Multiple Supra- and Infratentorial Intraparenchymal Hemorrhages Presenting With Seizure After Massive Sacral Cerebrospinal Fluid Drainage
Bibliographic record
Abstract
In Brief Study Design. Case report and review of the literature. Objective. To describe a case of multiple supra- and infratentorial hemorrhages after spinal surgery presenting with seizure. Summary of Background Data. Cerebrospinal fluid overdrainage is a well-documented factor associated with remote cerebellar hemorrhage, but supratentorial hemorrhages after spinal surgery have been reported rarely. Methods. A 64-year-old woman underwent a sacral laminectomy for recurrent chordoma. A negative pressure wound drain was left in after surgery and drained 1300 mL in the first 48 hours. On the fourth postoperative day, the patient presented with tonic-clonic seizures. Results. Diagnostic imaging showed multiple supra- and infratentorial intraparenchymal hemorrhages and a massive sacral cerebrospinal fluid leak. The patient underwent emergent surgery for a primary repair of the presumed dural defect. Conclusion. Patients who present with severe positional headache, altered mental status, or tonic-clonic seizures after undergoing intradural spinal procedures involving massive cerebrospinal fluid loss may be suffering from multiple supra- and infratentorial intracranial hemorrhages. We present a case report and literature review of a very rare case of multiple supra- and infratentorial hemorrhages after spinal surgery presenting with seizure. We discuss the incidence and proposed pathophysiologic mechanisms of this phenomenon and explain why this phenomenon must be included in the differential diagnosis of altered mental status after spinal surgery cases with large cerebrospinal fluid loss.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".