Preoperative Fibrinogen Level and Bleeding in Liver Transplantation for End-stage Liver Disease: A Cohort Study
Bibliographic record
Abstract
BACKGROUND: Liver transplantation is a high-risk surgery associated with important perioperative bleeding and transfusion needs. Uncertainties remain on the association between preoperative fibrinogen level and bleeding in this population. METHODS: We conducted a cohort study that included all consecutive adult patients undergoing a liver transplantation for end-stage liver disease in 1 center. We analyzed the association between the preoperative fibrinogen level and bleeding-related outcomes. Our primary outcome was intraoperative blood loss, and our secondary outcomes were estimated perioperative blood loss, intraoperative and perioperative red blood cell transfusions, reinterventions for bleeding and 1-y graft and patient survival. We estimated linear regression models and marginal risk models adjusted for all important potential confounders. We used restricted cubic splines to explore potential nonlinear associations and reported dose-response curves. RESULTS: We included 613 patients. We observed that a lower fibrinogen level was associated with a higher intraoperative blood loss, a higher estimated perioperative blood loss and a higher risk of intraoperative and perioperative red blood cell transfusions (nonlinear effects). Based on an exploratory analysis of the dose-response curves, these effects were observed below a threshold value of 3 g/L for these outcomes. We did not observe any association between preoperative fibrinogen level and reinterventions, 1-y graft survival or 1-y patient survival. CONCLUSIONS: This study suggests that a lower fibrinogen level is associated with bleeding in liver transplantation. The present results may help improving the selection of patients for further studies on preoperative fibrinogen administration in liver transplant recipients with end-stage liver disease.
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 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".