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Record W4407149780

PubMed is Slightly More Sensitive but More Time Intensive to Search than Ovid MEDLINE. A Review of: Katchamart, W., Faulkner, A., Feldman, B., Tomlinson, G., & Bombardier, C. (2011). PubMed had a higher sensitivity than Ovid-MEDLINE in the search for systematic reviews. Journal of Clinical Epidemiology, 64(7), 805-807. doi:10.1016/j.jclinepi.2010.06.004

2011· review· en· W4407149780 on OpenAlexaboutno aff
Cari Merkley

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2011
Typereview
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsMEDLINEMedicineLibrary scienceComputer scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

Objective — To compare the results of searching the MEDLINE database through Ovid and the free online version of PubMed administered by the National Library of Medicine for randomized controlled trials on the subject of the drug methotrexate (MTX) for patients suffering from rheumatoid arthritis. Design — Comparative analysis of search results. Setting — Searches conducted by researchers affiliated with Mahidol University in Bangkok, Thailand, and the University of Toronto and the University Health Network in Toronto, Ontario. Subjects — A total of 3966 search results obtained from Ovid MEDLINE and PubMed. Methods — This study employs an Ovid MEDLINE search strategy originally created for a published systematic review that identified randomized controlled trials on MTX and rheumatoid arthritis (Katchamart, Trudeau, Phumethum, & Bombardier, 2009). Two of the authors of the original systematic review (Katchamart and Bombardier) are among the authors of this current study.Appropriate medical subject heading (MeSH) terms and their synonyms were identified for the three main concepts (rheumatoid arthritis, MTX, and randomized controlled trials). The search was performed in Ovid MEDLINE, seeking articles in any language that met the terms using the Boolean operator OR. The searches for the three concepts were finally combined using AND. The Ovid MEDLINE search was then translated for use in PubMed by an information professional. The formatting and terminology used in some of the original Ovid MEDLINE search statements had to be changed so they would work in the new database environment, but the researchers tried to ensure that the two searches were as similar as possible. The translated search was then executed in PubMed.The final results, as well as the number of articles retrieved for each key search concept (rheumatoid arthritis, MTX, and randomized controlled trials), were then compared. The final results were further analyzed for measures of sensitivity, precision, and number needed to read. Sensitivity is calculated by the number of eligible studies found in a database divided by the “total number of eligible studies in the review” multiplied by 100 (Katchamart, Faulkner, Feldman, Tomlinson, & Bombardier, p. 806). Eligible studies were identified using the inclusion/exclusion criteria developed by Katchamart et al. The figure for “total number of eligible studies in the review” is taken from that same study, which forms the “gold standard” for this analysis (Katchamart et al., p. 806). Precision is calculated by dividing the total number of eligible citations from a database by the total number of citations returned by the database for the search multiplied by 100 (Katchamart et al., p. 806). The number needed to read (NNR) formula used by the authors is 1/precision, taken from a study by Bachman, Coray, Estermann, and Ter Riet (2002). Main Results — The PubMed search found more results than Ovid MEDLINE for each of the three key concepts – rheumatoid arthritis, MTX and randomized controlled trials. Once the three concepts were combined, PubMed found 106 more articles than Ovid MEDLINE (2036 vs. 1930).Once the review eligibility criteria were applied to the search results from PubMed, 18 eligible articles were identified, one more article than in Ovid MEDLINE. The authors indicated that the additional article located in PubMed was from a journal that was not yet indexed by MEDLINE at the time the relevant article was published. To determine database sensitivity, these numbers were then divided by 20, the total number of eligible studies located in the Katachamart et al. 2009 review, which employed tools like EMBASE and strategies like hand searching in addition to MEDLINE in order to identify relevant studies. Because of the additional study it located, the sensitivity of PubMed was determined to be slightly higher than Ovid MEDLINE (90% vs. 85%). There was little difference between the two databases in terms of precision and NNR. Precision for Ovid MEDLINE was calculated at 0.881% and at 0.884% for PubMed. The NNR was 114 for Ovid MEDLINE and 113 for PubMed. Conclusion — The authors state that while PubMed had a higher calculated sensitivity than Ovid MEDLINE in the context of this particular search because it contained content not indexed by Ovid MEDLINE that proved to be relevant for this topic, its precision and NNR were almost equal to MEDLINE’s.Some technical limitations of the PubMed interface were experienced by researchers during the study, such as periodic instability and the inability to save and modify searches and their results line by line. These same issues did not arise while using Ovid MEDLINE.The need for a skilled translation of Ovid MEDLINE searches for use in the PubMed interface was also emphasized by the authors, as differences in syntax and formatting that are not properly addressed could impact PubMed’s sensitivity and precision.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.107
metaresearch head score (Gemma)0.383
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.893
Threshold uncertainty score0.650

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1070.383
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0180.008
Bibliometrics0.0850.082
Science and technology studies0.0020.003
Scholarly communication0.0130.013
Open science0.0060.008
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.1940.044

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.744
GPT teacher head0.687
Teacher spread0.058 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainMethods
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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