Seizures following cervical laminectomy and lateral mass fusion: case report and review of the literature
Bibliographic record
Abstract
Incidental durotomy can occur as a complication of spine surgery, which may potentially result in serious intracranial complications. We report a case of a 72 years old male with significant cervical spinal stenosis from C3 to C5 with spinal cord myelomalacia who underwent a posterior cervical decompression with instrumentation and fusion from C3-C5. An incidental dural tear was encountered during the surgery, with a sudden gush of cerebrospinal fluid (CSF) managed intraoperatively. Unfortunately, he developed generalized tonic-clonic seizures subsequently in the immediate post-operative period. Computerized tomography (CT) scan was urgently done which revealed intracranial pneumocephalus, subarachnoid hemorrhage and a right acute subdural hematoma. This case illustrates the intracranial hemorrhage potential subsequent to iatrogenic dural tear and CSF leak manifested by generalized seizures. The repair of incidental durotomy should be done immediately to decrease the amount of CSF leak and prevent any devastating effects of intracranial hemorrhage. The mechanism of this type of bleeding, risk factors and appropriate management are discussed, along with a review of the literature.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".