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Apolipoprotein E‐polymorphism, frailty and mortality in older adults

2008· article· en· W2034294534 on OpenAlexafffundabout
Kenneth Rockwood, Bassam A Nassar, Arnold Mitnitski

Bibliographic record

VenueJournal of Cellular and Molecular Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchDalhousie UniversityDalhousie Medical Research Foundation
KeywordsGerontologyPolymorphism (computer science)Apolipoprotein EMedicineGeneticsBiologyDemographyInternal medicineGenotypeGeneDiseaseSociology

Abstract

fetched live from OpenAlex

Although apolipoprotein E (ApoE) polymorphism is associated with variable risks of several illnesses, and with mortality, no persuasive relationship has been demonstrated with frailty. Here, the clinical examination cohort (n=1452 older adults, aged 70+ years at baseline) of the Canadian Study of Health and Aging was evaluated, with 5-year follow-up data. Frailty was defined using both the phenotypic definition from the Cardiovascular Health Study (Frailty-CHS) and the 'Frailty Index', from which age-specific trajectories of deficit accumulation can be estimated. In age-sex adjusted analyses, people with ApoE 4 allele had a higher risk of death (hazard ratio [HR]=1.20; 95% confidence interval: 1.01-1.45), but this relationship was not significant when adjusted for cognitive impairment (1.06; 95% confidence interval: 0.88-1.27). There was no association between frailty and ApoE polymorphism, defined in age-sex adjusted models either as Frailty-CHS (ApoE4 HR 1.17; 95% confidence interval: 0.98-1.40, frailty HR 1.37; 95% confidence interval: 1.28-1.46) or by the Frailty Index (ApoE4 HR 1.07; 95% confidence interval: 0.90-1.29, frailty HR 35.3; 95% confidence interval: 20.4-61.1). The data do not support an association between ApoE polymorphism and frailty. This result did not depend on how frailty was defined.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.268
Teacher spread0.250 · 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

Citations43
Published2008
Admission routes3
Has abstractyes

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