Spinal electrical stimulation to improve sympathetic autonomic functions needed for movement and exercise after spinal cord injury: a scoping clinical review
Bibliographic record
Abstract
Spinal cord injury (SCI) results in sensory, motor, and autonomic dysfunction. Obesity, cardiovascular disease, and metabolic disease are highly prevalent after SCI. Although inadequate voluntary activation of skeletal muscle contributes, it is absent or inadequate activation of thoracic spinal sympathetic neural circuitry and suboptimal activation of homeostatic (cardiovascular and temperature) and metabolic support systems that truly limits exercise capacity, particularly for those with cervical SCI. Thus, when electrical spinal cord stimulation (SCS) studies aimed at improving motor functions began mentioning effects on exercise-related autonomic functions, a potential new area of clinical application appeared. To survey this new area of potential benefit, we performed a systematic scoping review of clinical SCS studies involving these spinally mediated autonomic functions. Nineteen studies were included, 8 used transcutaneous and 11 used epidural SCS. Improvements in blood pressure regulation at rest or in response to orthostatic challenge were investigated most systematically, whereas reports of improved temperature regulation, whole body metabolism, and peak exercise performance were mainly anecdotal. Effective stimulation locations and parameters varied between studies, suggesting multiple stimulation parameters and rostrocaudal spinal locations may influence the same sympathetic function. Brainstem and spinal neural mechanisms providing excitatory drive to sympathetic neurons that activate homeostatic and metabolic tissues that provide support for movement and exercise and their integration with locomotor neural circuitry are discussed. A unifying conceptual framework for the integrated neural control of locomotor and sympathetic function is presented which may inform future research needed to take full advantage of SCS for improving these spinally mediated autonomic functions.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".