Weight-adjusted dosing of fibrinogen concentrate and cryoprecipitate in the treatment of hypofibrinogenaemic bleeding adult cardiac surgical patients: a post hoc analysis of the Fibrinogen Replenishment in cardiac surgery randomised controlled trial
Bibliographic record
Abstract
BackgroundHypofibrinogenaemia is associated with excessive bleeding after cardiac surgery. Our aim was to compare the efficacy and safety of weight-adjusted vs empiric dosing of fibrinogen replacement in cardiac surgery.MethodsIn the Fibrinogen Replenishment in Cardiac Surgery (FIBRES) RCT, patients (n=735) received fibrinogen concentrate (4 g) or cryoprecipitate (10 units). In this post-hoc analysis, patients were grouped into quartiles based on increasing weight-adjusted dosing. Generalised estimating equations were used to account for hospital site, age, sex, surgical complexity, urgency, and critical preoperative status. The primary outcome was the number of units of red blood cells transfused within 24 h of cardiopulmonary bypass. Secondary outcomes included allogeneic blood components within 24 h, tamponade or major bleeding, and thromboembolic complications, ischaemic complications, or both within 28 days of cardiopulmonary bypass.ResultsThe median weight-adjusted doses were 52 mg kg−1 of fibrinogen concentrate (inter-quartile range [IQR], 45–61; n=372) and 1.30 units per 10 kg of cryoprecipitate (IQR, 1.11–1.54; n=363). When patients were divided into quartiles of lowest to highest weight-adjusted dosing, no differences were seen in the primary outcome of red blood cell units transfused within 24 h of cardiopulmonary bypass between the lowest and highest quartiles in either the fibrinogen group (adjusted relative risk [RR]=0.90; 95% confidence interval [CI], 0.71–1.13; P=0.36) or the cryoprecipitate group (adjusted RR=1.04; 95% CI, 0.76–1.43; P=0.80). Results were similar for all secondary outcomes.ConclusionOutcomes for the lowest and highest weight-adjusted doses of fibrinogen replacement were comparable. Weight-adjusted dosing does not appear to offer advantages over empiric dosing in this context.Clinical trial registrationNCT03037424.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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".