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Record W2042979672 · doi:10.1159/000048621

A Case-Control Analysis of Nonsteroidal Anti-Inflammatory Drugs and Alzheimer’s Disease: Are They Protective?

2002· article· en· W2042979672 on OpenAlex
Christina Wolfson, Anne Perrault, Yola Moride, John M. Esdaile, Lucien Abenhaim, F. Momoli

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNeuroepidemiology · 2002
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsMontreal General HospitalJewish General HospitalMcGill University
Fundersnot available
KeywordsMedicineNonsteroidalDiseaseDrugMedical prescriptionDementiaInternal medicineAlzheimer's diseaseRecall biasPharmacologyPathology

Abstract

fetched live from OpenAlex

In many studies of nonsteroidal anti-inflammatory drugs (NSAIDs) and Alzheimer's disease (AD), the exposure to NSAIDs was concurrent with AD or based on self (or surrogate) report. We conducted a case-control analysis of the Québec participants in the Canadian Study of Health and Aging who received a diagnosis of AD (cases) or were found to be cognitively unimpaired on screening (controls). Information on drug use was obtained from the Québec Provincial Pharmaceutical Services Database. There was no significant difference in the proportion of cases and controls who had received any NSAID prescriptions in the 3 years prior to the onset of symptoms of dementia; amongst NSAID users, there was no difference in mean dose or duration. Our findings, using a measure of drug use prior to symptom onset and not subject to recall bias, do not support a protective effect for NSAIDs.

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.

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)0.002
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 score0.115
Threshold uncertainty score0.841

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0000.000
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 head0.043
GPT teacher head0.270
Teacher spread0.227 · 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