Efficacy and safety of the drugs used to reverse direct oral anticoagulants: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND Direct oral anticoagulants (DOACs) are effective and safe for prophylaxis and treatment of thromboembolic phenomena. However, managing DOACs during bleeding emergencies is challenging. A systematic review and meta‐analysis was conducted on studies addressing efficacy and safety of the drugs used for reversal of DOACs. STUDY DESIGN AND METHODS Medline, Embase, Cochrane Library, and ClinicalTrials.gov were searched up to September 2016. Studies that examined clinical and laboratory effects of drugs used to reverse DOACs were included. Risk of bias was assessed using Newcastle‐Ottawa scale and Cochrane Collaboration tool. Primary and secondary outcomes assessed were reversal of clinical bleeding, clotting assays, and safety, respectively. Overall effect estimates were pooled, and clinical and statistical heterogeneity were assessed. Meta‐analysis was conducted using random‐effects model. RESULTS Four cohort studies in bleeding patients (n = 230) and eight randomized controlled trials in healthy volunteers (n = 381) were included, both with moderate risk of bias. Reversal of clotting assays in healthy volunteers was frequently reported, demonstrating that prothrombin complex concentrate (PCC) reversed prothrombin time (PT) and endogenous thrombin potential (ETP) substantially. For PT, pooled mean difference was 1.68 seconds (95% confidence interval [CI], −0.33 to 3.70 sec; p < 0.01; I2 = 97%). For ETP, pooled mean difference was 2.16 seconds (95% CI, 0.57 to 3.75 sec; p < 0.01; I2 = 98%). Andexanet alfa and idarucizumab both reverse clotting assays. No important safety concerns were identified. CONCLUSIONS Clotting assays are partially reversed by PCC in healthy volunteers. Idarucizumab and andexanet alfa have solid laboratory reversal effect and potential to be clinically efficacious and safe. However, clinical evidence is still lacking for all agents.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.045 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".