Perioperatively acquired disorders of coagulation
Bibliographic record
Abstract
PURPOSE OF REVIEW: To provide an overview of acquired coagulopathies that can occur in various perioperative clinical settings. Also described are coagulation disturbances linked to antithrombotic medications and currently available strategies to reverse their antithrombotic effects in situations of severe hemorrhage. RECENT FINDINGS: Recent studies highlight the link between low fibrinogen and decreased fibrin polymerization in the development of acquired coagulopathy. Particularly, fibrin(ogen) deficits are observable after cardiopulmonary bypass in cardiac surgery, on arrival at the emergency room in trauma patients, and with ongoing bleeding after child birth. Regarding antithrombotic therapy, although new oral anticoagulants offer the possibility of efficacy and relative safety compared with vitamin K antagonists, reversal of their anticoagulant effect with nonspecific agents, including prothrombin complex concentrate, has provided conflicting results. Specific antidotes, currently being developed, are not yet licensed for clinical use, but initial results are promising. SUMMARY: Targeted hemostatic therapy aims to correct coagulopathies in specific clinical settings, and reduce the need for allogeneic transfusions, thus preventing massive transfusion and its deleterious outcomes. Although there are specific guidelines for reversing anticoagulation in patients treated with antiplatelet agents or warfarin, there is currently little evidence to advocate comprehensive recommendations to treat drug-induced coagulopathy associated with new oral anticoagulants.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".