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Record W4403716428 · doi:10.1111/ene.16255

Plasma phosphorylated tau181 outperforms [<scp><sup>18</sup>F</scp>] <scp>fluorodeoxyglucose positron emission tomography</scp> in the identification of early Alzheimer disease

2024· article· en· W4403716428 on OpenAlexafffundabout
Kely Quispialaya, Joseph Therriault, Antonio Aliaga, Cécile Tissot, Stijn Servaes, Nesrine Rahmouni, Thomas K. Karikari, Andréa Lessa Benedet, Nicholas J. Ashton, Arthur C. Macedo, Firoza Z Lussier, Jenna Stevenson, Jaime Fernández Arias, Seyyed Ali Hosseini, Takashi Matsudaira, Bertrand J. Jean‐Claude, Brian M. Gilfix, Eduardo R. Zimmer, Jean‐Paul Soucy, Tharick A. Pascoal, Serge Gauthier, Henrik Zetterberg, Kaj Blennow, Pedro Rosa‐Neto

Bibliographic record

VenueEuropean Journal of Neurology · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteMontreal Neurological Institute and Hospital
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchHORIZON EUROPE Framework ProgrammeUniversity of California, San DiegoGenentechNational Institutes of HealthUK Dementia Research InstituteVetenskapsrådetEisaiUniversity of Southern CaliforniaUniversity College LondonEU Joint Programme – Neurodegenerative Disease ResearchWeston Brain InstituteNational Institute on AgingNational Institute for Health and Care ResearchNorthern California Institute for Research and EducationHjärnfondenEuropean CommissionFamiljen Erling-Perssons StiftelseFondation Brain CanadaBiogenBioClinicaAlzheimer's AssociationStiftelsen för Gamla TjänarinnorEli Lilly and CompanyU.S. Department of DefenseAlzheimer's Disease Neuroimaging InitiativeF. Hoffmann-La RocheBristol-Myers SquibbConsortium canadien en neurodégénérescence associée au vieillissementMcGill University
KeywordsPositron emission tomographyMedicineCerebrospinal fluidFluorodeoxyglucoseNeuroimagingDementiaNuclear medicinePathologyInternal medicineDiseasePsychiatry

Abstract

fetched live from OpenAlex

Abstract Background and purpose This study was undertaken to compare the performance of plasma p‐tau181 with that of [ 18 F]fluorodeoxyglucose (FDG) positron emission tomography (PET) in the identification of early biological Alzheimer disease (AD). Methods We included 533 cognitively impaired participants from the Alzheimer's Disease Neuroimaging Initiative. Participants underwent PET scans, biofluid collection, and cognitive tests. Receiver operating characteristic analyses were used to determine the diagnostic accuracy of plasma p‐tau181 and [ 18 F]FDG‐PET using clinical diagnosis and core AD biomarkers ([ 18 F]florbetapir‐PET and cerebrospinal fluid [CSF] p‐tau181) as reference standards. Differences in the diagnostic accuracy between plasma p‐tau181 and [ 18 F]FDG‐PET were determined by bootstrap‐based tests. Correlations of [ 18 F]FDG‐PET and plasma p‐tau181 with CSF p‐tau181, amyloid β (Aβ) PET, and cognitive performance were evaluated to compare associations between measurements. Results We observed that both plasma p‐tau181 and [ 18 F]FDG‐PET identified individuals with positive AD biomarkers in CSF or on Aβ‐PET. In the MCI group, plasma p‐tau181 outperformed [ 18 F]FDG‐PET in identifying AD measured by CSF ( p = 0.0007) and by Aβ‐PET ( p = 0.001). We also observed that both plasma p‐tau181 and [ 18 F]FDG‐PET metabolism were associated with core AD biomarkers. However, [ 18 F]FDG‐PET uptake was more closely associated with cognitive outcomes (Montreal Cognitive Assessment, Mini‐Mental State Examination, Clinical Dementia Rating Sum of Boxes, and logical memory delayed recall, p &lt; 0.001) than plasma p‐tau181. Conclusions Overall, although both plasma p‐tau181 and [ 18 F]FDG‐PET were associated with core AD biomarkers, plasma p‐tau181 outperformed [ 18 F]FDG‐PET in identifying individuals with early AD pathophysiology. Taken together, our study suggests that plasma p‐tau181 may aid in detecting individuals with underlying early AD.

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 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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.280
Teacher spread0.261 · 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
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

Citations8
Published2024
Admission routes3
Has abstractyes

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