Pro-Con Debate: Fibrinogen Concentrate or Cryoprecipitate for Treatment of Acquired Hypofibrinogenemia in Cardiac Surgical Patients
Bibliographic record
Abstract
Cryoprecipitate has been the gold standard for treating acquired hypofibrinogenemia in cardiac surgery for nearly 50 years. More recently, fibrinogen concentrate has been used off-label in the United States and is the standard in European countries and Canada to treat the acquired hypofibrinogenemia during cardiac surgery. Fibrinogen concentrate has multiple potential advantages including rapid reconstitution, greater dose predictability, viral inactivation during processing, and reduced transfusion-related adverse events. However, because fibrinogen concentrate lacks the other components contained in the cryoprecipitate, it may not be the "ideal" product for replacing fibrinogen in all cardiac surgical patients, particularly those with longer cardiopulmonary bypass duration. In this Pro-Con commentary article, we discuss the advantages and disadvantages of using fibrinogen concentrate and cryoprecipitate to treat acquired hypofibrinogenemia in cardiac surgical patients.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".