Risk Factors Associated With Seizure After Treatment of Chronic Subdural Hemorrhage: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Chronic subdural hemorrhage (cSDH) is a prevalent neurosurgical pathology, marked by blood collection between the dura mater and the arachnoid membrane. The aim of this systematic review was to provide a comprehensive overview of the risk factors associated with seizures after cSDH treatment. METHODS: We systematically searched the following databases for studies conducted until September 28, 2023: PubMed, Embase, SCOPUS, Cochrane Central, WOS, and EBSCO. We selected all studies aiming to assess risk factors associated with seizures after treatment of cSDH. Observation studies written in English, Spanish, and Portuguese were included. The quality of studies was assessed using the Newcastle-Ottawa scale for observational studies. RESULTS: A total of 1830 studies were screened after the elimination of duplicates. A total of 18 studies were included, representing 4966 patients. The pooled proportion of seizures after treatment of cSDH is 10% [95% CI 7%, 13%; I 2 = 93%]. The risk of seizures was lower in patients undergoing burr hole surgery compared to craniotomy, with an odds ratio of 0.23 (95% CI [0.10, 0.55]; I 2 = 0%). Additionally, the risk of seizures in patients receiving prophylactic antiepileptic treatment compared to those without was higher, with an odds ratio of 2.62 (95% CI [0.53, 13.06]; I 2 = 66%). CONCLUSION: Burr-hole treatment after cSDH presents a lower risk of seizures compared with craniotomy, and the use of prophylactic antiepileptic treatment did not conclusively affect seizure outcomes. Standardization in the reporting of outcomes and more comparative studies are needed to enable better recognition of risk factors of seizures after cSDH treatment.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".