Evidence map›Paper›PMID 36419644›Full record

ArticleFrontiers in human neuroscience2022

Common predictors of spoken and written language performance in aphasia, alexia, and agraphia.

Pélagie M Beeson, Kindle Rising, Alyssa Sachs, Steven Z Rapcsak

Open access · goldAbstract read
In one paragraph

Article in Frontiers in human neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

6 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
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  4. Situating word deafness within aphasia recovery: A case report.Cortex; a journal devoted to the study of the nervous system and behavior · 2024
    Article
  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 2 institutions in 1 country.

Pélagie M BeesonDepartment of Speech, Language, and Hearing Sciences, The University of Arizona, Tucson, AZ, United States.
Kindle RisingDepartment of Speech, Language, and Hearing Sciences, The University of Arizona, Tucson, AZ, United States.
Alyssa SachsDepartment of Speech, Language, and Hearing Sciences, The University of Arizona, Tucson, AZ, United States.
Steven Z RapcsakDepartment of Speech, Language, and Hearing Sciences, The University of Arizona, Tucson, AZ, United States.
University of Arizona · USBanner Alzheimer’s Institute

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Language performance requires support from central cognitive/linguistic abilities as well as the more peripheral sensorimotor skills to plan and implement spoken and written communication. Both output modalities are vulnerable to impairment following damage to the language-dominant hemisphere, but much of the research to date has focused exclusively on spoken language. In this study we aimed to examine an integrated model of language processing that includes the common cognitive processes that support spoken and written language, as well as modality-specific skills. To do so, we evaluated spoken and written language performance from 87 individuals with acquired language impairment resulting from damage to left perisylvian cortical regions that collectively constitute the dorsal language pathway. Comprehensive behavioral assessment served to characterize the status of central and peripheral components of language processing in relation to neurotypical controls (

Indexed as

aphasiadorsal language pathwaynamingphonological agraphiaphonological alexiareadingspellingwriting

Identifiers

PMID36419644
PMCPMC9677348
OpenAlexW4308480431

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.