Use of duraseal in repair of cerebrospinal fluid leaks.
Bibliographic record
Abstract
OBJECTIVE: The purpose of our article is to review the use of the DuraSeal Sealant System (Confluent Surgical Inc., Waltham, MA) in the repair of complex cerebrospinal fluid (CSF) leaks in endoscopic skull-base surgery. DESIGN: Retrospective chart review. SETTING: London Health Sciences Centre. METHODS: A database of endoscopic skull-base cases between 2007 and 2009 that involved CSF leakage repaired with DuraSeal was created. Demographic data and operative reports were collected and analyzed qualitatively. MAIN OUTCOME MEASURES: Recurrence of CSF leak after repair. RESULTS: Five cases were identified that met study criteria. In four of the five cases, the repair was successful. There were no complications related to DuraSeal use. Comparison to a subset of patients using Tisseel Fibrin Sealant (Baxter, Toronto, ON) for repair did not show a significant difference in failure rate (χ2 = 0.029, p = .858). CONCLUSIONS: There are a variety of techniques described to repair CSF rhinorrhea, with various studies demonstrating the advantages of using tissue glues in CSF leak repairs. We used DuraSeal in five patients to enhance graft strength and form a watertight seal. The system was effective in the majority of patients. Our study is the first to report on endoscopic endonasal repair of CSF leaks using DuraSeal.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".