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Record W2077589574 · doi:10.1212/wnl.0b013e3181f96253

Statin use and risk of epilepsy

2010· article· en· W2077589574 on OpenAlexaffabout
Mahyar Etminan, Ali Samii, James M. Brophy

Bibliographic record

VenueNeurology · 2010
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsVancouver Coastal Health
Fundersnot available
KeywordsMedicineNested case-control studyInternal medicineCohortStatinCohort studyEpilepsyConfoundingConfidence intervalPropensity score matchingPopulationLogistic regressionRelative riskPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the potential efficacy of hydroxymethyl-glutaryl-coenzyme A reductase inhibitors (statins) in the prevention of epilepsy. METHODS: This study was a population-based, nested case-control study among older adults in the province of Quebec, Canada. The primary cohort consisted of cardiovascular patients who had received a revascularization procedure. Within the cohort, those with the primary hospital diagnosis of epilepsy were identified (cases). Each case was matched to 10 controls by age and cohort entry time. Potential confounders were adjusted using a conditional logistic regression model. A sensitivity analysis was performed using propensity score matching. RESULTS: The initial cohort consisted of 150,555 subjects. Within the cohort, 217 hospital-diagnosed cases of epilepsy and 2,170 corresponding controls were identified. The adjusted rate ratio (ARR) for epilepsy among current statin users was 0.65 (95% confidence interval [CI] 0.46-0.92). The ARR for past users of statins was 0.72 (95% CI 0.39-1.30). No benefit was found for the control drug groups, including nonstatin cholesterol-lowering drugs, β-blockers, and angiotensin-converting enzyme inhibitors (1.00 [95% CI 0.45-2.20], 1.04 [95% CI 0.74-1.47], and 0.94 [95% CI 0.66-1.33]). CONCLUSIONS: These results suggest that statin use decreases the risk of hospitalization for epilepsy. Because of its observational nature, this study requires future research to confirm these intriguing findings.

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 score0.007
Threshold uncertainty score0.148

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 studies0.0000.000
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 head0.019
GPT teacher head0.294
Teacher spread0.274 · 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

Citations89
Published2010
Admission routes2
Has abstractyes

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