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Record W4319161166 · doi:10.1101/2023.01.31.23285249

Design and feasibility of an Alzheimer’s disease blood test study in a diverse community-based population

2023· preprint· en· W4319161166 on OpenAlexaboutno aff
Melody Li, Yan Li, Suzanne E. Schindler, Daniel Yen, Siobhan Sutcliffe, Ganesh M. Babulal, Tammie L.S. Benzinger, Eric J. Lenze, Randall J. Bateman

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institutes of HealthGHR FoundationInstitute of Clinical and Translational SciencesFoundation for Barnes-Jewish Hospital
KeywordsClinical Dementia RatingDementiaBlood testGerontologyTest (biology)Montreal Cognitive AssessmentMedicinePopulationCohortDiseaseClinical psychologyPsychologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

ABSTRACT INTRODUCTION Alzheimer’s disease (AD) blood tests are likely to become increasingly important in clinical practice, but need to be evaluated in diverse groups before use in the general population. METHODS This study enrolled a community-based sample of older adults in the Saint Louis, Missouri, USA area. Participants completed a blood draw, AD8® dementia screening interview, Montreal Cognitive Assessment (MoCA), and survey about their perceptions of the blood test. A subset of participants completed additional blood collection, amyloid PET, MRI, and Clinical Dementia Rating® (CDR). RESULTS Of the 859 participants enrolled in this ongoing study, 20.6% self-identified as Black or African American. The AD8 and MoCA correlated moderately with the CDR. The blood test was well-accepted by the cohort, but perceived more positively by White and highly educated individuals. DISCUSSION Studying an AD blood test in a diverse population is feasible, and may accelerate accurate diagnosis and implementation of effective treatments.

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)0.010
metaresearch head score (Gemma)0.008
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: Protocol · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
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 head0.218
GPT teacher head0.416
Teacher spread0.198 · 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
GenreProtocol

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
Published2023
Admission routes1
Has abstractyes

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Same venuemedRxiv→Same topicDementia and Cognitive Impairment Research→French-language works237,207→