Evidence map›Paper›PMID 35337283›Full record

ArticleBMC medical research methodology2022

Development and validation of search filters to identify articles on deprescribing in Medline and Embase.

Thomas Morel, Jérôme Nguyen-Soenen, Wade Thompson, Jean-Pascal Fournier

Open access · goldAbstract read
In one paragraph

Article in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 4 pooled it
2.5field-weighted citation impact, top 12% of its field
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

8 citing papers in PubMed, 4 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Withdrawal of antihypertensive drugs in older people.The Cochrane database of systematic reviews · 2025
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
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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 at 3 institutions in 3 countries.

Thomas MorelDépartement de Médecine Générale, Faculté de Médecine, Nantes Université, Nantes, France.ORCID 0000-0003-2141-1442
Jérôme Nguyen-SoenenDépartement de Médecine Générale, Faculté de Médecine, Nantes Université, Nantes, France.ORCID 0000-0002-6023-8892
Wade ThompsonWomen's College Hospital Research Institute, Toronto, ON, Canada.ORCID 0000-0002-8268-4092
Jean-Pascal FournierDépartement de Médecine Générale, Faculté de Médecine, Nantes Université, Nantes, France. jean-pascal.fournier@univ-nantes.fr.ORCID 0000-0002-9971-0672
Université de Tours · FRNantes Université · FRUniversity of Southern Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDeprescribing literature has been increasing rapidly. Our aim was to develop and validate search filters to identify articles on deprescribing in Medline via PubMed and in Embase via Embase.com .

methodsArticles published from 2011 to 2020 in a core set of eight journals (covering fields of interest for deprescribing, such as geriatrics, pharmacology and primary care) formed a reference set. Each article was screened independently in duplicate and classified as relevant or non-relevant to deprescribing. Relevant terms were identified by term frequency analysis in a 70% subset of the reference set. Selected title and abstract terms, MeSH terms and Emtree terms were combined to develop two highly sensitive filters for Medline via Pubmed and Embase via Embase.com . The filters were validated against the remaining 30% of the reference set. Sensitivity, specificity and precision were calculated with their 95% confidence intervals (95% CI).

resultsA total of 23,741 articles were aggregated in the reference set, and 224 were classified as relevant to deprescribing. A total of 34 terms and 4 MeSH terms were identified to develop the Medline search filter. A total of 27 terms and 6 Emtree terms were identified to develop the Embase search filter. The sensitivity was 92% (95% CI: 83-97%) in Medline via Pubmed and 91% (95% CI: 82-96%) in Embase via Embase.com .

conclusionsThese are the first deprescribing search filters that have been developed objectively and validated. These filters can be used in search strategies for future deprescribing reviews. Further prospective studies are needed to assess their effectiveness and efficiency when used in systematic reviews.

Indexed as

DeprescriptionsHumansMedical Subject HeadingsMEDLINEPubMedSystematic Reviews as TopicDeprescriptionsMedical subject headingsMethodsSensitivitySystematic review

Identifiers

PMID35337283
PMCPMC8953136
OpenAlexW4221049767

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.