Incidence, predictors, and clinical impact of bleeding recurrence in patients with prior gastrointestinal bleeding undergoing LAAC
Bibliographic record
Abstract
BACKGROUND: Gastrointestinal bleeding (GIB) is associated with a high recurrence rate and a prior GIB episode is common in real-world left atrial appendage closure (LAAC) recipients. The present study sought to evaluate the clinical characteristics and outcomes of patients with prior GIB undergoing LAAC, and to determine the factors associated with and clinical impact of GIB recurrence. METHODS: Multicenter study including 277 consecutive patients who underwent percutaneous LAAC and had prior GIB. All-cause death, all bleeding, GIB recurrence, and clinical ischemic stroke were recorded. RESULTS: After a median follow-up of 17 (interquartile range: 6-37) months post-LAAC, the rates of death, bleeding, GIB recurrence, and ischemic stroke were 14.0 per 100 person-year (PY), 29.3 per 100 PY, 17.7 per 100 PY, and 1.1 per 100 PY, respectively. GIB recurrence occurred within 3 months post-LAAC in 55.8% of patients. A previous lower GIB (vs. upper or unclassified) (HR: 1.76; 95% CI: 1.09-2.82; p = .020) and eGFR < 45 mL/min (HR: 1.70; 95% CI:1.04-2.67; p = .033) determined an increased risk of GIB recurrence. By multivariable analysis, eGFR < 45 mL/min (HR: 2.72; 95% CI: 1.70-4.34; p < .001), GIB recurrence following LAAC (HR: 2.15; 95% CI: 1.33-3.46; p = .002), diabetes mellitus (HR: 1.77; 95% CI: 1.10-2.84; p = .018), and age (HR: 1.06; 95% CI: 1.03-1.10; p < .001) were associated with an increased mortality. CONCLUSIONS: Patients with prior GIB undergoing LAAC exhibited a relatively low rate of GIB recurrence, and prior lower GIB and moderate-to-severe chronic kidney disease determined an increased risk. GIB recurrence was associated with an increased mortality.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 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".