Porcine Model of Acute Compartment Syndrome
Bibliographic record
Abstract
OBJECTIVES: Acute compartment syndrome is a devastating condition associated with lasting consequences or even death if not treated in a timely fashion. Current preclinical modeling is inadequate. Ideally a model should mimic human disease. There should be a trauma-induced reperfusion or direct muscle event that causes gradual increased pressure and is amenable to release with fasciotomy. We have attempted to reproduce this mechanism and outcome in a porcine model. METHODS: Anterior tibial musculature was injured with vascular occlusion plus exterior tourniquet crush or direct intracompartmental crush through balloon inflation. The injury was maintained for over 5 hours. At that time, the tourniquet or balloon was removed. The injuries were continuously monitored with an intramuscular continuous pressure sensor. Pressure changes were recorded and after 2 hours of postinjury observation, a fasciotomy was performed for the muscle compartment. RESULTS: Pressures were brought to 100 mm Hg during the injury phase. During the two-hour observation period, the balloon catheter technique achieved an average pressure of 25.1 ± SD 8.8 mm Hg with a maximum reading of 38.2 mm Hg and minimum reading of 14.1 mm Hg. During this same period, the ischemia-reperfusion + direct crush technique achieved an average pressure of 33.7 ± SD 7.3 mm Hg, with a maximum reading of 43.5 mm Hg and minimum reading of 23.5 mm Hg. Average pressure postfasciotomy for the balloon catheter technique was 2.4 ± SD 2.5 mm Hg; and for the crush technique, average value postfasciotomy was 4.9 ± SD 3.7 mm Hg-both representing a return to physiologic levels. CONCLUSION: This is the first preclinical model that shows the same response to injury and treatment as is observed in human physiology. Surgical and nonsurgical therapies for compartment syndrome can now be tested reliably.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".