Evidence map›Paper›PMID 33447252›Full record

ArticleFrontiers in neurology2020

Data-Driven, Visual Framework for the Characterization of Aphasias Across Stroke, Post-resective, and Neurodegenerative Disorders Over Time.

Joline M Fan, Maria Luisa Gorno-Tempini, Nina F Dronkers, Bruce L Miller, Mitchel S Berger, Edward F Chang

Abstract read
In one paragraph

Article in Frontiers in neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
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

6 authors.

Joline M FanDepartment of Neurology, University of California, San Francisco, San Francisco, CA, United States.
Maria Luisa Gorno-TempiniDepartment of Neurology, University of California, San Francisco, San Francisco, CA, United States.
Nina F DronkersDepartment of Psychology, University of California, Berkeley, Berkeley, CA, United States.
Bruce L MillerDepartment of Neurology, University of California, San Francisco, San Francisco, CA, United States.
Mitchel S BergerDepartment of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.
Edward F ChangDepartment of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.

Funding

TDP-43 Loss-of-Function: Biology to BiomarkersP01AG019724 · NIA · UNIVERSITY OF PENNSYLVANIA · PI BRUCE L MILLER · 2002 to 2026
$67.2M
Progressive Aphasia Cognition Anatomy and ProgressionR01NS050915 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARIA LUISA GORNO TEMPINI · 2004 to 2026
$11.0M
NRSA Training CoreTL1TR001871 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KANAYA, ALKA M., SOMSOUK, MA · 2016 to 2025
$10.1M
Functional organization of the superior temporal gyrus for speech perceptionR01DC012379 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Edward Chang · 2012 to 2026
$8.3M
Connectomic imaging in familial and sporadic frontotemporal degenerationU01AG052943 · NIA · UNIVERSITY OF PENNSYLVANIA · PI GORNO TEMPINI, MARIA LUISA, GROSSMAN, MURRAY · 2016 to 2019
$5.9M
Dynamic Brain Imaging of Speech in Primary Progressive AphasiaR01NS100440 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARIA LUISA GORNO TEMPINI, John Francis Houde · 2017 to 2026
$3.6M
Defining trajectories of dynamic biomarkers for C9ORF72 repeat expansion carriersR01AG058233 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LEE, SUZEE EURIE · 2018 to 2022
$3.2M
Neural Mechanisms of Language Production Decline in Primary Progressive AphasiaR01DC016345 · NIDCD · UNIVERSITY OF CALIFORNIA BERKELEY · PI DRONKERS, NINA F. · 2017 to 2022
$2.8M
Training program in the neurology of language and neurodegenerative aphasiasK24DC015544 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GORNO TEMPINI, MARIA LUISA · 2016 to 2025
$1.9M
Neocortical Mechanisms of Categorical Speech PerceptionR00NS065120 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHANG, EDWARD · 2010 to 2012
$729k
NCATS NIH HHS TL1 TR001871NIA NIH HHS P01 AG019724NIA NIH HHS R01 AG058233NIA NIH HHS U01 AG052943NIDCD NIH HHS K24 DC015544NIDCD NIH HHS R01 DC012379NIDCD NIH HHS R01 DC016345NINDS NIH HHS R00 NS065120NINDS NIH HHS R01 NS050915NINDS NIH HHS R01 NS100440
6 · The paper itself

Abstract

Aphasia classifications and specialized language batteries differ across the fields of neurodegenerative disorders and lesional brain injuries, resulting in difficult comparisons of language deficits across etiologies. In this study, we present a simplified framework, in which a widely-used aphasia battery captures clinical clusters across disease etiologies and provides a quantitative and visual method to characterize and track patients over time. The framework is used to evaluate populations representing three disease etiologies: stroke, primary progressive aphasia (PPA), and post-operative aphasia. A total of 330 patients across three populations with cerebral injury leading to aphasia were investigated, including 76 patients with stroke, 107 patients meeting criteria for PPA, and 147 patients following left hemispheric resective surgery. Western Aphasia Battery (WAB) measures (Information Content, Fluency, answering Yes/No questions, Auditory Word Recognition, Sequential Commands, and Repetition) were collected across the three populations and analyzed to develop a multi-dimensional aphasia model using dimensionality reduction techniques. Two orthogonal dimensions were found to explain 87% of the variance across aphasia phenotypes and three disease etiologies. The first dimension reflects shared weighting across aphasia subscores and correlated with aphasia severity. The second dimension incorporates fluency and comprehension, thereby separating Wernicke's from Broca's aphasia, and the non-fluent/agrammatic from semantic PPA variants. Clusters representing clinical classifications, including late PPA presentations, were preserved within the two-dimensional space. Early PPA presentations were not classifiable, as specialized batteries are needed for phenotyping. Longitudinal data was further used to visualize the trajectory of aphasias during recovery or disease progression, including the rapid recovery of post-operative aphasic patients. This method has implications for the conceptualization of aphasia as a spectrum disorder across different disease etiology and may serve as a framework to track the trajectories of aphasia progression and recovery.

Indexed as

aphasiaprimary progressive aphasiaprincipal component analysesstroketrajectories

Identifiers

PMID33447252
PMCPMC7801263

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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.