Comparison of Spinal Cord Stimulation vs. Dorsal Root Ganglion Stimulation vs. Association of Both in Patients with Refractory Chronic Back and/or Lower Limb Neuropathic Pain: An International, Prospective, Randomized, Double-Blinded, Crossover Trial (BOOST-DRG Study)
Bibliographic record
Abstract
While spinal cord stimulation (SCS) is a well-established therapy to address refractory persistent spinal pain syndrome after spinal surgery (PSPS-T2), its lack of spatial selectivity and reported discomfort due to positional effects can be considered as significant limitations. As alternatives, new waveforms, such as burst stimulation and different spatial neural targets, such as dorsal root ganglion stimulation (DRGS), have shown promising results. Comparisons between DRGS and standard SCS, or their combination, have never been studied on the same patients. "BOOST DRG" is the first prospective, randomized, double-blinded, crossover study to compare SCS vs. DRGS vs. SCS+DRGS. Sixty-six PSPS-T2 patients will be recruited internationally in three centers. Before crossing over, patients will receive each stimulation modality for 1 month, using tonic conventional stimulation. After 3 months, stimulation will consist in switching to burst for 1 month, and patients will choose which modality/waveform they receive and will then be reassessed at 6 and 12 months. In addition to our primary outcome based on pain rating, this study is designed to assess quality of life, functional disability, psychological distress, pain surface coverage, global impression of change, medication quantification, adverse events, brain functional imaging and electroencephalography, with the objective being to provide a multidimensional insight based on composite pain assessment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".