Collagen matrix duraplasty for cranial and spinal surgery: a clinical and imaging study
Bibliographic record
Abstract
OBJECT: The repair of dural defects is controversial in contemporary neurosurgery. To date, collagen-based products remain a continued area of interest in the development of dural grafts. The authors conducted a prospective case-control study in which they evaluated collagen matrix in the repair of dural defects following cranial and spinal surgery by using specific clinical and magnetic resonance (MR) imaging outcome measures. METHODS: Enrolled in the study were 79 patients, 36 male (45.6%) and 43 female (54.4%), with a mean age of 53 +/- 15.8 years. The pathological diagnosis was brain tumor in 49 cases (62%), vascular conditions in 16 (20.2%), degenerative spine in 10 (12.7%), trauma in two (2.5%), and other in two (2.5%). Most of the patients underwent supratentorial craniotomy (57; 72.2%), whereas 11 patients (13.9%) each underwent posterior fossa and spinal surgery. Sixty-three patients (79.7%) completed the study, which included clinical and MR imaging evaluations at 3 months postsurgery. There were no cerebrospinal fluid (CSF) leaks or delayed hemorrhages. The neurosurgical wound infection rate was 3.8%: superficial wound infection in two cases and deep infection and brain abscess in one case (recurrent brain tumor following radiation therapy). Among the 63 patients in whom 3-month postsurgery imaging data were available, asymptomatic small pseudomeningoceles were detected on MR imaging in two (3.2%); a minor subgaleal fluid collection, which resolved spontaneously, was apparent in another patient (1.6%). Nonspecific dural enhancement was demonstrated on images obtained in seven patients (11.1%), and asymptomatic spinal epidural enhancement was observed on images obtained in two of three patients who had undergone lumbar laminectomy for spinal stenosis. CONCLUSIONS: When used as a dural onlay graft, collagen matrix had a 100% CSF containment rate but might be associated with occult radiological abnormalities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".