Antiseizure Medications and Cardiovascular Events in Older People With Epilepsy in the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
Importance: How epilepsy may promote cardiovascular disease remains poorly understood. Objective: To estimate the odds of new-onset cardiovascular events (CVEs) over 6 years in older people with vs without epilepsy, exploring how enzyme-inducing antiseizure medications (EIASMs) and traditional cardiovascular risk factors mediate these odds. Design, Setting, and Participants: This was a prospective cohort study using the comprehensive cohort of the Canadian Longitudinal Study on Aging (CLSA), with 6 years of follow-up (2015-2021, analysis performed in December 2023). The CLSA is an ongoing, national study of 51 338 adults aged 45 to 85 years at baseline who are recruited in Canada. The comprehensive cohort includes 30 097 individuals living near 1 of 11 data collection centers. Participation in the CLSA was voluntary; participation rate was 45%. Among those in the comprehensive cohort, individuals reporting no previous history of CVEs (ie, stroke, transient ischemic attack [TIA], or myocardial infarction [MI]) at baseline were excluded. No other exclusion criteria were applied. A total of 86% of participants completed follow-up. Exposure: Lifetime history of epilepsy. Main Outcomes and Measures: The primary outcome was new-onset CVEs over 6 years. Secondary outcomes were new-onset strokes, TIAs, and MIs. Logistic models were fitted for these outcomes as a function of epilepsy, age, sex, household income, and education level. Mediation analyses were conducted for strong EIASM use, weak EIASM use, Framingham score, Physical Activity Scale for the Elderly (PASE) score, and waist to hip ratio. Results: Among the 30 097 individuals in the comprehensive cohort, a total of 27 230 individuals (mean [SD] age, 62.3 [10.1] years; 14 268 female [52.4%]) were included, 431 with a lifetime history of epilepsy. New-onset CVEs were more likely in epilepsy, with an adjusted odds ratio of 2.20 (95% CI, 1.48-3.27). The proportion of the effect of epilepsy on new-onset CVEs was mediated as follows by each of the following variables: strong EIASM use, 24.6% (95% CI, 6.5%-54.6%), weak EIASM use, 4.0% (95% CI, 0.8%-11.0%), Framingham score, 1.4% (95% CI, -1.6% to 4.5%), PASE score, 3.3% (95% CI, 1.4%-6.8%), and waist to hip ratio, 1.6% (95% CI, 0.4%-3.7%). Conclusions and Relevance: Results of this cohort study reveal that epilepsy was associated with new-onset CVEs. Nearly one-third of this association can be explained by EIASMs. These findings should be considered when choosing an antiseizure medication for a person at risk for cardiovascular disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".