Abstract 2051: Recombinant Factor VIIa Affects Vein Graft Patency and Flow in Rabbits
Bibliographic record
Abstract
INTRODUCTION: Recombinant factor VIIa (rVIIa) has been used to decrease postoperative bleeding in cardiac surgical patients. However, there is potential for rVIIa to interact with tissue factor expression at the site of new anastomoses resulting in early graft occlusion. This safety study tested the hypothesis that the administration of rVIIa dose-dependently reduces graft patency at the site of new vascular anastomoses comparable in size to human coronaries, in a rabbit model. METHODS: After ACC approval, a reversed venous graft was fashioned in the right carotid artery using autologous right jugular vein with 9 – 0 sutures in 64 anesthetized and heparinized rabbits. Animals were then given either one of three doses of rVIIa (300 ug/kg, 90 ug/kg or 20 ug/kg IV) or placebo (n=16/group). The primary outcome was graft patency, measured by a blinded observer 24 hours postoperatively using vascular ultrasound (HDI 5000cv, 15 MHz probe) and/or direct inspection. Factor VII activity levels were measured from citrated plasma samples with a 1-stage prothrombin time-based assay using rabbit thromboplastin. Data was analyzed using chi-square, fishers exact test, or ANOVA where appropriate, with p<0.05 considered significant. RESULTS: Physiologic variables (ACT, hemoglobin, pH, pCO2) and vessel diameter were similar between groups. Graft patency and flow were significantly reduced, and plasma factor VII levels significantly increased in the rVIIa treated rabbits in a dose-dependent fashion. DISCUSSION: The study suggests that high doses of rVIIa (300 and 90 ug/kg) are associated with an increased incidence of occlusion of new vascular grafts. A clear dose-response effect was observed, suggesting that higher doses may be associated with increased thrombotic outcomes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".