Antithrombotic Therapy After Cardiac Surgery: Role of Different Oral Anticoagulants
Bibliographic record
Abstract
Background and aim of the study: Aim of this study is to compare the incidence of postoperative bleeding events, identified as pericardial effusion, for those patients undergoing cardiac surgery and discharged on vitamin K antagonist (VKA) versus those discharged on NOACs. Methods: This was a retrospective observational cohort study; from July 2017 to July 2019, all the patients who underwent any cardiac surgical procedure and discharged on any oral anticoagulant, were rolled in the study. The study variables and setting followed the STROBE checklist. The final cohort was constituted by 382 patients (mean age 70±11.2 years); 260(68.1%) patients were discharged on VKA and 122(31.9%) were discharged on NOACs. The primary end point was the incidence of major postoperative bleeding, defined as pericardial effusion requiring surgical re-exploration. The key secondary composite end point was the late re-admission for pericardial effusion. Results: The overall incidence of in-hospital immediate bleeding events, with need of re-exploration for pericardial effusion, was 4.7% (n=18). The incidence of re-admission for pericardial effusion was 3.1% (n=12). Eight of those patients had surgical re-exploration: four patients were discharged on NOACs and the remnant four ones were discharged on VKA. No significant relationships were observed between the different oral anticoagulants and the incidence of pericardial effusion, at any time. No ischemic and thromboembolic events were recorded. Conclusions: The use of non-vitamin K antagonist oral anticoagulant, in post cardiac surgery patients, does not increase the incidence of major bleeding events, intended as immediate or late pericardial effusion.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".