Residual and Recurrent Spinal Cord Cavernous Malformations: Outcomes and Techniques to Optimize Resection and a Systematic Review of the Literature
Bibliographic record
Abstract
BACKGROUND: Intramedullary spinal cord cavernous malformations (SCCMs) account for only 5% of overall cavernous malformations (CMs). The occurrence of recurrent or residual SCCMs has not been well discussed, nor have the technical nuances of resection. OBJECTIVE: To assess the characteristics of residual SCCMs and surgical outcomes and describe the techniques to avoid leaving lesion remnants during primary resection. METHODS: Demographic, radiologic, intraoperative findings and surgical outcomes data for a cohort of surgically managed intramedullary SCCMs were obtained from an institutional database and retrospectively analyzed. A systematic literature review was performed using PRISMA guidelines. RESULTS: Of 146 SCCM resections identified, 17 were for residual lesions (12%). Patients with residuals included 13 men and 4 women, with a mean age of 43 years (range 16-70). All patients with residual SCCMs had symptomatic presentations: sensory deficits, paraparesis, spasticity, and pain. Residuals occurred between 3 and 264 months after initial resection. Approaches for 136 cases included posterior midline myelotomy (28.7%, n = 39), pial surface entry (37.5%, n = 51), dorsal root entry zone (27.9%, n = 38), and lateral entry (5.9%, n = 8). Follow-up outcomes were similar for patients with primary and residual lesions, with the majority having no change in modified Rankin Scale score (63% [59/93] vs 75% [9/12], respectively, P = .98). CONCLUSION: SCCMs may cause significant symptoms. During primary resection, care should be taken to avoid leaving residual lesion remnants, which can lead to future hemorrhagic events and neurological morbidity. However, satisfactory results are achievable even with secondary or tertiary resections.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.024 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".