Evidence map›Paper›PMID 37002267›Full record

ArticleCommunications biology2023

Bayesian stroke modeling details sex biases in the white matter substrates of aphasia.

Julius M Kernbach, Gesa Hartwigsen, Jae-Sung Lim, Hee-Joon Bae, Kyung-Ho Yu, Gottfried Schlaug, Anna Bonkhoff, Natalia S Rost, Danilo Bzdok

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 26% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Using unsupervised dimensionality reduction to identify lesion patterns predictive of post-stroke aphasia severity.Cortex; a journal devoted to the study of the nervous system and behavior · 2025
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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

9 authors at 7 institutions in 4 countries.

Julius M KernbachNeurosurgical Artificial Intelligence Laboratory Aachen (NAILA), RWTH Aachen University Hospital, Aachen, Germany.ORCID 0000-0002-0256-1923
Gesa HartwigsenMax Planck Institute for Human Cognitive and Brain Sciences, Lise Meitner Research Group Cognition and Plasticity, Leipzig, Germany.ORCID 0000-0002-8084-1330
Jae-Sung LimDepartment of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Hee-Joon BaeDepartment of Neurology, Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea.
Kyung-Ho YuDepartment of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea.ORCID 0000-0002-8997-5626
Gottfried SchlaugMusic, Neuroimaging, and Stroke Recovery Laboratory, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, 02215, USA.
Anna BonkhoffJ. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Natalia S RostJ. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Danilo BzdokDepartment of Biomedical Engineering, McConnell Brain Imaging Centre, Montreal Neurological Institute, Faculty of Medicine, School of Computer Science, McGill University, Montreal, QC, Canada. danilo.bzdok@mcgill.ca.ORCID 0000-0003-3466-6620
Beth Israel Deaconess Medical Center · USHarvard University · USHallym University Sacred Heart Hospital · KRMax Planck Institute for Human Cognitive and Brain Sciences · DEMontreal Neurological Institute and Hospital · CASeoul National University Bundang Hospital · KRUlsan College · KR

Funding

Investigating the impact of loneliness on brain aging and pre-symptomatic Alzheimer's disease progressionR01AG068563 · NIA · MCGILL UNIVERSITY · PI BZDOK, DANILO, SPRENG, ROBERT NATHAN · 2020 to 2024
$2.3M
NIA NIH HHS R01 AG068563
6 · The paper itself

Abstract

Ischemic cerebrovascular events often lead to aphasia. Previous work provided hints that such strokes may affect women and men in distinct ways. Women tend to suffer strokes with more disabling language impairment, even if the lesion size is comparable to men. In 1401 patients, we isolate data-led representations of anatomical lesion patterns and hand-tailor a Bayesian analytical solution to carefully model the degree of sex divergence in predicting language outcomes ~3 months after stroke. We locate lesion-outcome effects in the left-dominant language network that highlight the ventral pathway as a core lesion focus across different tests of language performance. We provide detailed evidence for sex-specific brain-behavior associations in the domain-general networks associated with cortico-subcortical pathways, with unique contributions of the fornix in women and cingular fiber bundles in men. Our collective findings suggest diverging white matter substrates in how stroke causes language deficits in women and men. Clinically acknowledging such sex disparities has the potential to improve personalized treatment for stroke patients worldwide.

Indexed as

AphasiaStrokeWhite MatterBayes TheoremBiasFemaleHumansMale

Identifiers

PMID37002267
PMCPMC10066402
OpenAlexW4362475097

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.