A Pragmatic Review on Spinal Cord Stimulation Therapy for Parkinson's Disease Gait Related Disorders: Gaps and Controversies
Bibliographic record
Abstract
BACKGROUND: Parkinson's Disease (PD) is a progressive neurological disorder that results in potentially debilitating mobility deficits. Recently, spinal cord stimulation (SCS) has been proposed as a novel therapy for PD gait disorders. The highest levels of evidence remain limited for SCS. OBJECTIVES: In this systematic review and narrative synthesis, the literature was searched using combinations of key phrases indicating spinal cord stimulation and PD. METHODS: We included pre-clinical studies and all published clinical trials, case reports, conference abstracts as well as protocols for ongoing clinical trials. Additionally, we included trials of SCS applied to atypical parkinsonism. RESULTS: A total of 45 human studies and trials met the inclusion criteria. Based on the narrative synthesis, a number of knowledge gaps and future avenues of potential research were identified. This review demonstrated that evidence for SCS is currently not sufficient to recommend it as an evidence-based therapy for PD related gait disorders. There remain challenges and significant barriers to widespread implementation, including issues regarding patient selection, effective outcome selection, stimulation location and mode, and in programming parameter optimization. Results of early randomized controlled trials are currently pending. SCS is prone to placebo, lessebo and nocebo as well as blinding effects which may impact interpretation of outcomes, particularly when studies are underpowered. CONCLUSION: Therapies such as SCS may build on current evidence and be shown to improve specific gait features in PD. Early negative trials should be interpreted with caution, as more evidence will be required to develop effective methodologies in order to drive clinical outcomes.
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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 | 0.018 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".