Cryoprecipitate transfusion: assessing appropriateness and dosing in trauma
Bibliographic record
Abstract
BACKGROUND: Originally developed for patients with congenital factor VIII deficiency, cryoprecipitate is currently largely used for acquired hypofibrinogenemia in the context of bleeding. However, scant evidence supports this indication and cryoprecipitate is commonly used outside guidelines. In trauma, the appropriate cryoprecipitate dose and its impact on plasma fibrinogen levels are unclear. OBJECTIVES: The aims were to evaluate (i) the appropriateness of cryoprecipitate transfusion in trauma and (ii) the plasma fibrinogen response to cryoprecipitate transfusion during massive transfusion in trauma. METHODS: Retrospective review (January 1998-June 2008) of indications, dose and plasma fibrinogen response to cryoprecipitate transfusion at a large teaching hospital. A fibrinogen of <1.0 g L(-1) within 2 and 6 h of transfusion was used for evaluating appropriateness. RESULTS: Ten thousand five hundred and forty cryoprecipitate units were transfused in 1004 patients. Thirty-seven percent and 31% were used in cardiac surgery and trauma, respectively. In 394 events in trauma, 238 (60%) and 259 (66%) were considered appropriate using the 2- and 6-h cut-off criteria, respectively. In patients who did not receive plasma components 2 h prior to cryoprecipitate, a dose of 8.7 (± 1.7) units caused a mean increase in fibrinogen levels of 0.55 (± 0.24) g L(-1), or 0.06 g L(-1) per unit. CONCLUSIONS: In our hospital, where transfusion guidelines are overseen by transfusion medicine specialists and technologists, and policies for rapid blood component and laboratory turnaround times exist, it is possible to achieve high rates of appropriateness for cryoprecipitate transfusion in trauma. The current recommended dose causes a modest increase in fibrinogen levels (0.55 g L(-1) ).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".