Evidence map›Paper›PMID 35926368›Full record

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

Predictors beyond the lesion: Health and demographic factors associated with aphasia severity.

Lisa Johnson, Samaneh Nemati, Leonardo Bonilha, Chris Rorden, Natalie Busby, Alexandra Basilakos, Roger Newman-Norlund, Argye E Hillis, Gregory Hickok, Julius Fridriksson

Abstract 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 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.

  1. Article
  2. Accelerated brain aging and anterior white matter hyperintensity burden in chronic post-stroke aphasia: a lesion-aware MRI analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
    Article
  3. Article
  4. Article
  5. Digital Twin Model of Treatment Outcomes in Post-Stroke Aphasia.medRxiv : the preprint server for health sciences · 2026
    Article
  6. Gene Expression-Based Lesion-Symptom Mapping:The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Effective neural connectivity deficits during speech auditory feedback processing in post-stroke aphasia: An fMRI study.Cortex; a journal devoted to the study of the nervous system and behavior · 2025
    Article
  11. 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

10 authors.

Lisa JohnsonDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA. Electronic address: LJ4@email.sc.edu.
Samaneh NematiDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
Leonardo BonilhaDepartment of Neurology, Medical University of South Carolina, Charleston, SC, USA.
Chris RordenDepartment of Psychology, University of South Carolina, Columbia, SC, USA.
Natalie BusbyDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
Alexandra BasilakosDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
Roger Newman-NorlundDepartment of Psychology, University of South Carolina, Columbia, SC, USA.
Argye E HillisDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Gregory HickokDepartment of Cognitive Sciences, University of California, Irvine, CA, USA.
Julius FridrikssonDepartment of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.

Funding

Telerehab for Aphasia (TERRA)P50DC014664 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FRIDRIKSSON, JULIUS · 2016 to 2025
$25.0M
Trans-cranial Direct Current Stimulation to Treat Aphasia: Phase II TrialU01DC011739 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FRIDRIKSSON, JULIUS · 2012 to 2016
$4.4M
Interdisciplinary Research Training in Otolaryngology and Communication SciencesT32DC014435 · NIDCD · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI DUBNO, JUDY R · 2015 to 2024
$2.9M
Neural Predictors of Anomia Recovery in AphasiaR01DC008355 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FRIDRIKSSON, JULIUS · 2007 to 2011
$1.7M
A Unified Neuroanatomical Model of Speech Production and Perception: ImplicationsR01DC009571 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FRIDRIKSSON, JULIUS, RORDEN, CHRISTOPHER · 2009 to 2013
$1.6M
SEMANTIC FEATURE PROCESSING IN INDIVIDUALS WITH STROKE APHASIAR03DC010262 · NIDCD · WORCESTER STATE COLLEGE · PI ANTONUCCI, SHARON · 2010 to 2012
$409k
Speech Entrainment Treatment for Broca's AphasiaR21DC014170 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FRIDRIKSSON, JULIUS · 2015 to 2016
$403k
Neurological Predictors of Aphasia RecoveryR03DC005915 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FRIDRIKSSON, JULIUS · 2003 to 2005
$218k
NIDCD NIH HHS P50 DC014664NIDCD NIH HHS R01 DC008355NIDCD NIH HHS R01 DC009571NIDCD NIH HHS R03 DC005915NIDCD NIH HHS R03 DC010262NIDCD NIH HHS R21 DC014170NIDCD NIH HHS T32 DC014435NIDCD NIH HHS U01 DC011739
6 · The paper itself

Abstract

backgroundLesion-related factors are associated with severity of language impairment in persons with aphasia. The extent to which demographic and health factors predict language impairment beyond traditional cortical measures remains unknown. Identifying and understanding the contributions of factors to predictive models of severity constitutes critical knowledge for clinicians interested in charting the likely course of aphasia in their patients and designing effective treatment approaches in light of those predictions.

methodsUtilizing neuroimaging and language testing from our cohort of 224 individuals in the chronic stage of recovery from a left-hemisphere stroke in a cross-sectional study, we first conducted a lesion symptom mapping (LSM) analysis to identify regions associated with aphasia severity scores. After controlling for lesion volume and damage to pre-identified areas, three models were created to predict severity scores: 1) Demographic Model (N = 147); 2) Health Model (N = 106); and 3) Overall Model (N = 106). Finally, all identified factors were entered into a Final Model to predict raw severity scores.

resultsTwo areas were associated with aphasia severity-left posterior insula and left arcuate fasciculus. The results from the Demographic Model revealed non-linguistic cognitive ability, age at stroke, and time post-stroke as significant predictors of severity (P = .005; P = .02; P = .001, respectively), and results from the Health Model suggested the extent of leukoaraiosis is associated with severity (P = .0004). The Overall Model showed a relationship between aphasia severity and cognitive ability (P = .01), time post-stroke (P = .002), and leukoaraiosis (P = .01). In the Final Model, which aimed to predict raw severity scores, demographic, health, and lesion factors explained 55% of the variance in severity, with health and demographic factors uniquely explaining nearly half of performance variance.

conclusionsResults from this study add to the literature suggesting patient-specific variables can shed light on individual differences in severity beyond lesion factors. Additionally, our results emphasize the importance of non-linguistic cognitive ability and brain health in aphasia recovery.

Indexed as

AphasiaLanguage Development DisordersLeukoaraiosisStrokeBrainCross-Sectional StudiesDemographyHumansMagnetic Resonance ImagingAgingAphasiaLeukoaraiosisRecoveryStroke

Identifiers

PMID35926368
PMCPMC11205278

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Registered trials

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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.