Spontaneous Spinal Epidural Hematoma: Report of Two Cases and Literature Review
Bibliographic record
Abstract
Spontaneous spinal epidural hematoma (SSEH) is a rare disease but may lead to life-threatening consequences if not timely diagnosed and managed. Emergent hematoma evacuation is indicated before neurological deficits become irreversible. We report two cases. The first case was a 45-year-old man brought to hospital because of an acute onset of quadriparesis and urinary incontinence. His cervical magnetic resonance imaging (MRI) showed an epidural hematoma at the C5-C6 level with severe spinal cord compression. He underwent an emergency C5-C6 right hemi-laminotomy to remove the clot and decompress the cord. Postoperatively, his left-sided deficits immediately resolved. His urinary function returned to normal two weeks after the surgery. He could independently walk two months later. The second case was a 57-year-old man admitted to the hospital because of severe neck pain and paresthesia in both arms. He had been using an antiplatelet for two months. His MRI revealed an epidural hematoma from C2 to C4 with spinal cord compression on the right. This patient was successfully treated with conservative treatment. If SSEH is left undiagnosed and untreated, the neurological deficits may be permanent. Early emergent hematoma evacuation contributes to a favorable outcome. Conservative management is reasonable if neurological deficits are not severe.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".