Compartment syndrome–induced microvascular dysfunction: an experimental rodent model
Bibliographic record
Abstract
BACKGROUND: Acute compartment syndrome (CS) is a limb-threatening disease that results from increased intracompartmental pressure. The pathophysiologic mechanisms by which this occurs are poorly understood. This study was designed to measure the effects of increased intracompartmental pressure on skeletal muscle microcirculation, inflammation and cellular injury using intravital videomicroscopy (IVVM) in a clinically relevant small animal model. METHODS: We induced CS in 10 male Wistar rats (175-250 g), using a saline infusion technique. Intracompartmental pressure was controlled between 30 and 40 mm Hg and maintained for 45 minutes. After fasciotomy, the extensor digitorum longus muscle was visualized using IVVM, and perfusion was quantified. We quantified leukocyte recruitment to measure the inflammatory response. We measured muscle cellular injury using a differential fluorescent staining technique. RESULTS: The number of nonperfused capillaries increased from 12.7 (standard error of the mean [SEM] 1.4 ) per mm in the control group to 30.0 (SEM 6.7) per mm following 45 minutes of elevated intracompartmental pressure (CS group; p = 0.031). The mean number of continuously perfused capillaries (and SEM) decreased from 78.4 (3.2) per mm in the control group to 41.4 (6.9) per mm in the CS group (p = 0.001). The proportion of injured cells increased from 5.0% (SEM 2.1%) in the control group to 16.3% (SEM 6.8%) in the CS group (p = 0.006). The mean number of activated leukocytes increased from 3.6 (SEM 0.7) per 100 μm(2) in the control group to 8.6 (SEM 1.8) per 100 μm(2) in the CS group (p = 0.033). CONCLUSION: Early CS-induced microvascular dysfunction resulted in a decrease in nutritive capillary perfusion and an increase in cellular injury and was associated with a severe acute inflammatory component.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".