The Perioperative Anticoagulant Use for Surgery Evaluation (PAUSE) Study for Patients on a Direct Oral Anticoagulant Who Need an Elective Surgery or Procedure: Design and Rationale
Bibliographic record
Abstract
Background The perioperative management of patients who take a direct oral anticoagulant (DOAC) for atrial fibrillation and require treatment interruption for an elective surgery/procedure is a common clinical scenario for which best practices are uncertain. The Perioperative Anticoagulant Use for Surgery Evaluation (PAUSE) study is designed to address this unmet clinical need. We discuss the rationale for the PAUSE design and analysis plan as well as the rationale supporting the perioperative DOAC protocol. Methods PAUSE is a prospective study with three parallel cohorts, one for each DOAC, to assess a standardized but patient-specific perioperative management protocol for DOAC-treated patients with atrial fibrillation. The perioperative protocol accounts for DOAC type, patient's renal function and surgery/procedure-related bleeding risk. The primary study aim is to demonstrate the safety of the PAUSE protocol for the perioperative management of each DOAC. The secondary aim is to determine the effect of the pre-procedure interruption on residual anticoagulation when measured by the dilute thrombin time for dabigatran and anti-factor Xa levels for rivaroxaban and apixaban. The study hypothesis is that the perioperative management protocol for each DOAC is safe for patient care, defined by expected risks for major bleeding of 1% (80% power to exclude 2%), and for arterial thromboembolism of 0.5% (80% power to exclude 1.5%) in each DOAC group. Conclusion The PAUSE study has the potential to establish a standard-of-care approach for the perioperative management of DOAC-treated patients. The PAUSE management protocol is designed to be easily applied in clinical practice, as it is standardized and also patient specific.
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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 | 0.063 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".