Aprotinin Versus Tranexamic Acid During Liver Transplantation: Impact on Blood Product Requirements and Survival
Bibliographic record
Abstract
BACKGROUND: Historically, orthotopic liver transplantation (OLT) has been associated with major blood loss and the need for blood product transfusions. Activation of the fibrinolytic system can contribute significantly to bleeding. Prophylactic administration of antifibrinolytic agents was found to reduce blood loss. METHODS: The efficacy of two antifibrinolytic compounds--aprotinin (AP) and tranexamic acid (TA)--was compared in OLT. Four hundred consecutive OLTs were studied: 300 patients received AP and 100 received TA. Multivariate logistic regression analysis was used to identify independent predictors of intraoperative transfusion requirement and 1-year patient mortality. RESULTS: There was no intergroup difference in intraoperative blood loss (1082±1056 vs. 1007±790 mL), red blood cell transfusion per patient (0.5±1.4 vs. 0.5±1.0), final hemoglobin (Hb) concentration (93±20 g/L vs. 95±22 g/L), the percentage of OLT cases requiring no blood product administration (80% vs. 82%), and 1-year survival (85.1% vs. 87.4%). Serum creatinine concentrations were also the same (116±55 vs. 119±36 μmol/L) 1 year after surgery. Two variables, starting Hb and phlebotomy, correlated with the two primary outcome measures (transfusion and 1-year survival). CONCLUSIONS: In our experience, administration of AP was not superior to TA with regards to blood loss and blood product transfusion requirement during OLT. In addition, we found no difference between the groups in the 1-year survival rate and renal function. Furthermore, we suggest that starting Hb concentration should be considered when prioritizing patients on the waiting list and planning perioperative care for OLT recipients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".