Evidence map›Paper›PMID 29923070›Full record

ReviewNeurology and therapy2018

A Systematic Review and Meta-Analysis of the Brief Cognitive Assessment for Multiple Sclerosis (BICAMS).

Freya Corfield, Dawn Langdon

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Neurology and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
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

30 citing papers in PubMed.

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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

2 authors.

Freya CorfieldPsychology Department, Royal Holloway, University of London, Egham, Surrey, UK.
Dawn LangdonPsychology Department, Royal Holloway, University of London, Egham, Surrey, UK. d.langdon@rhul.ac.uk.ORCID http://orcid.org/0000-0003-1128-7417

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple sclerosis (MS) is a neurological disease of the central nervous system which can lead to a range of severe physical disabilities. A large proportion of those affected will experience cognitive impairment, which is associated with a worse prognosis. Effective assessment of cognition in MS has been problematic due to a lack of suitable scales. The Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) was developed in 2010 as part of an international endeavour to facilitate cognitive assessment.

aimThe aim of this systematic review and meta-analysis was to synthesise the available literature published as part of the BICAMS international validation protocol.

methodsA literature search conducted using PubMed, PsycINFO and Google Scholar identified 16 studies for inclusion in the systematic review, 14 of which could be included in a meta-analysis.

resultsBICAMS has been widely validated across 11 languages and 14 individual cultures and locations. The meta-analysis demonstrated that BICAMS identified significantly reduced cognitive functioning in adults with MS compared to healthy controls. This was true for all three cognitive domains assessed by BICAMS: information processing speed (g = 0.943, 95% CI 0.839, 1.046, g < 0.001), immediate verbal recall memory (g = 0.688, 95% CI 0.554, 0.822, p < 0.001) and immediate visual recall memory (g = 0.635, 95% CI 0.534, 0.736, p < 0.001).

conclusionBICAMS has been widely applied across cultures and languages to assess cognition in MS. BICAMS offers a feasible, cost-effective means of assessing cognition in MS worldwide. Further validation studies are underway to support this project.

Indexed as

BICAMSBrief International Cognitive Assessment for Multiple SclerosisCognitionMeta-analysisMultiple sclerosisSystematic review

Identifiers

PMID29923070
PMCPMC6283796

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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.