Administration of Recombinant Factor VIIa Decreases Blood Loss After Blunt Trauma in Noncoagulopathic Pigs
Bibliographic record
Abstract
BACKGROUND: Activated factor VII catalyzes the activation of clotting factors IX and X within the clotting cascade, and has been used clinically to decrease bleeding in patients with hemophilia and other bleeding disorders. Studies suggest the use of recombinant VIIa (rVIIa) may decrease bleeding after injury in the presence of a coagulopathy, but there is conflicting evidence regarding its use in the absence of coagulopathy. This study was performed to determine whether a single dose of rVIIa would reduce blood loss in noncoagulopathic pigs after blunt trauma. METHODS: Anesthetized pigs were subject to multiple blunt injuries consisting of a femur fracture, liver laceration, and soft-tissue crush injury. Fifteen minutes after the trauma, pigs were randomized to receive a single 120 microg/kg dose of rVIIa or placebo. Mean arterial pressure, heart rate, temperature, and hematocrit (Hct) were measured during a 2-hour period of standardized fluid resuscitation. The primary endpoint was blood loss. RESULTS: The degree of trauma in the two groups was similar. Animals in the treated group had a mean blood loss of 19.6 mL/kg (13.5-25.7) versus 30.0 mL/kg (24.8-35.3) in the control group (p = 0.037). CONCLUSIONS: A single dose of 120 microg/kg of rVIIa can significantly decrease blood loss in traumatized pigs with no preexisting coagulopathy. Further studies are required to determine the lowest effective dose of this medication.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".