Rates of cerebrospinal fluid leak and pseudomeningocele formation after posterior fossa craniotomy versus craniectomy: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Postoperative cerebrospinal fluid (CSF) leak is a major concern after posterior fossa surgery with significant clinical implications. It has been postulated that replacing the bone flap, performing a craniotomy, would reinforce the surgical closure and decrease rates of CSF leak. This systematic review and meta-analysis compared the rate of CSF leak after posterior fossa craniotomies versus craniectomies. Methods: Three databases were searched for English studies comparing the primary outcome, rate of CSF leak, after adult posterior fossa craniotomies versus craniectomies. Secondary outcomes included the rate of postoperative pseudomeningocele formation, CSF leak and pseudomeningocele formation, CSF diversion, revision surgery, and infection. Pooled estimates and relative risks for dichotomous outcomes were calculated using Review Manager 5.4, with corresponding 95% confidence intervals (CIs). Results: A total of 1250 patients (635 craniotomies and 615 craniectomies), from nine studies, were included in the final analysis. Even though rates of CSF leak favored craniotomies, the difference did not reach statistical significance in our pooled analysis (Risk Ratio: 0.71, 95% Confidence Interval: 0.45-1.14, p-value = 0.15, Heterogeneity I-squared = 0%). On the other hand, comparing the rates of pseudomeningocele formation and CSF leak, as a combined outcome, or pseudomeningocele formation only showed a significant difference favoring craniotomies. The quality of evidence in this meta-analysis was graded as having a high risk of bias based on the risk of bias in non-randomized studies - of exposure criteria. Conclusion: Based on evidence with high risk of bias, rates of postoperative CSF leak and pseudomeningocele formation favored posterior fossa craniotomies over craniectomies. Further research with more robust methodology is required to validate these findings.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 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".