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Record W2521236458 · doi:10.1016/j.trci.2016.09.002

Multiple comorbid neuropathologies in the setting of Alzheimer's disease neuropathology and implications for drug development

2016· review· en· W2521236458 on OpenAlexafffund
Gil D. Rabinovici, María C. Carrillo, Mark S. Forman, Susan DeSanti, David S. Miller, Nicholas Kozauer, Ronald C. Petersen, Christopher Randolph, David S. Knopman, Eric E. Smith, Maria Isaac, Niklas Mattsson, Lisa J. Bain, James A. Hendrix, John R. Sims

Bibliographic record

VenueAlzheimer s & Dementia Translational Research & Clinical Interventions · 2016
Typereview
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
FundersPartenariat Canadien Contre Le CancerCanadian Institutes of Health ResearchAlberta InnovatesAlzheimer's Association
KeywordsNeuropathologyDiseaseDrug developmentNeuroscienceMedicinePsychiatryPsychologyDrugPathology

Abstract

fetched live from OpenAlex

Dementia is often characterized as being caused by one of several major diseases, such as Alzheimer's disease (AD), cerebrovascular disease, Lewy body disease, or a frontotemporal degeneration. Failure to acknowledge that more than one entity may be present precludes attempts to understand interactive relationships. The clinicopathological studies of dementia demonstrate that multiple pathologic processes often coexist. How overlapping pathologic findings affect the diagnosis and treatment of clinical AD and other dementia phenotypes was the topic taken up by the Alzheimer's Association's Research Roundtable in October 2014. This review will cover the neuropathologic basis of dementia, provide clinical perspectives on multiple pathologies, and discuss therapeutics and biomarkers targeting overlapping pathologies and how these issues impact clinical trials.High prevalence of multiple pathologic findings among individuals with clinical diagnosis of AD suggests that new treatment strategies may be needed to effectively treat AD and other dementing illnesses.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.416
GPT teacher head0.547
Teacher spread0.131 · 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 designNot applicable
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".

Quick stats

Citations157
Published2016
Admission routes2
Has abstractyes

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