P.022 Neuroimaging findings and seizure type as risk factors for adult focal drug resistant epilepsy
Bibliographic record
Abstract
Background: About 35% of patients with epilepsy may develop drug-resistant epilepsy (DRE). Identifying risk factors associated with DRE will allow us to identify earlier patients in the course of the disease. Methods: This is a case-control study nested within a cohort. Chart reviews of subjects who full fill inclusion criteria were completed. Inclusion criteria included age>18 years, focal epilepsy determined by clinical correlation and EEG. DRE was determined by ILAE criteria. Results: 149 subjects were included. Seventy had DRE (cases), and seventy-nine did not have DRE (controls). DRE group had a mean age of 41 years (SD+14.8) compared to the control group (49+17.5) (p=0.003). DRE group had a mean age at diagnosis of epilepsy of 19+15.3 compared to the control group with a mean of 33.6+21. (p=<0.001). The main risk factors identified in this study were; cortical dysplasia OR 8.67 (CI 1.04-72.3, p=0.026); mesial temporal sclerosis (MTS) (OR 2.69; CI 1.12-6.47; p=0.024); and presence of complex partial seizures (OR 2.04. Conclusions: Young age at diagnosis of focal epilepsy, diagnosis of cortical dysplasia, MTS, and presence of complex partial seizures are risk factors for DRE
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".