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Record W4311999505 · doi:10.1002/alz.064818

Biomarkers and neuropathology in posterior cortical atrophy: an international, multi‐site study

2022· article· en· W4311999505 on OpenAlexaff
Marianne Chapleau, Renaud La Joie, Nidhi S. Mundada, Giorgio Fumagalli, Maïté Formaglio, Lea T. Grinberg, Gabrielle Hromas, Kensaku Kasuga, Mégane Lacombe‐Thibault, Netta Levin, Albert Lladó, Carolin Miklitz, Daniela Perani, Federico J. Rodriguez-Porcel, William W. Seeley, Salvatore Spina, Babak Tousi, Rik Vandenberghe, Jamie M. Walker, Liyong Wu, Keir Yong, Victoria S. Pelak, Rik Ossenkoppele, Gil D. Rabinovici

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsNeuropathologyPosterior cortical atrophyMedicineAtrophyBiomarkerNeuroimagingInternal medicinePathologyOncologyImaging biomarkerCohortDiseaseMagnetic resonance imagingDementiaPsychiatryRadiologyBiology

Abstract

fetched live from OpenAlex

Abstract Background Posterior cortical atrophy (PCA) is a clinically defined syndrome characterized by impairment in higher‐order visual processing. The underlying pathology in PCA is most commonly Alzheimer’s disease (AD), but large‐scale biomarker and neuropathological studies are lacking. In this ongoing project we aim to describe demographic, clinical, biomarker and neuropathological correlates of PCA in a large‐scale international cohort. Method We contacted 55 research centers conducting PCA research identified in a literature review (n=1353 papers) as well as additional sites recruited through the ISTAART Atypical AD Professional Interest Group (n=7 sites) requesting deidentified, single‐subject data from PCA patients (published and unpublished). Inclusion criteria were: 1. clinical diagnosis of PCA, 2. availability of AD biomarkers (PET or CSF) or 3. availability of autopsy diagnosis. Single‐subject demographic, clinical, fluid, neuroimaging and neuropathological data were collected. Result As of January 2022, we have collected individual patient data from 390 participants evaluated at 14 sites in 10 countries (Table 1). In the preliminary sample, mean age at symptom onset was 63.1 ± 8.8 years, 62.3% of participants were female, and 78.3% presented with a “PCA‐pure” clinical syndrome by Crutch 2017 diagnostic criteria. APOE4 genotype was present in 45.6% (n=125). Preliminary results show that 82.9% (n=270) display predominant MRI atrophy and 91.9% (n=185) predominant FDG hypometabolism in posterior cortical regions. CSF amyloid markers were positive in 80.2% participants (n=187), while CSF phosphorylated tau markers were positive in 61.4% (n=184). Amyloid PET was positive in 85.2% (n=129) while tau PET was only available in 65 patients (positive in all, and all were amyloid positive). At autopsy (n=36, data from 4 centers), high AD neuropathologic changes were found in all but one patient, who had primary frontotemporal lobar degeneration with TDP‐43 type A pathology. Lewy bodies, argyrophilic grains and cerebral amyloid angiopathy were common co‐pathologies (Figure 1). Conclusion In a large international cohort, PCA is strongly associated with positive AD biomarkers and neuropathology. Data collection is ongoing, and we further aim to identify clinical features associated with non‐AD underlying causes of PCA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.294
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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