Skip to content
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
A search filter to identify pragmatic trials in MEDLINE was highly specific but lacked sensitivity
Journal of Clinical Epidemiology, Volume 124, Year 2020
Notification
URL copied to clipboard!
Description
Objectives: Identifying pragmatic trials from among all randomized trials is challenging because of inconsistent reporting. Our objective was to develop and validate a search filter to identify reports of pragmatic trials from Ovid MEDLINE. Study Design and Setting: Two sets of known and probable pragmatic trial records were analyzed using text mining to generate candidate terms. Two large population sets comprising clinical trials and explanatory trials were used to select discriminating terms. Various combinations of terms were tested iteratively to achieve optimal search performance. Two externally derived sets were used to validate sensitivity and specificity of the derived filters. Results: Our validated sensitivity-maximizing filter (combines trial design terms with terms relating to attributes of pragmatic trials) retrieves over 42,000 records in MEDLINE and has sensitivity of 46.4% (95% confidence interval (CI) 37.2 to 55.7%) and estimated specificity of 98.1% (95% CI 93.4 to 99.8%). Search performance is superior to other ad hoc filters for pragmatic trials. The Cochrane search for randomized trials has much better sensitivity (98.2%), but poorer specificity (1.9%) and retrieves 4.5 million records. Conclusion: A highly specific filter (low false positive rate) with moderate sensitivity is available for identifying reports of trials more likely to be pragmatic. © 2020 Elsevier Inc.
Authors & Co-Authors
Taljaard, Monica K.
Canada, Ottawa
L'hôpital D'ottawa
Canada, Ottawa
University of Ottawa
McDonald, Steve J.
Australia, Clayton
Monash University
Nicholls, Stuart G.
Canada, Ottawa
L'hôpital D'ottawa
Grimshaw, Jeremy M.
Canada, Ottawa
L'hôpital D'ottawa
Canada, Ottawa
University of Ottawa
Fergusson, Dean A.
Canada, Ottawa
L'hôpital D'ottawa
Canada, Ottawa
University of Ottawa
Zwarenstein, Merrick F.
Canada, London
Western University
McKenzie, Joanne E.
Australia, Clayton
Monash University
Statistics
Citations: 16
Authors: 7
Affiliations: 6
Identifiers
Doi:
10.1016/j.jclinepi.2020.05.003
ISSN:
08954356
Research Areas
Environmental
Study Design
Cross Sectional Study