Relationship between Early Vasopressor Administration and Spinal Cord Hemorrhage in a Porcine Model of Acute Traumatic Spinal Cord Injury
Bibliographic record
Abstract
Current practice guidelines for acute spinal cord injury (SCI) recommend augmenting mean arterial blood pressure (MAP) for the first 7 days post-injury. After SCI, the cord may be compressed by the bone/ligaments of the spinal column, limiting regional spinal cord blood flow. Following surgical decompression, blood flow may be restored, and can potentially promote a "reperfusion" injury. The effects of MAP augmentation on the injured cord during the compressed and decompressed conditions have not been previously characterized. Here, we used our porcine model of SCI to examine the impact of MAP augmentation on blood flow, oxygenation, hydrostatic pressure, metabolism, and intraparenchymal (IP) hemorrhage within the compressed and then subsequently decompressed spinal cord. Yucatan mini-pigs underwent a T10 contusion injury followed by 2 h of sustained compression. MAP augmentation of ∼20 mm Hg was achieved with norepinephrine (NE). Animals received MAP augmentation either during the period of cord compression (CP), after decompression (DCP), or during both periods (CP-DCP). Probes to monitor spinal cord blood flow (SCBF), oxygenation, pressure, and metabolic responses were inserted into the cord parenchyma adjacent to the injury site to measure these responses. The cord was harvested for histological evaluation. MAP augmentation increased SCBF and oxygenation in all groups. In the CP-DCP group, spinal cord pressure steadily increased and histological analysis showed significantly increased hemorrhage in the spinal cord at and near the injury site. MAP augmentation with vasopressors may improve blood flow and reduce ischemia in the injured cord but may also induce undesirable increases in IP pressure and hemorrhage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".