Meta-Analysis of Randomized Trials on First Line and Adjunctive Levetiracetam
Bibliographic record
Abstract
CONTEXT: New evidence suggests that levetiracetam may be as effective as traditional agents, with better safety profile. OBJECTIVE: To synthesize evidence regarding efficacy and tolerability of levetiracetam as first line, adjunctive or prophylactic antiepileptic agent. Study Selection & Data Extraction: Eligible studies were randomized controlled trials (RCTs) of levetiracetam used in adults with epilepsy. MEDLINE, EMBASE, CENTRAL, CINHAL, PAPERSFIRST, PROCEEDINGSFIRST, PROQUEST and conference proceedings identified studies (to September 30, 2010). Two investigators independently selected, appraised studies, collected and analyzed data. RESULTS: Of ten eligible randomized trials, eight investigated adjunctive levetiracetam for refractory seizures, one as monotherapy for newly diagnosed seizures, one as monotherapy for prophylaxis. Eight RCTs of adjunctive levetiracetam were of moderate quality (GRADE criteria), with two showing lack of allocation concealment. Meta-analyses showed adjunctive levetiracetam was more effective than placebo in achieving at least 50% reduction of seizure frequency, when added to baseline antiepileptic regimen (pooled RR 2.15 [1.65,2.82], I2 = 45%, p value (heterogeneity) = 0.08, p value (overall effect) < 0.01). Likelihood of serious adverse events necessitating withdrawal from study was not significantly different between levetiracetam and control (pooled RR 1.37 [0.88,2.13], I2 = 0%, p value (heterogeneity) = 0.84, p value (overall effect) = 0.17). Subgroup analyses suggested similar effects across different dosages. Sensitivity analysis of studies with adequate concealment showed similar effects. CONCLUSIONS: Levetiracetam is an effective adjunctive agent for refractory epilepsy. More studies are needed to establish whether it is effective as monotherapy for newly diagnosed seizures, and for prophylaxis in traumatic brain injury.
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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 | 0.043 | 0.106 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.034 | 0.076 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".