The Effectiveness and Safety of Tranexamic Acid in Orthotopic Liver Transplantation Clinical Practice
Bibliographic record
Abstract
BACKGROUND: Randomized trials have demonstrated the efficacy of tranexamic acid (TXA) in reducing blood loss and transfusion requirements during liver transplantation. However, clinical utilization is limited due to a perceived lack of generalizable effectiveness and concerns regarding its thromboembolic risks. The aim of this study was to describe the clinical use of TXA and to provide a pragmatic reappraisal of its effectiveness and safety. METHODS: After ethics approval, data were collected from 1799 consecutive liver transplant recipients between January 1, 2002, and December 31, 2015, using retrospectively collected electronic databases. Propensity matching was used to account for confounders of transfusion and thrombotic risk. Exposure was defined as a total TXA dose greater than 10 mg/kg for 50% of the operative duration. RESULTS: After propensity matching, 367 unique pairs were well balanced in terms of all measured covariates. In the matched pairs, patients exposed to TXA received less red blood cell (3 [0, 6] vs 4 [1, 7] P = 0.003) and frozen plasma (6 [2, 10] vs 6 [2, 12], P = 0.032) transfusions. There were no differences in thromboembolic events between the groups (22 [6.0%] vs 36 [9.8%]). CONCLUSIONS: TXA appears effective in reducing red blood cell transfusion requirements without increasing the risk of thromboembolic events across a wide variety of liver transplant recipients, including those at low risk of bleeding or high risk of thromboembolic complications. We did not detect evidence of an increased risk of thrombotic complications with TXA exposure.
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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 | 0.009 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".