Antiseizure Medications in Adult Patients With Traumatic Brain Injury: A Systematic Review and Bayesian Network Meta-Analysis
Bibliographic record
Abstract
OBJECTIVES: We sought to evaluate the effectiveness of any antiseizure medication on the incidence of early post-traumatic seizures among adult patients with traumatic brain injury. DATA SOURCES: MEDLINE, Embase, PubMed, Cochrane Central Register of Controlled Trials, and LILACS were searched from inception to October 2023. STUDY SELECTION: We included randomized trials of adult patients with traumatic brain injury evaluating any antiseizure medication compared with either placebo or another agent. DATA EXTRACTION: Two reviewers independently extracted individual study data and evaluated studies for risk of bias using the Cochrane Risk of Bias tool. Our main outcome of interest was the occurrence of early seizures (i.e., within 7 d); secondary outcomes included late-seizures and all-cause mortality. DATA SYNTHESIS: Bayesian network meta-analyses were used to derive risk ratios (RRs) alongside 95% credible intervals (CrIs). We used Grading of Recommendations Assessment, Development, and Evaluation methodology to rate the certainty in our findings. Overall, ten individual randomized controlled trials (1851 participants) were included. Compared with placebo, phenytoin (RR, 0.28; 95% CrI, 0.13-0.57; moderate certainty) and levetiracetam (RR, 0.20; 95% CrI, 0.07-0.60; moderate certainty) were associated with a reduction in the risk of early seizures. Carbamazepine may be associated with a reduced risk of early seizures, but the evidence is very uncertain (RR, 0.41; 95% CrI, 0.12-1.27; very low certainty). Valproic acid may result in little to no difference in the risk of early seizures, but the evidence is very uncertain (RR, 0.97; 95% CrI, 0.16-9.00; very low certainty). The evidence is very uncertain about the impact of any antiseizure medication on the risk of late seizures or all-cause mortality at longest reported follow-up time. CONCLUSIONS: Phenytoin or levetiracetam reduce the risk of early seizures among adult patients with traumatic brain injury. Further research is needed to evaluate required duration of therapy and long-term safety profiles.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| 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".