Lamotrigine–valproic acid combination therapy for medically refractory epilepsy
Bibliographic record
Abstract
PURPOSE: A retrospective study of lamotrigine (LTG)-valproic acid (VPA) combination therapy in medically refractory epilepsy. METHODS: Patients were identified with an adult epilepsy clinic database and were included if they had been on LTG-VPA combination therapy for at least 6 months. Patient demographics and information about epilepsy type, severity, and degree of medical intractability were obtained by retrospective chart review. The primary outcome measure was change in baseline seizure frequency, and patients were stratified into three groups: (i) seizure-free, (ii) improved (at least 50% reduction in baseline seizure frequency), and (iii) not improved. RESULTS: Thirty-five patients met all inclusion-exclusion criteria. Epilepsy type was generalized in 25 patients (71%) and partial in 10 patients (29%). Before LTG-VPA treatment, 27 of 35 (77%) experienced disabling seizures on a monthly basis, and 17 of 35 (49%) of patients had at least one disabling seizure per week. Patients had previously failed treatment with a median of five antiepileptic drugs (AEDs), alone or in combination. With LTG-VPA therapy, 18 (51.4%) remained completely seizure-free, four (11.4%) were improved, and 13 (37.1%) were unimproved. Median follow-up was 42 months. Of the 22 patients who improved, 11 had previously failed LTG and VPA monotherapy. There was no significant difference between improved and unimproved patients with respect to demographics, epilepsy type or severity, or number of previously failed AEDs. DISCUSSION: The combination of LTG and VPA should be considered in patients with medically refractory epilepsy. The effectiveness of this combination appears to be independent of epilepsy type or patient demographics.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".