Spinal Cord Ependymoma: Radical Surgical Resection and Outcome
Bibliographic record
Abstract
OBJECTIVE: Several authors have noted increased neurological deficits and worsening dysesthesia in the postoperative period in patients with spinal cord ependymoma. We describe the neurological progression and pain evolution of these patients over the 1-year period after surgery. In addition, our favored method of en bloc tumor resection is illustrated, and the rate of complications, recurrence, and survival in this group of patients is addressed. METHODS: We operated on 26 patients (12 male and 14 female) with low-grade spinal cord ependymomas between 1975 and 2001. The median age at diagnosis was 42 years. Tumors extended into the cervical cord in 13 patients, the thoracic cord in 7 patients, and the conus medullaris in 6 patients. Eleven patients had previous surgery and/or radiation therapy. RESULTS: We achieved a gross total resection in 88% of patients, whereas 8% had a subtotal resection and 4% had a biopsy. Only 1 patient developed a recurrence over a mean follow-up period of 31 months. CONCLUSION: We conclude that radical surgical resection of spinal cord ependymomas can be safely achieved in the majority of patients. A trend toward neurological improvement from a postoperative deficit can be expected between 1 and 3 months after surgery and continues up to 1 year. Postoperative dysesthesias begin to improve within 1 month of surgery and are significantly better by 1 year after surgery. The best predictor of outcome is the preoperative neurological status.
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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) | 0.000 | 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 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".