Spinal Hemangiomas
Bibliographic record
Abstract
STUDY DESIGN: Multicenter, ambispective observational study. OBJECTIVE: To quantify local recurrence and mortality rates after surgical treatment of symptomatic spinal hemangiomas and identify prognostic variables for local disease control. SUMMARY OF BACKGROUND DATA: Spinal hemangiomas are the most common primary tumors of the spine and are generally benign and usually asymptomatic. Because of the rarity of symptomatic spinal hemangiomas, optimal surgical treatment remains unclear. METHODS: AOSpine Knowledge Forum Tumor Investigators created a multicenter database of primary spinal tumors including demographics, presentation, diagnosis, treatment, survival, and recurrence data. Tumors were classified according to Enneking and Weinstein-Boriani-Biagini. Descriptive statistics were summarized and time to mortality and recurrence was determined. RESULTS: Between 1996 and 2012, 68 patients (mean age = 51 yr, SD = 16) underwent surgical treatment of a spinal hemangioma. Epidural disease was present in 55% of patients (n = 33). Pain and neurological compromise were presenting symptoms in 82% (n = 54) and 37% (n = 24) of patients, respectively. Preoperative embolization was performed in 35% of patients (n = 23), 10% (n = 7) had adjuvant radiotherapy, and 81% (n = 55) underwent posterior-alone surgery. The local recurrence rate was 3% (n = 2). Mortality secondary to spinal hemangioma was not observed (mean follow-up = 3.9 yr, SD = 3.8). CONCLUSION: This is the largest multicenter surgical cohort of spinal hemangiomas. Symptomatic spinal hemangiomas are a benign tumor despite frequently presenting with epidural disease and neurological compromise. Thus, formal en bloc resection is not required, and excellent rates of local control and long-term survival can result from aggressive intralesional resection during index surgery. LEVEL OF EVIDENCE: 3.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".