Direct Oral Anticoagulant Use Early After Cardiac Surgery: A Retrospective Cohort Study
Bibliographic record
Abstract
Background There is limited literature guiding the prescribing of direct oral anticoagulants (DOACs) early after cardiac surgery due to this population being excluded from landmark randomized controlled trials. This study aims to determine the rate of in-hospital DOAC use compared to warfarin early after cardiac surgery, evaluate factors associated with DOAC use, determine difference in post-operative length of stay, and characterize bleeding events. Methods A retrospective cohort study was conducted in adult patients with an indication for anticoagulation and receiving either a DOAC or warfarin after cardiac surgery during their index hospitalization. Patients were excluded if they had any contraindications to DOAC use. The primary outcome was the proportion of patients discharged on a DOAC compared to warfarin. Results Of included 210 patients, 30% received a DOAC and 70% received warfarin on discharge. The most common DOAC used was apixaban (74.6%) and median post-operative day of initiation was 5 days. Patients receiving a DOAC were older (70.8 versus 68.0 years), had less valvular heart disease (38.1% versus 63.9%), more likely to be on a DOAC pre-operatively (50.8% versus 31.3%), and more likely to have undergone coronary artery bypass graft alone (54.0% versus 24.5%) compared to those on warfarin. Post-operative length of stay (7 versus 9 days, p=0.59) and in-hospital bleeding (1.6% versus 2.0%, p=1.00) did not differ between DOAC and warfarin groups. Conclusion At a quaternary referral center for cardiac surgery, DOACs were used in approximately one-third of patients with an indication for anticoagulation early after cardiac surgery.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".