Early and Long-Term Clinical and Echocardiographic Outcomes of Sutureless vs. Sutured Bioprosthesis for Aortic Valve Replacement
Bibliographic record
Abstract
Objective: The goal of this manuscript is to compare clinical and echocardiographic outcomes of patients undergoing aortic valve replacement (AVR) with Perceval sutureless bioprosthesis (SU-AVR) and sutured bioprosthesis (SB). Methods: Following the PRISMA statement, data were extracted from studies published after August 2022 and found in PubMed/MEDLINE, EMBASE, CENTRAL/CCTR, ClinicalTrials.gov, SciELO, LILACS, and Google Scholar. The primary outcome of interest was post-procedural permanent pacemaker implantation, and the secondary outcomes were new left bundle branch block (LBBB), moderate/severe paravalvular leak (PVL), valve dislocation (pop-out), need for a second transcatheter heart valve, 30-day mortality, stroke, and echocardiographic outcomes. Results: Twenty-one studies were included in the analysis. When SU-AVR was compared to other SB, mortality ranged from 0 to 6.4% for Perceval and 0 to 5.9% for SB. Incidence of PVL (Perceval 1–19.4% vs. SB 0–1%), PPI (Perceval 2–10.7% vs. SB 1.8–8.5%), and MI (Perceval 0–7.8% vs. SB 0–4.3%) were comparable. In addition, the stroke rate was lower in the SU-AVR group when compared to SB (Perceval 0–3.7% vs. SB 1.8–7.3%). In patients with a bicuspid aortic valve, the mortality rate was 0–4% and PVL incidence was 0–2.3%. Long-term survival ranged between 96.7 and 98.6%. Valve cost analysis was lower for the Perceval valve and higher for sutured bioprosthesis. Conclusions: Compared to SB valves, Perceval bioprosthesis has proved to be a reliable prosthesis for surgical aortic valve replacement due to its non-inferior hemodynamics, implantation speed, reduced cardiopulmonary bypass time, reduced aortic cross-clamp time, and shorter length of stay.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".