The prophylactic use of fibrinogen concentrate in high‐risk cardiac surgery
Bibliographic record
Abstract
BACKGROUND: Perioperative blood loss is a major contributor to morbidity and mortality in cardiac surgery. Plasma fibrinogen levels play an essential role in hemostasis and deplete quickly during hemorrhage. The objective of this study was to determine whether prophylactic fibrinogen concentrate administration lowers overall blood product transfusion requirements in high-risk cardiac surgery in patients with low fibrinogen plasma levels. METHODS: The study was performed in a prospective, randomized, and double-blinded design. The investigation included 62 patients undergoing elective, high-risk cardiac surgery. After weaning from cardiopulmonary bypass and reversal of heparin patients received either fibrinogen concentrate or placebo. The primary outcome variable was overall blood product usage 24 hours after intervention. RESULTS: The fibrinogen group received numerically fewer total units of blood products than the placebo group, but the difference was not statistically or clinically significant (for groups n = 27; n = 29 and 19 vs 37 units, respectively, P = .908). The overall transfusion rate in both groups was significantly lower than the institutional average suggested (fibrinogen group 26%, placebo group 28%). The fibrinogen group showed significantly higher fibrinogen levels (2.38 vs 1.83 g/L (end of surgery), P < .001; 3.33 vs 2.68 g/L (12 hours after intervention), P = .003) and improved viscoelastic coagulation parameters (FIBTEM MCF, 27 vs 23 mm, P = .022). CONCLUSION: This randomized, controlled trial demonstrates that point-of-care guided and prophylactic treatment with fibrinogen concentrate does not reduce transfusion of blood products in a setting of unexpectedly low transfusion rate as tested in this cohort, but may improve coagulation parameters in the setting of high-risk cardiac surgery.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".