Impact of percutaneous closure device type on vascular and bleeding complications after TAVR: A post hoc analysis from the BRAVO‐3 randomized trial
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Prostar XL (PS) and ProGlide (PG) are common vascular closure devices (VCD) used in TAVR via transfemoral vascular approach. The impact of these VCD on vascular and bleeding complications remains unclear. METHODS: The BRAVO-3 trial randomized 802 patients undergoing transfemoral TAVR. We stratified patients according to type of VCD used and examined the 30-day incidence of major or minor vascular complications, major bleeding (BARC ≥3b), AKI and major adverse cardiac and cerebrovascular events (MACCE; death, myocardial infarction or stroke). RESULTS: A total of 746 (93%) patients were treated with either PS (n = 352, 47%) or PG (n = 394, 53%) VCD, without significant differences in successful deployment rate (PS 322 [91.2%] vs. PG 373 [94.2%] respectively, p = .20). PG was associated with a significantly lower incidence of major or minor vascular complications, compared to PS (adjusted OR: 0.54; 95% CI: 0.37-0.80; p < .01). Rates of acute kidney injury were also lower with the PG device. There was no significant difference between bleeding, MACCE, and death. CONCLUSIONS: Compared to PS, the PG VCD was associated with a lower rate of major or minor vascular complications and lower rates of AKI after transfemoral TAVR.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".