Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 414

The DOI matches its Crossref record; 130 of the 130 references it cites were found in a registry or an index.

Primary progressive aphasia: clinicopathological correlations

Open access
Grossman, Murray·2010·Nature Reviews Neurology

Abstract

Primary progressive aphasia (PPA) is a disorder of declining language that is a frequent presentation of neurodegenerative diseases such as frontotemporal lobar degeneration. Three variants of PPA are recognized: progressive nonfluent aphasia, semantic dementia, and logopenic progressive aphasia. In an era of etiology-specific treatments for neurodegenerative conditions, determining the histopathological basis of PPA is crucial. Clinicopathological correlations in PPA emphasize the contributory role of dementia with Pick bodies and other tauopathies, TDP-43 proteinopathies, and Alzheimer disease. These data suggest an association between a specific PPA variant and an underlying pathology, although many cases of PPA are associated with an unexpected pathology. Neuroimaging and biofluid biomarkers are now emerging as important adjuncts to clinical diagnosis. There is great hope that the addition of biomarker assessments to careful clinical examination will enable accurate diagnosis of the pathology associated with PPA during a patient's life, and that such findings will serve as the basis for clinical trials in this spectrum of disease.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/nrneurol.2009.216

Cites

130 of 130 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 130 references

Cited by

See all 414

Metadata

Authors
Grossman, M.
Venue
Nature Reviews Neurology
Published
2010-02
Volume
6
Issue
2
Pages
88-97
ISSN
  • 1759-4758 (ISSN-L)
  • 1759-4766
OpenAlex
W2070458400
Cited by
414
References
130
FWCI
4.01
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Primary progressive aphasia: clinicopathological correlations. https://app.cochat.ai/papers/10.1038/nrneurol.2009.216
The paper
Grossman, M. (2010). Primary progressive aphasia: clinicopathological correlations. Nature Reviews Neurology. https://doi.org/10.1038/nrneurol.2009.216

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.