Combined Activity‐Based Therapy and Cervical Spinal Cord Stimulation: Active Ingredients, Targets and Mechanisms of Actions to Optimize Neurorestoration of Upper Limb Function After Cervical Spinal Cord Injury
Bibliographic record
Abstract
BACKGROUND: Improving hand and arm function is an important goal for individuals with cervical spinal cord injury (cSCI). Activity Based Therapy (ABT) is a neurorestorative approach that incorporates a high intensity, long duration and effortful engagement to garner sensory-motor improvements. Spinal cord stimulation is a neuromodulation modality that can restore sensory-motor function. Spinal cord stimulation can elevate the excitability of the spinal neural network and potentially enhance the neurorestorative benefits of ABT. However, there is scarce evidence on the combined effects of ABT and spinal cord stimulation on UL recovery after cSCI. OBJECTIVE: This report aims to describe how theory informed the design and development of a Phase 1 study on a new UL intervention combining ABT and transcutaneous cervical spinal cord stimulation (tCSCS) (short form:ABT-tCSCS) delivered simultaneously for individuals with cSCI. METHOD: The design of the ABT-tCSCS was guided by theory-based frameworks such as the Rehabilitation treatment specification system and the Template for Intervention Description and Replication guide. The ABT-TCSCS aimed to improve somatosensory-motor deficits and function in the UL after cSCI. The ABT-tCSCS intervention was developed through the following stages: (a) Description of the active ingredients, mechanism of action, and targets of the ABT-tCSCS; (b) Tailoring of ABT-tCSCS; and (c) Development of treatment regimen guidelines for the delivery of the ABT-tCSCS. RESULTS: ABT constitutes 4 types of exercises, including cardio-fitness, resistance, postural/weightbearing, and functional exercises, for activation of the neuromuscular system below the level of lesion to target somatosensory-motor impairments. In tCSCS, electrical stimulation is delivered at a frequency of 30-50 Hz at 500-1000 μs between C3-C7. The spinal neural networks of the cervical region are stimulated to neuromodulate the descending motor commands which control the muscles. ABT-tCSCS will be delivered simultaneously over 28 sessions (1 h/session, 3x/week over 9-10 weeks). CONCLUSIONS: Combined ABT-tCSCS is a new intervention for neurorestoration of the upper limbs after cSCI. TRAIL REGISTRATION: ClinicalTrials.gov ID: NCT06472986.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".