Evidence map›Paper›PMID 29976134›Full record

ArticleBMC medical research methodology2018

Development and validation of a MEDLINE search filter/hedge for degenerative cervical myelopathy.

Benjamin M Davies, Samuel Goh, Keonwoo Yi, Isla Kuhn, Mark R N Kotter

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical research methodology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 4 pooled it
2.6field-weighted citation impact, top 11% 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

23 citing papers in PubMed, 4 syntheses or guidelines pooled it, 36 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Benjamin M DaviesDepartment of Academic Neurosurgery, Cambrige University Hospital, University of Cambridge, Cambridge, UK. Benjamin.davies4@nhs.net.ORCID 0000-0003-0591-5069
Samuel GohUniversity of Cambridge Medical School, University of Cambridge, Cambridge, UK.
Keonwoo YiUniversity of Cambridge Medical School, University of Cambridge, Cambridge, UK.
Isla KuhnUniversity of Cambridge Medical Library, University of Cambridge, Cambridge, UK.
Mark R N KotterDepartment of Academic Neurosurgery, Cambrige University Hospital, University of Cambridge, Cambridge, UK.
University of Cambridge · GB

Funding

Department of Health CS-2015-15-023
6 · The paper itself

Abstract

backgroundDegenerative cervical myelopathy (DCM) is a common condition with many unmet clinical needs. Pooled analysis of studies is an important tool for advancing medical understanding. This process starts with a systematic search of the literature. Identification of studies in DCM is challenged by a number of factors, including non-specific terminology and index terms. Search filters or HEDGEs, are search strings developed and validated to optimise medical literature searches. We aimed to develop a search filter for DCM for the MEDLINE database.

methodsThe diagnostic test assessment framework of a "development dataset" and seperate "validation dataset" was used. The development dataset was formed by hand searching four leading spinal journals (Spine, Journal of Neurosurgery Spine, Spinal Cord and Journal of Spinal Disorders and Techniques) in 2005 and 2010. The search filter was initially developed focusing on sensitivity and subsequently refined using NOT functions to improve specificity. One validation dataset was formed from DCM narrative and systematic review articles and the second, articles published in April of 1989, 1993, 1997, 2001, 2005, 2009, 2013 and 2017 retrieved via the search MeSH term 'Spine'. Metrics of sensitivity, specificity, precision and accuracy were used to test performance.

resultsHand searching identified 77/1094 relevant articles for 2005 and 55/1199 for 2010. We developed a search hedge with 100% sensitivity and a precision of 30 and 29% for the 2005 and 2010 development datasets respectively. For the selected time periods, EXP Spine returned 2113 publications and 30 were considered relevant. The search filter identified all 30 relevant articles, with a specificity of 94% and precision of 20%. Of the 255 references listed in the narrative index reviews, 225 were indexed in MEDLINE and 165 (73%) were relevant articles. All relevant articles were identified and accuracy ranged from 67 to 97% over the three reviews. Of the 42 articles returned from 3 recent systematic reviews, all were identified by the filter.

conclusionsWe have developed a highly sensitive hedge for the research of DCM. Whilst precision is similarly low as other hedges, this search filter can be used as an adjunct for DCM search strategies.

Indexed as

MEDLINECervical VertebraeHumansInformation Storage and RetrievalReproducibility of ResultsSpinal Cord DiseasesCervicalDegenerationDisc herniationHedgeMEDLINEMyelopathyOssification posterior longitudinal ligamentSearch filterSpondylosisSpondyloticStenosisSystematic review

Identifiers

PMID29976134
PMCPMC6034255
OpenAlexW2845553653

What Socratic 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 Socratic graph.