One Versus Double Burr Holes for Treating Chronic Subdural Hematoma Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE AND DESIGN: There is controversy among neurosurgeons regarding whether double burr hole craniostomy (DBHC) is better than single burr hole craniostomy (SBHC) in the treatment of chronic subdural hematoma (CSH), in terms of having a lower revision rate. In order to compare the revision rates after SBHC versus DBHC, we performed a meta-analysis of the available studies in the literature. MATERIALS AND METHODS: Multiple electronic health databases were searched to identify all the studies published between 1966 and December 2010 that compared SBHC and DBHC. Data were processed in Review Manager 5.0.18. Effect sizes were expressed in pooled odds ratio (OR) estimates, and due to heterogeneity between studies we used random effect of the inverse variance weighted method to perform the meta-analysis. RESULTS: Five observational retrospective cohort studies were identified: four published studies and one unpublished, describing the outcomes of 355 DBHC and 358 SBHC to evacuate 713 CSH in 631 patients. Meta-analysis showed that there was no significant difference in the revision rates between double burr hole craniostomy and single burr hole craniostomy when performed to evacuate CSH. Pooled odds ratio for all the studies was 0.62 (95% confidence interval 0.26 - 1.46). CONCLUSIONS: The results of this meta-analysis suggest that SBHC is as good as DBHC in evacuating chronic subdural hematoma and is not associated with a higher revision rate compared to DBHC.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.052 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".