Epidural stimulation improves cerebral autoregulation and autonomic cardiac control in humans with spinal cord injury
Bibliographic record
Abstract
Spinal cord injury (SCI) results in impaired cerebrovascular buffering of blood pressure changes and cardiovagal baroreflex sensitivity. These impairments appear to be at least partially the result of disrupted spinal autonomic pathways after SCI, and likely contribute to high rates of unstable blood pressure control, orthostatic intolerance, vascular‐cognitive impairment and high risk of stroke in this population. Acute spinal cord epidural electrical stimulation has recently been shown to activate the sympathetic nervous system. We therefore reasoned that acute epidural spinal cord stimulation could improve cerebrovascular buffering of blood pressure as well as baroreflex functionality after SCI. We tested this hypothesis by assessing the beat‐by‐beat relationships between heart rate, mean arterial blood pressure, and middle cerebral artery blood velocity in several individuals with SCI at rest and with acute epidural electrical stimulation after surgical implantation. We found epidural stimulation acutely improved cerebrovascular buffering of blood pressure and cardiovagal baroreflex function in people with SCI, raising the possibility that this intervention may be a viable therapy for improving cerebrovascular health in this population. Sponsors: Minnesota State Office of Higher Education. Natural Sciences and Engineering Research Council of Canada Canadian Institutes of Health Research Clinical Neurosciences Pilot Research Fund Program Libin Cardiovascular Institute Hotchkiss Brain Institute Compute Canada Support or Funding Information Natural Sciences and Engineering Research Council of Canada, Canadian Institutes of Health Research, Libin Cardiovascular Institute, Hotchkiss Brain Institute, Compute Canada This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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) | 0.002 | 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".