The coagulopathy of massive transfusion
Bibliographic record
Abstract
Recently, the Groupe d'Intérêt en Hémostase Périopératoire reviewed the pathophysiology of coagulopathy in massively transfused, adult and previously haemostatically competent patients in both elective surgical and trauma settings. In this article, we focus on our main observations. First, in most cases, the onset and severity of coagulopathy associated with massive transfusion differs depending on whether haemorrhage occurs as a result of trauma or elective surgery. In trauma patients, tissue trauma is uncontrolled, the interval between haemorrhage and treatment can vary widely, hypovolemia, shock and hypothermia are frequent, and coagulopathy is often related to the development of disseminated intravascular coagulation. Monitoring of haemostasis occurs late, when coagulopathy is installed, and treatment can be very difficult. In elective surgery patients, the situation remains controlled and, in most cases, a decrease in fibrinogen concentration is observed initially while thrombocytopenia is a late occurrence. Monitoring of haemostasis is ongoing and treatment is usually much simpler. Second, blood products have changed over time and this has affected the management of the bleeding patient. Contrary to the recommendations of studies published at a time when whole blood was readily available, the first line of treatment (at least in elective surgery patients) ought to be with fresh-frozen plasma to correct decreased levels of coagulation factors. The role of recombinant activated factor VII to treat bleeding that cannot be controlled by conventional measures remains to be clarified. Coagulopathy associated with massive transfusion remains an important clinical problem. Treatment strategies must be adapted to the context and to the blood products available. Nevertheless, the level of evidence supporting specific treatment options is low and more studies are required to guide our management of massively transfused 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".