The impact of seizures on epilepsy outcomes: A national, community‐based survey
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to examine the impact of seizures on persons living with epilepsy in a national, community-based setting. METHODS: The data source was the Survey of Living with Neurological Conditions in Canada (SLNCC), a cohort derived from a national population-based survey of noninstitutionalized persons aged 15 or more years. Participants had to be on a seizure drug or to have had a seizure in the past 5 years to meet the definition of active epilepsy. The respondents were further stratified by seizure status: the seizure group experienced ≥1 seizure in the past 5 years versus the no seizure group who were seizure-free in the past ≥5 years regardless of medication status. Weighted overall and stratified prevalence estimates and odds ratios were used to estimate associations. RESULTS: The SLNCC included 713 persons with epilepsy with a mean age of 45.4 (standard deviation 18.0) years. Fewer people in the seizure group (42.7%) reported being much better than a year ago versus those in the no seizure group (70.1%). Of those with seizures, 32.1% (95% confidence interval [95% CI] 18.8-45.3) had symptoms suggestive of major depression (as per the Patient Health Questionnaire-9) compared to 7.7% (95% CI 3.4-11.9) of those without seizures. Driving, educational, and work opportunities were also significantly limited, whereas stigma was significantly greater in those with seizures. SIGNIFICANCE: This community-based study emphasizes the need for seizure freedom to improve clinical and psychosocial outcomes in persons with epilepsy. Seizure freedom has an important influence on overall health, as those with at least one seizure over the prior 5 years had an increased risk of mood disorders, worse quality of life, and faced significantly more stigma.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".