Vitamin K antagonist reversal strategies: Systematic review and network meta‐analysis from the <scp>AABB</scp>
Bibliographic record
Abstract
BACKGROUND: Anticoagulation requires urgent reversal in cases of life-threatening bleeding or invasive procedures. STUDY DESIGN AND METHODS: Network meta-analysis for comparing the safety and efficacy of warfarin reversal strategies including plasma and prothrombin complex concentrates (PCCs). RESULTS: Seven studies including 594 subjects using reversal agents plasma, 3-factor-PCC (Uman Complex and Konyne), and 4-factor-PCC (Beriplex/KCentra, Octaplex, and Cofact) met inclusion criteria. Compared with plasma, patients receiving Cofact probably have a higher rate of international normalized ratio (INR) correction (risk difference [RD] 499 more per 1000 patients, 95% confidence interval [CI], 176-761, low certainty[LC]); higher reversal of bleeding (323 more per 1000 patients, 11-344 more, LC); and fewer transfusion requirements (0.96 fewer units, 1.65-0.27 fewer, LC). Patients receiving Beriplex/KCentra probably have a higher rate of INR correction (476 more per 1000 patients, 332-609 more, LC); higher reversal of bleeding (127 more per 1000 patients, 43 fewer to 236 more); and similar transfusion requirements (0.01 fewer units, 0.31 fewer to 0.28 more, high/moderate certainty). Patients receiving Octaplex probably have a higher rate of INR correction (RD 579 more per 1000 patients, 189-825 more, LC). CONCLUSIONS: PCCs probably provide an advantage in INR reversal compared to plasma. There was no added risk of adverse events with PCCs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".