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Identifying diagnostic accuracy studies in EMBASE.

Authors: Bachmann, Lucas M.; Estermann, Pius; Kronenberg, Corinna; ter Riet, Gerben;

Identifying diagnostic accuracy studies in EMBASE.

Abstract

The objective was to develop and test search strategies to identify diagnostic articles recorded on EMBASE.Four general medical journals were hand searched for diagnostic accuracy studies published in 1999. Identified studies served as a gold standard. Candidate terms for search strategies were identified using a word-frequency analysis of their abstracts. According to the frequency of identified terms, searches were run for each term independently. Sensitivity, precision, and number needed to read (NNR) (1/precision) of every candidate term were calculated. Terms with the highest "sensitivity*precision" product were used as free-text terms and combined into a final strategy using the Boolean operator "OR."The most frequently occurring eight terms (sensitiv* or detect* or accura* or specific* or reliab* or positive or negative or diagnos*) produced a sensitivity of 100% (95% confidence interval [CI] 94.1 to 100%) and an NNR of 27 (95% CI 21.0 to 34.8). The combination of the two truncated terms sensitiv* or detect* gave a sensitivity of 73.8% (95% CI 60.9 to 84.2%) and an NNR of 5.7 (95% CI 4.4 to 7.6).The identified search terms offer the choice of either reasonably sensitive or precise search strategies for the detection of diagnostic accuracy studies in EMBASE. The terms are useful both for busy health care professionals who value precision and for reviewers who value sensitivity.

Country
Netherlands
Related Organizations
Keywords

Diagnosis, Humans, Information Storage and Retrieval, Diagnostic Errors, Periodicals as Topic, Databases, Bibliographic, Sensitivity and Specificity

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    popularity
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    Average
    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Average
Top 10%
Top 10%
gold