Cervical Spinal Cord and Dorsal Nerve Root Stimulation for Neuropathic Upper Limb Pain
Bibliographic record
Abstract
BACKGROUND: Spinal cord stimulation (SCS) is a well-established treatment for chronic neuropathic pain in the lower limbs. Upper limb pain comprises a significant proportion of neuropathic pain patients, but is often difficult to target specifically and consistently with paresthesias. We hypothesized that the use of dorsal nerve root stimulation (DNRS), as an option along with SCS, would help us better relieve pain in these patients. METHODS: All 35 patients trialed with spinal stimulation for upper limb pain between July 1, 2011, and October 31, 2013, were included. We performed permanent implantation in 23/35 patients based on a visual analogue scale pain score decrease of ≥50% during trial stimulation. RESULTS: Both the SCS and DNRS groups had significant improvements in average visual analogue scale pain scores at 12 months compared with baseline, and the majority of patients in both groups obtained ≥50% pain relief. The majority of patients in both groups were able to reduce their opioid use, and on average had improvements in Short Form-36 quality of life scores. Complication rates did not differ significantly between the two groups. CONCLUSIONS: Treatment with SCS or DNRS provides meaningful long-term relief of chronic neuropathic pain in the upper limbs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".