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Record W2082485125 · doi:10.1016/j.jalz.2011.03.012

Nonsteroidal anti‐inflammatory drug use and the risk of cognitive impairment and Alzheimer's disease

2012· article· en· W2082485125 on OpenAlexaffabout
Sharlène Côté, Pierre‐Hugues Carmichael, René Verreault, Joan Lindsay, Jean Lefèbvre, Danielle Laurin

Bibliographic record

VenueAlzheimer s & Dementia · 2012
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsUniversity of OttawaUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsDementiaMedicineHazard ratioIncidence (geometry)Internal medicineConfidence intervalDiseaseCohort studyObservational studyCohortPopulationAlzheimer's diseaseProportional hazards modelVascular dementiaEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Some observational studies have established an association between exposure to nonsteroidal anti-inflammatory drugs (NSAIDs) and a decreased risk of subsequently developing Alzheimer's disease (AD). Mild cognitive impairment or cognitive impairment, not dementia (CIND) is more likely to convert to AD, and no specific preventive method is currently available. The objective of this study was to determine the association of NSAID use in 5276 cognitively normal subjects of the Canadian Study of Health and Aging, a 10-year population-based cohort study, with the incidence of CIND, AD, and all-cause dementia. METHODS: Hazard ratios were calculated from Cox proportional hazards models with age as the time scale according to three study samples including 824 cases of dementia (563 cases of AD), 630 cases of dementia (435 cases of AD), and 883 cases of CIND, respectively. Adjustments were made for gender, education, lifestyle factors, comorbid diseases, and vascular risk factors. RESULTS: Lower risks for AD and all-cause dementia were significantly associated with the use of any NSAIDs and the salicylates without barbiturates subgroup in the study sample including subjects with CIND at baseline. There was a weak association between any NSAIDs and the risk of CIND (hazard ratio, 0.87; 95% confidence interval, 0.76-1.00). CONCLUSION: These results suggest that there is an association between NSAID use and a lower incidence of AD and, to a lesser extent, of CIND.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.246
Teacher spread0.225 · 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

Citations123
Published2012
Admission routes2
Has abstractyes

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