Effects of Tonic Spinal Cord Stimulation on External Mechanical and Thermal Stimuli Perception Using Quantitative Sensory Testing
Bibliographic record
Abstract
OBJECTIVES: Tonic spinal cord stimulation (SCS) is currently used to treat neuropathic pain. With this type of stimulation, an implantable pulse generator generates electrical paresthesias in the affected area through 1 or more epidural leads. The goal of this study was to evaluate the impact of tonic SCS on the sensory perception of chronic pain patients using quantitative sensory testing (QST). MATERIALS AND METHODS: Forty-eight patients (mean age: 57 y) with chronic leg pain due to failed back surgery syndrome or complex regional pain syndrome treated with SCS were recruited from 3 research centers. Test procedures included 2 sessions (stimulation On or Off), with measures of detection thresholds for heat, touch, vibration, and of pain thresholds for cold, heat, pressure, the assessment of dynamic mechanical allodynia, and temporal pain summation. Three different areas were examined: the most painful area of the most painful limb covered with SCS-induced paresthesias (target area), the contralateral limb, and the ipsilateral upper limb. Wilcoxon signed-rank tests were used to compare the mean difference between On and Off for each QST parameter at each area tested. P-values <0.05 were considered significant. RESULTS: Regarding the mean difference between On and Off, patients felt less touch sensation at the ipsilateral area (-0.4±0.9 g, P=0.0125) and were less sensitive at the contralateral area for temporal pain summation (-4.9±18.1 on Visual Analog Scale 0 to 100, P=0.0056) with SCS. DISCUSSION: It is not clear that the slight changes observed were clinically significant and induced any changes in patients' daily life. Globally, our results suggest that SCS does not have a significant effect on sensory perception.
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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 | 0.001 | 0.002 |
| 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) | 0.003 | 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".