwal A, Cataneo AJM, Oliveira LD, Bazan R, Braz LG, Pereira JEG, and El Dib R
- Subjects
- Humans, MEDLINE, Anesthesiology, Information Storage and Retrieval methods, Review Literature as Topic, Search Engine methods, Subject Headings
- Abstract
Background: A high-quality electronic search is essential for ensuring accuracy and comprehensiveness among the records retrieved when conducting systematic reviews. Therefore, we aimed to identify the most efficient method for searching in both MEDLINE (through PubMed) and EMBASE, covering search terms with variant spellings, direct and indirect orders, and associations with MeSH and EMTREE terms (or lack thereof)., Design and Setting: Experimental study. UNESP, Brazil., Methods: We selected and analyzed 37 search strategies that had specifically been developed for the field of anesthesiology. These search strategies were adapted in order to cover all potentially relevant search terms, with regard to variant spellings and direct and indirect orders, in the most efficient manner., Results: When the strategies included variant spellings and direct and indirect orders, these adapted versions of the search strategies selected retrieved the same number of search results in MEDLINE (mean of 61.3%) and a higher number in EMBASE (mean of 63.9%) in the sample analyzed. The numbers of results retrieved through the searches analyzed here were not identical with and without associated use of MeSH and EMTREE terms. However, association of these terms from both controlled vocabularies retrieved a larger number of records than did the use of either one of them., Conclusions: In view of these results, we recommend that the search terms used should include both preferred and non-preferred terms (i.e. variant spellings and direct/indirect order of the same term) and associated MeSH and EMTREE terms, in order to develop highly-sensitive search strategies for systematic reviews.
- Published
- 2018
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