Epidural Spinal Cord Stimulation of Lumbosacral Networks Modulates Arterial Blood Pressure in Individuals With Spinal Cord Injury-Induced Cardiovascular Deficits
Bibliographic record
Abstract
Disruption of motor and autonomic pathways induced by spinal cord injury (SCI) often leads to persistent low arterial blood pressure and orthostatic intolerance. Spinal cord epidural stimulation (scES) has been shown to enable independent standing and voluntary movement in individuals with clinically motor complete SCI. In this study, we addressed whether scES configured to activate motor lumbosacral networks can also modulate arterial blood pressure by assessing continuous, beat-by-beat blood pressure and lower extremity electromyography during supine and standing in seven individuals with C5-T4 SCI. In three research participants with arterial hypotension, orthostatic intolerance, and low levels of circulating catecholamines (group 1), scES applied while supine and standing resulted in increased arterial blood pressure. In four research participants without evidence of arterial hypotension or orthostatic intolerance and normative circulating catecholamines (group 2), scES did not induce significant increases in arterial blood pressure. During scES, there were no significant differences in electromyographic (EMG) activity between group 1 and group 2. In group 1, during standing assisted by scES, blood pressure was maintained at 119/72 ± 7/14 mmHg (mean ± SD) compared with 70/45 ± 5/7 mmHg without scES. In group 2 there were no arterial blood pressure changes during standing with or without scES. These findings demonstrate that scES configured to facilitate motor function can acutely increase arterial blood pressure in individuals with SCI-induced cardiovascular deficits.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".