Sutureless Valve in Repeated Aortic Valve Replacement: Results from an International Prospective Registry
Bibliographic record
Abstract
Objective To report early and midterm results registry of patients undergoing repeated aortic valve replacement (RAVR) with sutureless prostheses from an international prospective registry (SURE-AVR). Methods Between March 2011 and June 2019, 69 patients underwent RAVR with self-expandable sutureless aortic bioprostheses at 22 international cardiac centers. Results Overall mortality was 2.9% with a predicted logistic EuroSCORE II of 10.7%. Indications for RAVR were structural valve dysfunction (84.1%) and infective prosthetic endocarditis (15.9%) and were performed in patients with previously implanted bioprostheses (79.7%), mechanical valves (15.9%), and transcatheter valves (4.3%). Minimally invasive approach was performed in 15.9% of patients. Rate of stroke was 1.4% and rate of early valve-related reintervention was 1.4%. Overall survival rate at 1 and 5 years was 97% and 91%, respectively. No major paravalvular leak occurred. Rate of pacemaker implantation was 5.8% and 0.9% per patient-year early and at follow-up, respectively. The mean transvalvular gradient at 1-year and 5-year follow-up was 10.5 mm Hg and 11.5 mm Hg with a median effective orifice area of 1.8 cm 2 and 1.8 cm 2 , respectively. Conclusions RAVR with sutureless valves is a safe and effective approach and provides excellent clinical and hemodynamic results up to 5 years.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".