A scoping review of novel spinal cord stimulation modes for complex regional pain syndrome
Bibliographic record
Abstract
Background Paresthesia-based spinal cord stimulation (PB-SCS) is used for the treatment of complex regional pain syndrome (CRPS), but many patients are refractory to PB-SCS or experience attenuation of analgesic effect over time due to tolerance. Novel SCS modes including high-frequency, BurstTM, and high-density (HDTM) stimulation were introduced recently and this systematic review was conducted to summarize the evidence on their role for CRPS.Materials and Methods We searched MEDLINE and other databases (up to September 21, 2017) for studies including adults with refractory CRPS treated by paresthesia-free SCS (PF-SCS) modes compared to placebo, conventional medical treatment, or PB-SCS. We determined the posttreatment intensity of pain (up to 24 months after intervention), changes in CRPS-associated symptoms, and associated domains. Sustainability and adverse effects were also assessed.Results We identified 13 studies (seven case series, five conference abstracts, one randomized controlled trial) including 62 patients with upper or lower limb CRPS. Eleven papers reported on outcomes of high-frequency stimulation at 10 kHz (HF-10) and other high frequencies, two papers were on Burst, and one paper was on HD. In 59 patients, pain intensity with novel SCS modes was reduced by 30% to 100% with a corresponding reduction in analgesic medications. Novel SCS modes also attenuated CRPS-associated symptoms and six papers reported significant improvement of quality of life.Conclusions Novel SCS modes have the potential to provide analgesia in patients with CRPS. However, the low quality of available evidence necessitates definitive and prospective comparative effectiveness studies to establish the role of these modes in CRPS.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".