ArticleHealth information and libraries journal2019
The development of search filters for adverse effects of medical devices in medline and embase.
Article in Health information and libraries journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed, 9 citations in OpenAlex.
- Searching for the social determinants of health: observations from evidence synthesis publications.Systematic reviews · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundObjectively derived search filters for adverse drug effects and complications in surgery have been developed but not for medical device adverse effects.
objectiveTo develop and validate search filters to retrieve evidence on medical device adverse effects from ovid medline and embase.
methodsWe identified systematic reviews from Epistemonikos and the Health Technology Assessment (hta) database. Included studies within these reviews that reported on medical device adverse effects were randomly divided into three test sets and one validation set of records. Using word frequency analysis from one test set, we constructed a sensitivity maximising search strategy. This strategy was refined using two other test sets, then validated.
resultsFrom 186 systematic reviews which met our inclusion criteria, 1984 unique included studies were available from medline and 1986 from embase. Generic adverse effects searches in medline and embase achieved 84% and 83% sensitivity. Recall was improved to over 90%, however, when specific adverse effects terms were added.
conclusionWe have derived and validated novel search filters that retrieve over 80% of records with medical device adverse effects data in medline and embase. The addition of specific adverse effects terms is required to achieve higher levels of sensitivity.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.