Evidence map›Paper›PMID 15784134›Full record

ArticleBMC medical informatics and decision making2005

Developing optimal search strategies for detecting clinically sound and relevant causation studies in EMBASE.

R Brian Haynes, Monika Kastner, Nancy L Wilczynski, Hedges Team

Abstract readComparative Study
In one paragraph

Article in BMC medical informatics and decision making, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Search strategies to identify observational studies in MEDLINE and Embase.The Cochrane database of systematic reviews · 2019
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Search strategies to identify information on adverse effects: a systematic review.Journal of the Medical Library Association : JMLA · 2009
    Pooled it
  6. Trial
  7. Article
  8. Review
  9. Review
  10. Literature search strategies in dental education and research.Journal of Taibah University Medical Sciences · 2021
    Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Search filter precision can be improved by NOTing out irrelevant content.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2011
    Article
  17. Article
  18. Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

R Brian HaynesHealth Information Research Unit, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, L8N 3Z5, Canada. bhaynes@mcmaster.ca
Monika Kastner
Nancy L Wilczynski
Hedges Team

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEvaluating the existence and strength of an association between a putative cause and adverse clinical outcome is complex and best done by assessing all available evidence. With the increasing burden of chronic disease, greater time demands on health professionals, and the explosion of information, effective retrieval of best evidence has become both more important and more difficult. Optimal search retrieval can be hampered by a number of obstacles, especially poor search strategies, but using empirically tested methodological search filters can enhance the accuracy of searches for sound evidence concerning etiology. Although such filters have previously been developed for studies of relevance to causation in MEDLINE, no empirically tested search strategy exists for EMBASE.

methodsAn analytic survey was conducted, comparing hand searches of journals with retrievals from EMBASE for candidate search terms and combinations. 6 research assistants read all issues of 55 journals indexed in EMBASE. All articles were rated using purpose and quality indicators and categorized into clinically relevant original studies, review articles, general papers, or case reports. The original and review articles were then categorized as 'pass' or 'fail' for scientific merit according to explicit criteria in the areas of causation (etiology) and other clinical topics. Candidate search strategies were developed for causation, then run in a subset of 55 EMBASE journals, the retrievals being compared with the hand search data. The sensitivity, specificity, precision, and accuracy of the search strategies were calculated.

resultsOf the 1489 studies classified as causation, 14% were methodologically sound. When search terms were combined, sensitivity reached 92%. Compared with the best single-term strategy, the best combination of terms resulted in an absolute increase in sensitivity (19%) and specificity (5.2%). Maximizing specificity for combined terms resulted in an increase of 7.1% compared with the single term but this came at an expense of sensitivity (39% absolute decrease). A search strategy that optimized the trade-off between sensitivity and specificity achieved 81.9% for sensitivity and 81.4% for specificity.

conclusionWe have discovered search strategies that retrieve high quality studies of causation from EMBASE with high sensitivity, high specificity, or an optimal balance of each.

Indexed as

CausalityDatabases, BibliographicEmpirical ResearchEvidence-Based MedicineHumansInformation Storage and RetrievalPeriodicals as TopicQuality ControlResearch DesignSensitivity and SpecificitySubject HeadingsUser-Computer Interface

Identifiers

PMID15784134
PMCPMC1087487

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.