Long-Term Outcome of Patients with Atrial Fibrillation and High Risk of Stroke Treated with Oral Anticoagulation or Left Atrial Appendage Occlusion: A Cardinality Matched Analysis
Bibliographic record
Abstract
INTRODUCTION: Atrial fibrillation (AF) poses a significant risk of stroke. Left atrial appendage occlusion (LAAO) is an alternative for patients with contraindications to oral anticoagulation (OAC) or with high risk of bleeding. This study aims to compare the outcomes of LAAO versus conventional stroke prevention in high-risk AF-patients. METHODS: This secondary analysis incorporates data from the prospective Swiss-AF and Beat-AF cohorts, and the Zurich LAAO Registry. Cardinality matching was performed to create two comparable cohorts: conventional treatment (92% OAC) and LAAO. The primary endpoint was a composite of stroke, cardiovascular (CV) death, and clinically relevant bleeding. Kaplan-Meier method with competing risk analysis was used. RESULTS: Each group included 468 patients (age 76.4 [70.5, 82.0] years, 33% female). The LAAO group exhibited higher baseline bleeding risk (HAS BLED 2.0 [1.0-3.0] versus 3.0 [3.0-4.0]; p < 0.001). Median follow-up time: 6.0 (4.7-7.0) years in conventional treatment group and 4.0 (1.5-6.1) in LAAO group. No significant difference in the primary composite endpoint (HR 0.87, 95% CI: 0.72-1.06, p = 0.18), stroke risk (HR 1.14, 95% CI: 0.66-1.97, p = 0.64), or CV mortality (HR 1.08, 95% CI: 0.82-1.42, p = 0.60) was observed between groups. LAAO correlated with a significantly lower risk of clinically relevant bleeding (HR 0.61, 95% CI: 0.47-0.80, p < 0.001). CONCLUSION: In this cardinality matched analysis with long-term follow-up, LAAO showed similar stroke and CV death rates but lower clinically relevant bleeding risk compared to conventional therapy in high-risk AF-patients.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".