Global Use of Idarucizumab in Clinical Practice: Outcomes of the RE-VECTO Surveillance Program
Bibliographic record
Abstract
Idarucizumab was approved for the reversal of dabigatran in 2015. We investigated whether postapproval usage patterns of idarucizumab in a real-world setting reflect those observed in the pivotal trials. No safety or efficacy data were collected in this medical record-based observational study. RE-VECTO, a global postapproval, international, surveillance program, involved hospital pharmacies in countries where idarucizumab was licensed and dispensed (August 2016-June 2018). Characteristics of sites prescribing idarucizumab and of eligible patients (≥ 18 years old and receiving idarucizumab regardless of prior oral anticoagulant use), as well as idarucizumab utilization data, were collected and analyzed descriptively. Sixty-one sites enrolled 359 patients. Most pharmacies (85.2%) were centralized, and the median idarucizumab units stocked per hospital was 2.0 (interquartile range, 1.0-3.0). Almost three-quarters of patients were elderly (74.9% aged > 70 years), and only four (1.1%) had received idarucizumab before. Nearly all patients were treated with dabigatran (97.5%). There was a low frequency of unapproved dabigatran dosage regimens (3.3%). Life-threatening or uncontrolled bleeding was the most frequent indication for idarucizumab (57.7%), followed by emergency surgery/urgent procedure (35.9%). Of the life-threatening bleeding events, the most frequent were gastrointestinal tract (44.4%) and intracranial (38.6%). Most patients (95.0%) were given the full dose of two vials (2 × 2.5 g) of idarucizumab initially, and very few (1.7%) received a second dose. Of those patients requiring emergency or scheduled/planned surgery/procedures, 25.5% underwent gastrointestinal and/or abdominal surgery/procedures. Real-world usage patterns of idarucizumab provide valuable insights into emergency reversal strategies. Off-label use was minimal.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".