Oral Anticoagulation Use and Left Atrial Appendage Occlusion in LAAOS III
Bibliographic record
Abstract
BACKGROUND: LAAOS III (Left Atrial Appendage Occlusion Study III) showed that left atrial appendage (LAA) occlusion reduces the risk of ischemic stroke or systemic embolism in patients with atrial fibrillation undergoing cardiac surgery. This article examines the effect of LAA occlusion on stroke reduction according to variation in the use of oral anticoagulant (OAC) therapy. METHODS: Information regarding OAC use was collected at every follow-up visit. Adjusted proportional hazards modeling, including using landmarks of hospital discharge, 1 and 2 years after randomization, evaluated the effect of LAA occlusion on the risk of ischemic stroke or systemic embolism, according to OAC use. Adjusted proportional hazard modeling, with OAC use as a time-dependent covariate, was also performed to assess the effect of LAA occlusion, according to OAC use throughout the study. RESULTS: At hospital discharge, 3027 patients (63.5%) were receiving a vitamin K antagonist, and 879 (18.5%) were receiving a non-vitamin K antagonist oral anticoagulant (direct OAC), with no difference in OAC use between treatment arms. There were 2887 (60.5%) patients who received OACs at all follow-up visits, 1401 (29.4%) who received OAC at some visits, and 472 (9.9%) who never received OACs. The effect of LAA occlusion on the risk of ischemic stroke or systemic embolism was consistent after discharge across all 3 groups: hazard ratios of 0.70 (95% CI, 0.51-0.96), 0.63 (95% CI, 0.43-0.94), and 0.76 (95% CI, 0.32-1.79), respectively. An adjusted proportional hazards model with OAC use as a time-dependent covariate showed that the reduction in stroke or systemic embolism with LAA occlusion was similar whether patients were receiving OACs or not. CONCLUSIONS: The benefit of LAA occlusion was consistent whether patients were receiving OACs or not. LAA occlusion provides thromboembolism reduction in patients independent of OAC use.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".