Complex Regional Pain Syndrome. A Comprehensive Review on Neuroplastic Changes Supporting the Use of Non-invasive Neurostimulation in Clinical Settings
Bibliographic record
Abstract
Background: Complex regional pain syndrome (CRPS) is a rare debilitating disorder characterized by severe pain affecting one or more limbs. CRPS presents a complex multifactorial physiopathology. The peripheral and sensorimotor abnormalities reflect maladaptive changes of the central nervous system. These changes of volume, connectivity, activation, metabolism, etc., could be the keys to understand chronicization, refractoriness to conventional treatment, and developing more efficient treatments. Objective: This review discusses the use of non-pharmacological, non-invasive neurostimulation techniques in CRPS, with regard to the CRPS physiopathology, brain changes underlying chronicization, conventional approaches to treat CRPS, current evidence, and mechanisms of action of peripheral and brain stimulation. Conclusion: Future work is warranted to foster the evidence of the efficacy of non-invasive neurostimulation in CRPS. It seems that the approach has to be individualized owing to the integrity of the brain and corticospinal function. Non-invasive neurostimulation of the brain or of nerve/muscles/spinal roots, alone or in combination with conventional therapy, represents a fertile ground to develop more efficient approaches for pain management 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".