Evidence map›Paper›PMID 36087431›Full record

ArticleCortex; a journal devoted to the study of the nervous system and behavior2022

Efficient and effective assessment of deficits and their neural bases in stroke aphasia.

Ajay D Halai, Blanca De Dios Perez, James D Stefaniak, Matthew A Lambon Ralph

Open access · hybridAbstract read
In one paragraph

Article in Cortex; a journal devoted to the study of the nervous system and behavior, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

11 citing papers in PubMed, 25 citations in OpenAlex.

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  9. Defining aphasia: Content analysis of six aphasia diagnostic batteries.Cortex; a journal devoted to the study of the nervous system and behavior · 2023
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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 1 country.

Ajay D HalaiMRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, United Kingdom. Electronic address: ajay.halai@mrc-cbu.cam.ac.uk.
Blanca De Dios PerezNeuroscience and Aphasia Research Unit (NARU), School of Biological Sciences, The University of Manchester, Manchester, United Kingdom; Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, United Kingdom.
James D StefaniakNeuroscience and Aphasia Research Unit (NARU), School of Biological Sciences, The University of Manchester, Manchester, United Kingdom.
Matthew A Lambon RalphMRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, United Kingdom. Electronic address: matt.lambon-ralph@mrc-cbu.cam.ac.uk.
MRC Cognition and Brain Sciences Unit · GBUniversity of Manchester · GBUniversity of Nottingham · GB

Funding

Medical Research Council MC_UU_00030/9Medical Research Council MR/R023883/1Medical Research Council MR/V031481/1Wellcome Trust 203914/Z/16/Z
6 · The paper itself

Abstract

objectiveMulti-assessment batteries are necessary for diagnosing and quantifying the multifaceted deficits observed post-stroke. Extensive batteries are thorough but impractically long for clinical settings or large-scale research studies. Clinically-targeted "shallow" batteries superficially cover a wide range of language skills relatively quickly but can struggle to identify mild deficits or quantify the impairment level. Our aim was to compare these batteries across a large group of chronic stroke aphasia and to test a novel data-driven reduced version of an extensive battery that maintained sensitivity to mild impairment, ability to grade deficits and the underlying component structure.

methodsWe tested 75 chronic left-sided stroke participants, spanning global to mild aphasia. The underlying structure of these three batteries was analysed using cross-validation and principal component analysis, in addition to univariate and multivariate lesion-symptom mapping.

resultsThis revealed a four-factor solution for the extensive and data-reduced batteries, identifying phonology, semantic skills, fluency and executive function in contrast to a two-factor solution using the shallow battery (language severity and cognitive severity). Lesion symptom mapping using participants' factor scores identified convergent neural structures for phonology (superior temporal gyrus), semantics (inferior temporal gyrus), speech fluency (precentral gyrus) and executive function (lateral occipitotemporal cortex). The two shallow battery components converged with the phonology and executive function clusters. In addition, we show that multivariate models could predict the component scores using neural data, however not for every component.

conclusionsOverall, the data-driven battery appears to be an effective way to save time yet retain maintained sensitivity to mild impairment, ability to grade deficits and the underlying component structure observed in post-stroke aphasia.

Indexed as

AphasiaStrokeBrainBrain MappingHumansMagnetic Resonance ImagingNeuropsychological TestsAssessment sensitivityComprehensive AphasiaPost-stroke aphasiaPrincipal component analysistest

Identifiers

PMID36087431
PMCPMC9548407
OpenAlexW4291335374

What OpenQuestion holds

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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.