10‐kHz Spinal Cord Stimulation for Chronic Postsurgical Pain: Results From a 12‐Month Prospective, Multicenter Study
Bibliographic record
Abstract
BACKGROUND: Chronic postsurgical pain (CPSP) can be caused by peripheral nerve injury (PNI) resulting from surgical procedures and has a significant neuropathic component. This prospective, single-arm study was conducted to document the effectiveness of 10-kHz spinal cord stimulation (10-kHz SCS) as a treatment for patients with CPSP. METHODS: Subjects with CPSP who were refractory to conventional medical interventions and reported pain scores of ≥5 cm on a 10-cm VAS underwent trial stimulations lasting up to 14 days. Epidural leads were implanted at locations appropriate for the primary area of pain, and trials resulting in ≥40% pain relief were considered successful. Subjects with successful trials underwent implantation with a permanent 10-kHz SCS system and were followed for 12 months after implantation. RESULTS: Of the 34 subjects who underwent trial stimulation, 1 was withdrawn early and 29 (87.9%) had a successful trial and received a permanent implant. After 12 months of treatment, the mean VAS score decreased by 6.5 cm, the response rate was 88.0% (22/25), and 18 subjects (62.1%) were remitters with VAS scores sustained at ≤3.0 cm. Scores for all components of the short-form McGill Pain Questionnaire 2 were significantly reduced, including affective descriptors of pain. Pain catastrophizing and vigilance, patient function, physical and mental well-being, and sleep quality all improved over the course of the study. No neurologic deficits reported in the study. CONCLUSIONS: 10-kHz SCS is effective and tolerated in patients with CPSP, and further study of its clinical application in this population is warranted.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".