Laminoplasty for Cervical Spinal Cord Stimulator Implantation in Patients With Cervical Spondylosis and Fusion: A Technical Note
Bibliographic record
Abstract
Background: Epidural spinal cord stimulator (SCS) implantation is a commonly used strategy for treating refractory neuropathic pain, but the literature on the technical aspects of cervical SCS surgery remains scarce. Degenerative cervical stenosis and prior fusion surgery are relatively frequent conditions in this population, and the optimal method for cervical lead placement among such patients has not been established. Decompressive laminectomy may be required for cervical SCS placement in the presence of spinal stenosis. However, extensive decompression may increase the rate of lead migration and destabilize the spine, especially when performed above an existing fusion. Case Series: We present a surgical technique for cervical SCS implantation and the cases of 3 patients with significant spinal stenosis and/or prior fusion. In these patients, the paddle lead placement was safely achieved using cervical laminoplasty techniques. Conclusion: In addition to stabilizing the epidural paddle lead, laminoplasty offers several potential advantages compared to decompression alone.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".