A Scoping Review of Epidural Spinal Cord Stimulation for Improving Motor and Voiding Function Following Spinal Cord Injury
Bibliographic record
Abstract
Objectives: To identify and synthesize the existing evidence on the effectiveness and safety of epidural spinal cord stimulation (SCS) for improving motor and voiding function and reducing spasticity following spinal cord injury (SCI). Methods: This scoping review was performed according to the framework of Arksey and O'Malley. Comprehensive serial searches in multiple databases (MEDLINE, Embase, Cochrane Central, Cochrane Database of Systematic Reviews, LILACS, PubMed, Web of Science, and Scopus) were performed to identify relevant publications that focused on epidural SCS for improving motor function, including spasticity, and voiding deficits in individuals with SCI. Results: Data from 13 case series including 88 individuals with complete or incomplete SCI (American Spinal Injury Association Impairment Scale [AIS] grade A to D) were included. In 12 studies of individuals with SCI, the majority (83 out of 88) demonstrated a variable degree of improvement in volitional motor function with epidural SCS. Two studies, incorporating 27 participants, demonstrated a significant reduction in spasticity with SCS. Two small studies consisting of five and two participants, respectively, demonstrated improved supraspinal control of volitional micturition with SCS. Conclusion: Epidural SCS can enhance central pattern generator activity and lower motor neuron excitability in individuals with SCI. The observed effects of epidural SCS following SCI suggest that the preservation of supraspinal transmission is sufficient for the recovery of volitional motor and voiding function, even in patients with complete SCI. Further research is warranted to evaluate and optimize the parameters for epidural SCS and their impact on individuals with differing degrees of severity of SCI.
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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 | 0.012 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.021 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".