Literature DB >> 21775104

Sensitive Clinical Queries retrieved relevant systematic reviews as well as primary studies: an analytic survey.

Nancy L Wilczynski1, K Ann McKibbon, R Brian Haynes.   

Abstract

OBJECTIVE: To determine how well the previously validated broad and narrow Clinical Queries for treatment, diagnosis, prognosis, and etiology studies, retrieve not only primary studies but also relevant systematic reviews. STUDY DESIGN AND
SETTING: Using the Clinical Hedges Database housed at McMaster University, we tested the retrieval performance of the Clinical Queries.
RESULTS: For most purpose categories (therapy, diagnosis, prognosis, and etiology) and most databases (MEDLINE, EMBASE, CINAHL, and PsycINFO), the sensitive (broad) Clinical Queries search terms had sensitivities higher than 90% for retrieving relevant systematic reviews as well as primary studies. When testing specific (narrow) Clinical Queries, in 8 of 12 cases, specificity was 94% or higher, but sensitivity dropped below 50%. For all purpose categories and all databases, performance was improved when combining the sensitive or specific Clinical Queries with our existing sensitive or specific systematic review search filter using the Boolean OR; sensitivities ranged from 90.7% to 99.7% and specificities ranged from 92.4% to 98.0% with sensitivities higher than 50%.
CONCLUSION: The sensitive Clinical Queries for therapy, diagnosis, prognosis, and etiology perform well in retrieving not only primary studies but also systematic reviews. Search performance can be improved by combining the Clinical Queries with our sensitive or specific systematic review filter.
Copyright © 2011 Elsevier Inc. All rights reserved.

Mesh:

Year:  2011        PMID: 21775104     DOI: 10.1016/j.jclinepi.2011.04.007

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  6 in total

1.  Optimizing a literature surveillance strategy to retrieve sound overall prognosis and risk assessment model papers.

Authors:  Patricia L Kavanagh; Francine Frater; Tamara Navarro; Peter LaVita; Rick Parrish; Alfonso Iorio
Journal:  J Am Med Inform Assoc       Date:  2021-03-18       Impact factor: 4.497

2.  Reporting, handling and assessing the risk of bias associated with missing participant data in systematic reviews: a methodological survey.

Authors:  Elie A Akl; Alonso Carrasco-Labra; Romina Brignardello-Petersen; Ignacio Neumann; Bradley C Johnston; Xin Sun; Matthias Briel; Jason W Busse; Shanil Ebrahim; Carlos E Granados; Alfonso Iorio; Affan Irfan; Laura Martínez García; Reem A Mustafa; Anggie Ramírez-Morera; Anna Selva; Ivan Solà; Andrea Juliana Sanabria; Kari A O Tikkinen; Per O Vandvik; Robin W M Vernooij; Oscar E Zazueta; Qi Zhou; Gordon H Guyatt; Pablo Alonso-Coello
Journal:  BMJ Open       Date:  2015-09-30       Impact factor: 2.692

Review 3.  Concordance between decision analysis and matching systematic review of randomized controlled trials in assessment of treatment comparisons: a systematic review.

Authors:  Rahul S Mhaskar; Hesborn Wao; Helen Mahony; Ambuj Kumar; Benjamin Djulbegovic
Journal:  BMC Med Inform Decis Mak       Date:  2014-07-15       Impact factor: 2.796

4.  Systematic review automation technologies.

Authors:  Guy Tsafnat; Paul Glasziou; Miew Keen Choong; Adam Dunn; Filippo Galgani; Enrico Coiera
Journal:  Syst Rev       Date:  2014-07-09

Review 5.  Toward a comprehensive evidence map of overview of systematic review methods: paper 1-purpose, eligibility, search and data extraction.

Authors:  Carole Lunny; Sue E Brennan; Steve McDonald; Joanne E McKenzie
Journal:  Syst Rev       Date:  2017-11-21

6.  Automated screening of research studies for systematic reviews using study characteristics.

Authors:  Guy Tsafnat; Paul Glasziou; George Karystianis; Enrico Coiera
Journal:  Syst Rev       Date:  2018-04-25
  6 in total

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