Microsurgery Versus Embolization for Spinal Cord Arteriovenous Malformations: A Proposed Grading System
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Comparing microsurgery and embolization for spinal cord arteriovenous malformations (SCAVMs) is challenging because of the disease's rarity and the highly heterogeneous angioarchitecture. The aim of this study was to compare outcomes between microsurgery and embolization using a grading system for SCAVMs that effectively stratifies angioarchitectural complexities. METHODS: A total of 714 patients were included, with 308 undergoing microsurgery. The grading system was developed based on independent risk factors of incomplete resection, including anterior sulcal artery supply, metameric manifestations, the maximum diameter of lesion, and lesion depth. Each parameter was assigned one point, stratifying angioarchitectural complexities of SCAVMs into five grades. RESULTS: Microsurgery carried significantly higher treatment risks than embolization across all grades. For patients scoring 0 to 2 points, microsurgery achieved significantly higher complete obliteration rates than embolization. For patients scoring 3 or 4 points, the complete obliteration rates between the two methods were similar. Long-term clinical deterioration after microsurgery was significantly more frequent after embolization for patients scoring 1; for patients scoring 0, the higher long-term deterioration rate after embolization was also observed, but not statistically significant; for patients scoring 2 to 4 points, risks of long-term clinical deterioration between the two methods were comparable. At the last follow-up, the rate of poor prognosis was similar between the two methods for patients scoring 0 points. For the remaining groups, microsurgery showed a worse prognosis. CONCLUSION: Embolization should be the primary treatment option for patients with SCAVMs; however, microsurgery should be considered as an alternative for patients scoring 0 or 1 point if endovascular treatment fails to achieve complete obliteration.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".