Cerebrospinal Fluid Leak During Cervical Corpectomy for Ossified Posterior Longitudinal Ligament
Bibliographic record
Abstract
In Brief Study Design. Retrospective. Objective. To study the incidence of intraoperative cerebrospinal fluid (CSF) leak in patients with ossified posterior longitudinal ligament (OPLL) undergoing central cervical corpectomy (CC) and to describe a reliable technique for treating the leak after CC. Summary of Background Data. The rate of dural tear after CC is higher in patients with OPLL compared to other causes of cervical spinal stenosis. Various techniques have been described to deal with dural tears with CSF leak in OPLL. We assessed the efficacy of the repair technique used to deal with this complication in our patients with OPLL who had undergone CC. Methods. A retrospective study was performed of all patients diagnosed with OPLL (n = 144) who had undergone CC between July 1992 and June 2007 (15 years). The dural defect was repaired with an onlay graft of crushed muscle/fascia and a layer of gelatin sponge. Bed rest and a lumbar subarachnoid drain were used for 5 days after surgery. Results. Intraoperative CSF leak was noted in 9 patients (6.3%). The dural defects ranged in size from a few mm to about 15 mm (10–75 mm2). All patients had a successful repair with no patient requiring reoperation for the CSF leak. Conclusion. Intraoperative CSF leak was encountered in 6.3% of patients undergoing CC for OPLL. A successful repair was achieved using fascial graft, gelatin sponge, lumbar CSF drainage, and bed rest. In our experience of 144 patients with ossified posterior longitudinal ligament, there was a 6.3% incidence of dural tear with cerebrospinal fluid leak, after central corpectomy. A simple technique of placing an onlay fascial graft, gelatin sponge, and lumbar cerebrospinal fluid drainage resulted in a successful repair in all patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".