Contribution of inflammation to cellular injury in compartment syndrome in an experimental rodent model
Bibliographic record
Abstract
Compartment syndrome, a devastating consequence of limb trauma, is characterised by severe tissue injury and microvascular perfusion deficits. We hypothesised that leucopenia might provide significant protection against microvascular dysfunction and preserve tissue viability. Using our clinically relevant rat model of compartment syndrome, microvascular perfusion and tissue injury were directly visualised by intravital video microscopy in leucopenic animals. We found that while the tissue perfusion was similar in both groups (38.8% (standard error of the mean (sem) 7.1), 36.4% (sem 5.7), 32.0% (sem 1.7), and 30.5% (sem 5.35) continuously-perfused capillaries at 45, 90, 120 and 180 minutes compartment syndrome, respectively versus 39.2% (sem 8.6), 43.5% (sem 8.5), 36.6% (sem 1.4) and 50.8% (sem 4.8) at 45, 90, 120 and 180 minutes compartment syndrome, respectively in leucopenia), compartment syndrome-associated muscle injury was significantly decreased in leucopenic animals (7.0% (sem 2.0), 7.0%, (sem 1.0), 9.0% (sem 1.0) and 5.0% (sem 2.0) at 45, 90, 120 and 180 minutes of compartment syndrome, respectively in leucopenia group versus 18.0% (sem 4.0), 23.0% (sem 4.0), 32.0% (sem 7.0), and 20.0% (sem 5.0) at 45, 90, 120 and 180 minutes of compartment syndrome in control, p = 0.0005). This study demonstrates that the inflammatory process should be considered central to the understanding of the pathogenesis of cellular injury in compartment syndrome.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".