GIANT CELL EPENDYMOMA OF THE THORACIC SPINE
Bibliographic record
Abstract
UNLABELLED: INTRODUCTION AND IMPORTANCE: Spinal ependymomas are slow-growing lesions that comprise the majority of primary spinal cord neoplasms. When surgery is indicated, the extent of tumor removal is most prognostic for long-term survival. Unusual histological subtypes can make intraoperative diagnosis spurious, possibly altering the surgical approach from gross total resection for ependymomas to debulking for high-grade astrocytomas. CLINICAL PRESENTATION: We describe a 67-year-old woman with a thoracic spine intramedullary giant cell ependymoma. She presented with decreased lower extremity sensation leading to unsteadiness and an eventual fall. A physical examination revealed lower extremity hyperreflexia and ankle clonus, but no clear sensory level. Magnetic resonance imaging demonstrated an intramedullary T1 and T2 hypointense, homogenously enhancing lesion at T8 with extensive cephalad and caudal edema. INTERVENTION AND TECHNIQUE: A laminectomy at T8 to T9 afforded gross total resection of the lesion that had a clear cleavage plane with normal spinal cord. Intraoperative pathology suggested a high-grade glioblastoma, but final section showed sporadic giant cells with marked pleomorphism, uniform immunofluorescence staining with both glial fibrillary acidic protein and cluster of differentiation 99, and high MIB-1 index. Electron microscopy showed "zipper-like" junctions. There were no detected genomic abnormalities consistent with glioblastoma. CONCLUSION: We present this first reported case of thoracic spine giant cell ependymoma alongside scant literature yielding 1 case in the cervical spine and 2 cases at the filum terminale. Those cases had benign courses, whereas ours demonstrates a high degree of proliferation, making the malignant potential difficult to assess.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".