Correlates of disability related to seizures in persons with epilepsy
Bibliographic record
Abstract
OBJECTIVE: Seizure-related disability is an important contributor to health-related quality of life in persons with epilepsy. Yet, there is little information on patient-centered reports of seizure-related disability, as most studies focus on specific constructs of health-related disability, rather than epilepsy. We investigated how patients rate their own disability and how these ratings correlate with various clinical and sociodemographic characteristics. METHODS: In a prospective cohort of 250 adults with epilepsy consecutively enrolled in the Neurological Disease and Depression Study (NEEDs), we obtained a broad range of clinical and patient-reported measures, including patients' ratings of seizure-related disability and epilepsy severity using self-completed, single-item, 7-point response global assessment scales. Spearman's correlation, multiple linear regression, and mediation analyses were used to examine the association between seizure-related disability scores and clinical and demographic characteristics of persons with epilepsy. RESULTS: The mean age and duration of epilepsy was 39.8 and 16.7 years, respectively. About 29.5% of the patients reported their seizures as "not at all disabling," whereas 5.8% of the patients reported them as "extremely disabling." Age, seizure freedom at 1 year, anxiety, and epilepsy severity were identified as statistically significant predictors of disability scores. The indirect effects of age and seizure freedom, attributable to mediation through epilepsy severity, accounted for 25.0% and 30.3% of the total effects of these determinants on seizure-related disability, respectively. SIGNIFICANCE: Measuring seizure-related disability has heuristic value and it has important correlates and mediators that can be targeted for intervention in practice. Addressing modifiable factors associated with disability (e.g., seizure freedom and anxiety) could have a significant impact on decreasing the burden of disability in people with epilepsy.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".