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Record W4379400740 · doi:10.14283/jpad.2023.72

Clinicians' Perspectives on How Disease Modifying Drugs for Alzheimer's Disease Impact Specialty Care

2023· article· en· W4379400740 on OpenAlexaff
Serge Gauthier, Zahinoor Ismail, Zahra Goodarzi, Kee Peng Ng, Pedro Rosa‐Neto

Bibliographic record

VenueThe Journal of Prevention of Alzheimer s Disease · 2023
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineReferralDiseaseSpecialtyPopulationIntensive care medicineInternal medicinePathologyFamily medicine

Abstract

fetched live from OpenAlex

Clinicians specialized in the diagnosis and management of persons living with early-stage Alzheimer's disease need to enable access, for those meeting criteria, to the new class of disease modifying drugs (DMDs). These drugs act on amyloid β42 and delay progression of symptoms. Thus, there will be interest from patients and families. Over the short term, the use of antibodies administered intravenously with serial MRIs to detect amyloid-related imaging abnormalities (ARIA) may require participation in structured phase 4 studies or in registries with third party funding for support staff and MRI scans. In the mid term, the availability of oral anti-amyloid therapy, likely with lower risk of ARIA, may transform clinical practice to a model of screening suitable patients using plasma biomarkers, with a subsequent rapid referral to a specialized memory clinic. Eventually, the biological profile of patients for amyloid, tau, and inflammation will determine which type of DMD to use. We are optimistic that clinicians will gain confidence with the use DMDs and answer the increasing needs of our aging population.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.069
GPT teacher head0.400
Teacher spread0.331 · 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.

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

Citations6
Published2023
Admission routes1
Has abstractyes

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