Cardio-centric hemodynamic management improves spinal cord oxygenation and mitigates hemorrhage in acute spinal cord injury
Bibliographic record
Abstract
Abstract Chronic high-thoracic and cervical spinal cord injury (SCI) results in a complex phenotype of cardiovascular consequences, including impaired left ventricular (LV) contractility. Here, we aim to determine whether such dysfunction manifests immediately post-injury, and if so, whether correcting impaired contractility can improve spinal cord oxygenation (SCO 2 ), blood flow (SCBF) and metabolism. Using a porcine model of T2 SCI, we assess LV end-systolic elastance (contractility) via invasive pressure-volume catheterization, monitor intraparenchymal SCO 2 and SCBF with fiberoptic oxygen sensors and laser-Doppler flowmetry, respectively, and quantify spinal cord metabolites with microdialysis. We demonstrate that high-thoracic SCI acutely impairs cardiac contractility and substantially reduces SCO 2 and SCBF within the first hours post-injury. Utilizing the same model, we next show that augmenting LV contractility with the β-agonist dobutamine increases SCO 2 and SCBF more effectively than vasopressor therapy, whilst also mitigating increased anaerobic metabolism and hemorrhage in the injured cord. Finally, in pigs with T2 SCI survived for 12 weeks post-injury, we confirm that acute hemodynamic management with dobutamine appears to preserve cardiac function and improve hemodynamic outcomes in the chronic setting. Our data support that cardio-centric hemodynamic management represents an advantageous alternative to the current clinical standard of vasopressor therapy for acute traumatic 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 | 0.000 | 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 | 0.001 |
| 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".