Collagen matrix duraplasty for posterior fossa surgery: evaluation of surgical technique in 52 adult patients
Bibliographic record
Abstract
OBJECT: Complete dural closure is not always possible following posterior fossa surgery, often requiring a graft to secure complete closure. The authors report their experience of using a collagen matrix as an onlay dural graft for repair of a posterior fossa dural defect. METHODS: A retrospective analysis was performed in 52 adult patients who had undergone collagen matrix duraplasty for the posterior fossa. Complications directly related to the dural graft, the presence or absence of hydrocephalus, and the role of closed suction wound drainage in relation to postsurgical pseudomeningoceles were analyzed. RESULTS: The indication for posterior fossa surgery was tumors in 32 patients, vascular abnormalities in 9 patients, and spontaneous cerebellar hemorrhage in 11 patients. Closed suction wound drainage was used in 23 patients (44.2%). Forty-eight (92.3%) of 52 patients had a dural defect > 2 cm. Nine (81.8%) of 11 patients with hydrocephalus required ventriculoperitoneal shunts. Complications of the surgery included pseudomeningoceles in 2 patients (3.8%; no closed suction wound drainage); superficial wound infections in 1 patient (1.9%; with closed suction wound drainage); and unexplained eosinophilia in 1 patient. CONCLUSIONS: Duraplasty using a collagen matrix is safe and effective in the posterior fossa, and is easy to use and time efficient. Meticulous layered wound closure, the detection and effective control of hydrocephalus, and the use of closed suction wound drainage reduces complications related to collagen matrix duraplasty for the posterior fossa.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".