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P.002 Improving the quality of systematic reviews of neurological conditions with more accurate search strategies: a series of validation studies

Published online by Cambridge University Press:  02 June 2017

KA Bui
Affiliation:
(Montréal)
J Abdaem
Affiliation:
(Montreal)
GC Gore
Affiliation:
(Montreal)
MR Keezer
Affiliation:
(Montréal)
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Abstract

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Background: A well-constructed search strategy is an important feature of any systematic review. We aimed to design and validate electronic database (e.g. Pubmed) search strategies (i.e. a hedge or series of words used to identify articles of interest) for six neurological conditions. Methods: We enumerated 10311 consecutive articles in the 21 highest impact factor English-language general neurology journals. We constructed a simple hedge, limited to one keyword, for each condition. We also constructed a complex hedge using a series of MeSH terms and keywords. Two reviewers independently reviewed (confirmed by a third reviewer) all articles and established which condition(s) were the article’s subject. We calculated sensitivity/specificity estimates for the simple and complex hedges, and compared these using McNemar’s test. Results: The results are summarized in the Table. Conclusions: Our complex hedges for most conditions dramatically improve sensitivity without compromising specificity. This study will help improve the accuracy of search strategies in future systematic reviews.

Type
Poster Presentations
Copyright
Copyright © The Canadian Journal of Neurological Sciences Inc. 2017