Definitions and Risk Factors for Drug-Resistant Epilepsy in an Adult Cohort
Bibliographic record
Abstract
Background: Less than one-third of people with epilepsy will develop drug-resistant epilepsy (DRE). Establishing the prognosis of each unique epilepsy case is an important part of evaluation and treatment.Most studies on DRE prognosis have been based on a pooled, heterogeneous group, including children, adults, and older adults, in the absence of clear recognition and control of important confounders, such as age group. Furthermore, previous studies were done before the 2010 definition of DRE by the International League Against Epilepsy (ILAE), so data based on the current definitions have not been entirely elucidated. This study aimed to explore the difference between 3 definitions of DRE and clinical predictors of DRE in adults and older adults. Methods: Patients with a new diagnosis of epilepsy ascertained at a Single Seizure Clinic (SSC) in Saskatchewan, Canada were included if they had at least 1 year of follow-up. The first study outcome was the diagnosis of DRE epilepsy at follow-up using the 2010 ILAE definition. This was compared with 2 alternative definitions of DRE by Kwan and Brodie and Camfield and Camfield. Finally, risk factors were analyzed using the ILAE definition. Results: In total, 95 patients with a new diagnosis of epilepsy and a median follow-up of 24 months were included. The median age of patients at the diagnosis of epilepsy was 33 years, and 51% were men. In the cohort, 32% of patients were diagnosed with DRE by the Kwan and Brodie definition, 10% by Camfield and Camfield definition, and 15% by the ILAE definition by the end of follow-up. The only statistically significant risk factor for DRE development was the failure to respond to the first anti-seizure medication (ASM). Conclusion: There were important differences in the percentage of patients diagnosed with DRE when using 3 concurrent definitions. However, the use of the ILAE definition appeared to be the most consistent through an extended follow-up. Finally, failure to respond to the first ASM was the sole significant risk factor for DRE in the cohort after considering the age group.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".