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 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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".