Successful spinal cord stimulation using fast-acting sub-perception therapy for postoperative neuropathic pain of syringomyelia with Chiari malformation type 1: a case report and literature review
Bibliographic record
Abstract
BACKGROUND: Central neuropathic pain after foramen magnum decompression (FMD) for Chiari malformation type 1 (CM-1) with syringomyelia can be residual and refractory. Here we present a case of refractory central neuropathic pain after FMD in a CM-1 patient with syringomyelia who achieved improvements in pain following spinal cord stimulation (SCS) using fast-acting sub-perception therapy (FAST™). CASE PRESENTATION: A 76-year-old woman presented with a history of several years of bilateral upper extremity and chest-back pain. CM-1 and syringomyelia were diagnosed. The pain proved drug resistant, so FMD was performed for pain relief. After FMD, magnetic resonance imaging showed shrinkage of the syrinx. Pain was relieved, but bilateral finger, upper arm and thoracic back pain flared-up 10 months later. Due to pharmacotherapy resistance, SCS was planned for the purpose of improving pain. A percutaneous trial of SCS showed no improvement of pain with conventional SCS alone or in combination with Contour™, but the combination of FAST™ and Contour™ did improve pain. Three years after FMD, percutaneous leads and an implantable pulse generator were implanted. The program was set to FAST™ and Contour™. After implantation, pain as assessed using the McGill Pain Questionnaire and visual analog scale was relieved even after reducing dosages of analgesic. No adverse events were encountered. CONCLUSION: Percutaneously implanted SCS using FAST™ may be effective for refractory pain after FMD for CM-1 with syringomyelia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".