Movement Disorders Secondary to Novel Antiseizure Medications in Pediatric Populations: A Systematic Review and Meta-analysis of Risk
Bibliographic record
Abstract
Novel antiseizure medications are thought to be safer than their conventional counterparts, though no dedicated analysis of movement disorder risk among pediatric populations using novel antiseizure medications has been completed. We report a systematic review with meta-analysis describing the relationship between novel antiseizure medications and movement disorders in pediatrics.MEDLINE, EMBASE, and the World Health Organization's International Clinical Trials Registry Platform were searched up to October 2020 for randomized controlled trials investigating novel antiseizure medications in pediatric populations. Antiseizure medications included lacosamide, perampanel, eslicarbazepine, rufinamide, fenfluramine, cannabidiol, and brivaracetam. Outcomes were pooled using random effects models; risk difference (RD) and 95% confidence intervals (CIs) were calculated.Twenty-three studies were selected from 1690 nonredundant manuscripts (n = 1912 total). There was a significantly increased risk of movement disorders associated with perampanel (RD 0.07, 95% CI 0.01-0.13; n = 133), though only 1 relevant trial was found. No increased risk of movement disorders was found with other antiseizure medications.Our findings indicate most novel antiseizure medications are safe to use in pediatric populations with respect to movement disorders. However, findings were limited by quality of adverse event reporting.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.030 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".