KOMET: an unblinded, randomised, two parallel-group, stratified trial comparing the effectiveness of levetiracetam with controlled-release carbamazepine and extended-release sodium valproate as monotherapy in patients with newly diagnosed epilepsy
Bibliographic record
Abstract
OBJECTIVE: To compare the effectiveness of levetiracetam (LEV) with extended-release sodium valproate (VPA-ER) and controlled-release carbamazepine (CBZ-CR) as monotherapy in patients with newly diagnosed epilepsy. METHODS: This unblinded, randomised, 52-week superiority trial (NCT00175903) recruited patients (≥16 years of age) with ≥2 unprovoked seizures in the previous 2 years and ≥1 in the previous 6 months. The physician chose VPA or CBZ as preferred standard treatment; each patient was randomised to standard treatment or LEV. The primary outcome was time to treatment withdrawal (LEV vs standard antiepileptic drugs (AEDs)). Analyses also compared LEV with VPA-ER, and LEV with CBZ-CR. FINDINGS: 1688 patients (mean age 41 years; 44% female) were randomised to LEV (n=841) or standard AEDs (n=847). Time to treatment withdrawal was not significantly different between LEV and standard AEDs: HR (95% CI) 0.90 (0.74 to 1.08). Time to treatment withdrawal (HR (95% CI)) was 1.02 (0.74 to 1.41) for LEV/VPA-ER and 0.84 (0.66 to 1.07) for LEV/CBZ-CR. Time to first seizure (HR, 95% CI) was significantly longer for standard AEDs, 1.20 (1.03 to 1.39), being 1.19 (0.93 to 1.54) for LEV/VPA-ER and 1.20 (0.99 to 1.46) for LEV/CBZ-CR. Estimated 12-month seizure freedom rates from randomisation: 58.7% LEV versus 64.5% VPA-ER; 50.5% LEV versus 56.7% CBZ-CR. Similar proportions of patients within each stratum reported at least one adverse event: 66.1% LEV versus 62.0% VPA-ER; 73.4% LEV versus 72.5% CBZ-CR. CONCLUSIONS: LEV monotherapy was not superior to standard AEDs for the global outcome, namely time to treatment withdrawal, in patients with newly diagnosed focal or generalised seizures.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".