Prognostic value of chronic kidney disease in patients undergoing left atrial appendage occlusion
Bibliographic record
Abstract
AIMS: Atrial fibrillation (AF) and chronic kidney disease (CKD) often coexist and share an increased risk of thrombo-embolism (TE). CKD concomitantly predisposes towards a pro-haemorrhagic state. Our aim was to evaluate the prognostic value of CKD in patients undergoing percutaneous left atrial appendage occlusion (LAAO). METHODS AND RESULTS: A total of 2124 consecutive AF patients undergoing LAAO were categorized into CKD stage 1+2 (n = 1089), CKD stage 3 (n = 796), CKD stage 4 (n = 170), and CKD stage 5 (n = 69) based on the estimated glomerular filtration rate at baseline. The primary endpoint included cardiovascular (CV) mortality, TE, and major bleeding. The expected annual TE and major bleeding risks were estimated based on the CHA2DS2-VASc and HAS-BLED scores. A non-significant higher incidence of major peri-procedural adverse events (1.7 vs. 2.3 vs. 4.1 vs. 4.3) was observed with worsening CKD (P = 0.14). The mean follow-up period was 13 ± 7 months (2226 patient-years). In comparison to CKD stage 1+2 as a reference, the incidence of the primary endpoint was significantly higher in CKD stage 3 (log-rank P-value = 0.04), CKD stage 4 (log-rank P-value = 0.01), and CKD stage 5 (log-rank P-value = 0.001). Left atrial appendage occlusion led to a TE risk reduction (RR) of 72, 66, 62, and 41% in each group. The relative RR of major bleeding was 58, 44, 51, and 52%, respectively. CONCLUSION: Patients with moderate-to-severe CKD had a higher incidence of the primary composite endpoint. The relative RR in the incidence of TE and major bleeding was consistent across CKD groups.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".