Safety of idarucizumab in the reversal of dabigatran at six tertiary care Ontario hospitals
Bibliographic record
Abstract
BACKGROUND: Idarucizumab, a monoclonal antibody fragment that reverses the anticoagulant effect of dabigatran, was approved for use in Canada in 2016. OBJECTIVE: Our objective was to assess the safety of idarucizumab among patients who received the drug within the first 3 years of its use in Canada. PATIENTS/METHODS: We performed a retrospective health records review of all idarucizumab use, excluding use in those <18 years of age, between May 16, 2016, and August 1, 2019, at six Ontario tertiary care hospitals. The primary outcome was mortality. The secondary outcomes were in-hospital arterial thrombotic event (ATE), in-hospital venous thromboembolism (VTE), length of hospital stay, and length of critical care stay. RESULTS: A total of 85 patients received idarucizumab during the study period for the following indications: 37 (43.5%) for spontaneous bleeding, 28 (32.9%) for traumatic bleeding, 11 (12.9%) for emergency surgeries/procedures, 5 (5.9%) for elective surgeries/procedures, and 4 (4.7%) for other indications. Nineteen patients (22.4%; 95% confidence interval [CI], 14.8%-32.3%) did not survive their hospitalization. During hospitalization, two patients (2.4%; 95% CI, 0.7%-8.2%) had ATE, and three patients (3.5%; 95% CI, 1.2%-9.9%) had VTE. The median length of stay was 8 (interquartile range [IQR], 2.5-13) days in hospital and 3 (IQR, 2-5) days in critical care. CONCLUSIONS: Compared with clinical trial data, we found a numerically higher rate of mortality and similar rate of ATE and VTE among patients treated with idarucizumab in the real world.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".