Prothrombin complex concentrates versus fresh frozen plasma for warfarin reversal A systematic review and meta-analysis
Bibliographic record
Abstract
Urgent reversal of warfarin is required for patients who experience major bleeding or require urgent surgery. Treatment options include the combination of vitamin K and coagulation factor replacement with either prothrombin complex concentrate (PCC) or fresh frozen plasma (FFP). However, the optimal reversal strategy is unclear based on clinically relevant outcomes. We searched in MEDLINE, EMBASE and Cochrane library to December 2015. Thirteen studies (5 randomised studies and 8 observational studies) were included. PCC use was associated with a significant reduction in all-cause mortality compared to FFP (OR= 0.56, 95 % CI; 0.37-0.84, p=0.006). A higher proportion of patients receiving PCC achieved haemostasis compared to those receiving FFP, but this was not statistically significant (OR 2.00, 95 % CI; 0.85-4.68). PCC use was more likely to achieve normalisation of international normalised ratio (INR) (OR 10.80, 95 % CI; 6.12-19.07) and resulted in a shorter time to INR correction (mean difference -6.50 hours, 95 %CI; -9.75 to -3.24). Red blood cell transfusion was not statistically different between the two groups (OR 0.88, 95 % CI: 0.53-1.43). Patients receiving PCC had a lower risk of post-transfusion volume overload compared to FFP (OR 0.27, 95 % CI; 0.13-0.58). There was no statistically significant difference in the risk of thromboembolism following administration of PCC or FFP (OR 0.91, 95 % CI; 0.44-1.89). In conclusion, as compared to FFP, the use of PCC for warfarin reversal was associated with a significant reduction in all-cause mortality, more rapid INR reduction, and less volume overload without an increased risk of thromboembolic events.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".