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Record W4391123303 · doi:10.1016/s1474-4422(23)00414-3

Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis

2024· review· en· W4391123303 on OpenAlexafffund
Marianne Chapleau, Renaud La Joie, Keir Yong, Federica Agosta, Isabel Elaine Allen, Liana G. Apostolova, John Best, Baayla D.C. Boon, Sebastian J. Crutch, Massimo Filippi, Giorgio Fumagalli, Daniela Galimberti, Jonathan Graff‐Radford, Lea T. Grinberg, David J. Irwin, Keith A. Josephs, Patricio Chrem Méndez, Raffaella Migliaccio, Zachary Miller, Maxime Montembeault, Melissa E. Murray, Sára Nemes, Victoria S. Pelak, Daniela Perani, Jeffrey S. Phillips, Yolande A.L. Pijnenburg, Emily Rogalskı, Jonathan M. Schott, William W. Seeley, A. Campbell Sullivan, Salvatore Spina, Jeremy A. Tanner, Jamie M. Walker, Jennifer Whitwell, David A. Wolk, Rik Ossenkoppele, Gil D. Rabinovici, Zeinab Abdi, Samrah Ahmed, Daniel Alcolea, Kieren Allinson, Andrea Arighi, Mircea Balasa, Frederik Barkhof, Katherine D. Brandt, Jared R. Brosch, James R. Burrell, Christopher Butler, Ismael Luis Calandri, Silvia Paola Caminiti, Elisa Canu, María C. Carrillo, Francesca Caso, Min Chu, Nicholas J. Cordato, Ana Sofia Costa, Yue Cui, Bradford C. Dickerson, Dennis W. Dickson, Ranjan Duara, Bruno Dubois, Mark C. Eldaief, Martin Farlow, Chiara Fenoglio, Klaus Fließbach, Maïté Formaglio, Juan Fortea, Nick C. Fox, David Foxe, Caroline Tilikete, Matthew P. Frosch, Douglas Galasko, Oscar Garat, Giulia Giardinieri, Caroline Graff, Colin Groot, Ann Marie Hake, Oskar Hansson, Alison Headley, Micaela A Hernández, Daisy Hochberg, John R. Hodges, Patrick R. Hof, Janice L. Holton, Gabrielle Hromas, Ignacio Illán‐Gala, Zane Jaunmuktane, Donglai Jing, Sonja M. Kagerer, Kensaku Kasuga, Yu Kong, Enikò Kövari, Mégane Lacombe-Thibault, Alberto Lleó, Robert Laforce, Tammaryn Lashley, Gabriel C. Léger, Richard Lévy, Yang Liu, Li Liu, Albert Lladó Plarrumaní, Diane Lucente, Mary M. Machulda, Giuseppe Magnani, Éloi Magnin, Maura Malpetti, Brandy R. Matthews, Scott McGinnis, Mario F. Mendez, Marsel Mesulam, Carolin Miklitz, Nidhi S. Mundada, Peter J. Nestor, Dilek Ocal, Ross W. Paterson, Olivier Piguet, Deepti Putcha, Megan Quimby, Kathrin Reetz, Netaniel Rein, Tamás Révész, Neguine Rezaii, Federico Rodríguez‐Porcel, James B. Rowe, Natalie S. Ryan, Raquel Sánchez‐Valle, Luca Sacchi, Miguel Santos‐Santos, Janet C. Sherman, Erik Stomrud, Pontus Tideman, Takayoshi Tokutake, Giacomo Tondo, Alexandra Touroutoglou, Babak Tousi, Rik Vandenberghe, Wiesje M. van der Flier, Sandra Weıntraub, Bonnie Wong, Liyong Wu, Kexin Xie

Bibliographic record

VenueThe Lancet Neurology · 2024
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersNational Institute of Neurological Disorders and StrokeNational Institute on Deafness and Other Communication DisordersNational Institute on AgingNIHR Cambridge Biomedical Research CentreNational Health and Medical Research CouncilEconomic and Social Research CouncilMedical Research CouncilFonds de Recherche du Québec - SantéAvid RadiopharmaceuticalsNational Institutes of HealthGIESKES-STRIJBIS FONDSAlzheimer's SocietyItalfarmacoFondation pour la Recherche sur AlzheimerGenentechMarcus och Amalia Wallenbergs minnesfondCelgeneSkånes universitetssjukhusStichting DioraphteNational Natural Science Foundation of ChinaUK Dementia Research InstituteFondazione Italiana di Ricerca per la Sclerosi Laterale AmiotroficaKnut och Alice Wallenbergs StiftelseAustralian GovernmentLunds UniversitetVetenskapsrådetEisaiWolfson FoundationBrain Research TrustEli Lilly and CompanyHersenstichtingBristol-Myers SquibbTeva Pharmaceutical IndustriesDepartment of Health and Social CareUniversity College LondonBritish Heart FoundationParkinsonfondenMinistero della SaluteMater FoundationPfizerEU Joint Programme – Neurodegenerative Disease ResearchZonMwWeston Brain InstituteReta Lila Weston Institute of Neurological Studies, UCL Queen Square Institute of Neurology,University College LondonKonung Gustaf V:s och Drottning Victorias FrimurarestiftelseNederlandse Organisatie voor Wetenschappelijk OnderzoekFondazione Italiana Sclerosi MultiplaAlzheimer NederlandBiogenNovo NordiskUniversity of PennsylvaniaAlexion PharmaceuticalsNational Institute for Health and Care ResearchAlzheimer's AssociationRoche NederlandSanofi
KeywordsBiomarkerAtrophyMeta-analysisCohortMedicineCohort studyPosterior cortical atrophyPathologyOncologyBiologyDiseaseDementia

Abstract

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Background Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort. Methods We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I 2 . Findings We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9–59·8; I 2 =77%), 60% (56–64; I 2 =35%) were women, and 80% (72–89; I 2 =98%) presented with posterior cortical atrophy pure syndrome. Amyloid β in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75–87; I 2 =78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56–75; I 2 =87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90–97; I 2 =15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93–100; I 2 =12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90–97; I 2 =0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54–88; I 2 =89%), Lewy body disease (44%, 25–62; I 2 =77%), and cerebrovascular injury (42%, 24–60; I 2 =88%). Interpretation These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity. Funding None.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.281
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.531
GPT teacher head0.519
Teacher spread0.013 · 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 teacher head, not a consensus.

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

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".

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Citations63
Published2024
Admission routes2
Has abstractyes

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