Unplanned Hospital Readmissions After Transcatheter Aortic Valve Replacement in the Era of New-Generation Devices
Bibliographic record
Abstract
OBJECTIVES: Unplanned hospital readmissions after transcatheter aortic valve replacement (TAVR) are frequent and have been associated with a poor prognosis. We sought to determine the trends in the incidence and causes of unplanned hospital readmission after TAVR in patients receiving new-generation devices (NGDs) vs early-generation devices (EGDs). METHODS: The study population consisted of 1802 consecutive TAVR recipients (863 EGDs and 939 NGDs). Early and late readmissions were defined as those occurring ≤30 days and >30 days to 1-year post TAVR, respectively. RESULTS: A total of 986 unplanned hospital readmissions (cardiac cause, 38.4%; non-cardiac cause, 61.6%) were recorded at a median time of 110 days (interquartile range [IQR], 37-217) post TAVR. The rates of early (12.3% vs 9.4%; P=.046) and late (39.1% vs 31.6%; P<.01) readmission were lower in the NGD population. In the NGD group, major/life-threatening periprocedural bleeding (hazard ratio [HR], 2.40, 95% confidence interval [CI], 1.06-5.42; P=.04) and estimated glomerular filtration rate (eGFR) <60 mL/min at hospital discharge (HR, 1.80; 95% CI, 1.15-2.83; P=.01) were associated with an increased risk of early readmission post TAVR. Chronic obstructive pulmonary disease (HR, 1.42; 95% CI, 1.07-1.88; P=.02), eGFR <60 mL/min (HR, 1.43; 95% CI, 1.11-1.84; P<.01), and combining antiplatelet and anticoagulation therapy (HR, 1.37; 95% CI, 1.01-1.85; P=.04) determined an increased risk of late readmission. CONCLUSIONS: TAVR recipients receiving NGDs exhibited a significant but modest reduction in unplanned hospital readmissions, with about one-third of patients still requiring rehospitalization at 1-year follow-up in the contemporary TAVR era. Non-cardiac comorbidities, periprocedural bleeding events, and intensive antithrombotic therapy determined an increased risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".