Perioperative interruption of direct oral anticoagulants and vitamin K antagonists in patients with atrial fibrillation: A comparative analysis
Bibliographic record
Abstract
BACKGROUND: There is a paucity of studies comparing postoperative thromboembolic and major bleeding complications following perioperative interruption of the direct oral anticoagulants (DOACs) and vitamin K antagonists (VKAs). OBJECTIVE/METHODS: We conducted a retrospective cohort study to compare postoperative thromboembolic and major bleeding outcomes following perioperative interruption of DOACs and VKAs in patients with atrial fibrillation. The primary efficacy and safety outcomes were the 30-day postoperative rates of arterial thromboembolic events (ATEs) and major bleeding, respectively. The secondary outcomes included the 30-day rates of clinically relevant nonmajor bleeding (CRNMB) and overall mortality. Thromboembolic, major bleeding, and mortality outcomes were independently adjudicated. Multivariable mixed-effects logistic-regression models were used to adjust for potential confounding variables between the DOAC and VKA cohorts. RESULTS: A total of 325 DOAC patients undergoing 351 procedures and 199 VKA patients undergoing 221 procedures were included. The 30-day ATE rate was 0.57% (95% confidence interval [CI], 0.27-0.8) in the DOAC cohort. There were no ATEs in the VKA cohort. The 30-day rates of major bleeding were 0.57% (95% CI, 0.27-0.8) and 3.62% (95% CI, 0-7.3) in the DOAC and the VKA cohorts, respectively. There were significantly more postoperative major bleeding events in the VKA cohort. The 30-day rate of CRNMB was 4.27% (95% CI, 4.15-4.42) in the DOAC cohort and 4.52% (95% CI, 3.67-5.38) in the VKA cohort. There were 2 deaths in the VKA cohort, one of which was deemed to be a fatal nonsurgical bleeding event. CONCLUSIONS: The perioperative interruption of VKAs may be associated with higher postoperative major bleeding rates as compared to DOACs. Careful postoperative reinitiation and monitoring of VKA anticoagulation may be warranted following surgical procedures.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".