Perioperative Management of Dabigatran
Bibliographic record
Abstract
BACKGROUND: The perioperative management of dabigatran in clinical practice is heterogeneous. We performed this study to evaluate the safety of perioperative management of dabigatran using a specified protocol. METHODS AND RESULTS: Patients treated with dabigatran and planned for an invasive procedure were eligible for inclusion. The timing of the last dose of dabigatran before the procedure was based on the creatinine clearance and procedure-related bleeding risk. Resumption of dabigatran was prespecified according to the complexity of the surgery and consequences of a bleeding complication. Patients were followed up for 30 days for major bleeding (primary outcome), minor bleeding, arterial thromboembolism, and death. We included 541 cases: 324 procedures (60%) with standard risk of bleeding and 217 procedures (40%) with increased risk of bleeding. The last dose of dabigatran was at 24, 48, or 96 hours before surgery according to the protocol in 46%, 37%, and 6%, respectively, of the patients. Resumption was timed according to protocol in 77% with 75 mg as the first dose on the day of procedure in 40% of the patients. Ten patients (1.8%; 95% confidence interval, 0.7-3.0) had major bleeding, and 28 patients (5.2%; 95% confidence interval, 3.3-7.0) had minor bleeding events. The only thromboembolic complication was transient ischemic attack in 1 patient (0.2%; 95% confidence interval, 0-0.5), and there were 4 deaths unrelated to bleeding or thrombosis. Bridging was not used preoperatively but was administered in 9 patients (1.7%) postoperatively. CONCLUSION: Our protocol for perioperative management of dabigatran appears to be effective and feasible.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".