Next-day discharge after transcatheter aortic valve replacement in a Dutch hospital
Bibliographic record
Abstract
BACKGROUND: In recent years, hospital stays after transcatheter aortic valve replacement (TAVR) have shortened. Previous studies have shown that next-day discharge (NDD) is feasible without compromising patient safety, but data from the Dutch hospital setting are lacking. To assess the real-world effect of a NDD policy after TAVR. METHODS: A next-day discharge policy was introduced in 2022 at St. Antonius Hospital Nieuwegein, the Netherlands. We included elective TAVR patients between August 2022 and August 2024, excluding those with pre-existing hospitalisation, transapical access, or intraprocedural mortality. RESULTS: Among 460 patients (mean age 80.1 ± 6.2 years, 40.9% female, and a median Edmonton Frail score of 3.0 [1.0-4.0]), the majority underwent transfemoral TAVR (99.1%), under local anaesthesia (97.0%), using self-expanding valves (78.3%). Patients in the NDD group were more often male, less frail, and less likely to have right bundle branch block before TAVR compared to delayed discharge (DD) patients. NDD was feasible in 269 patients (58.5%) with a low number of post-discharge complications at 30 days: 1.9% permanent pacemaker implantation and 2.2% minor vascular complications. There were no cases of mortality, major vascular complications, or in-hospital stroke. Main reasons for DD were conduction disorders, access site complications, and stroke, which contributed to a higher incidence of complications in the DD group (18.3% permanent pacemaker implantation, p < 0.001, 3.1% stroke, p = 0.004, 1.6% major vascular complication, overall p-value 0.02). CONCLUSION: After implementing an NDD policy, 58.5% of patients were eligible for NDD after TAVR with a very low post-discharge complication rate.
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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 | 0.000 | 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) | 0.001 | 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".