Safety of prothrombin complex concentrates for rapid anticoagulation reversal of vitamin K antagonists
Bibliographic record
Abstract
Prothrombin complex concentrates (PCCs) are recommended as the treatment of choice in warfarin-related coagulopathy. However, the risk of thromboembolic complications associated with their use is not well defined. We performed a meta-analysis to estimate the rate of thromboembolic complications in patients receiving vitamin K antagonists (VKAs) treated with PCCs for bleeding or before urgent surgery. Medline and Embase databases were searched. Two reviewers performed study selection and extracted data independently. Studies providing data on incidence of thromboembolic complications in VKA-treated patients were eligible for the study. Weighted mean proportion of the rate of thromboembolic complications and the mortality rate were calculated. Twenty-seven studies (1,032 patients) were included. Seven studies used 3-factor, and 20 4-factor PCCs. Twelve patients had a thromboembolic complication (weighted mean 1.4%; 95% CI 0.8-2.1), of which two were fatal. The incidence of thromboembolic events was 1.8% (95% CI 1.0-3.0) in patients treated with 4-factor PCCs, and 0.7% (95% CI 0.0-2.4) in patients treated with 3-factor PCCs. Total mortality rate was 10.6% (95% CI 5.9-16.6). In conclusion, our results suggest there is a low but quantifiable risk of thromboembolism in VKA-treated patients receiving PCCs for anticoagulation reversal. These findings should be confirmed in randomised, controlled trials.
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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 | 0.030 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.020 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".