Benefits and Pitfalls of the Perceval Sutureless Bioprosthesis
Bibliographic record
Abstract
Objective: To highlight the main target points covered by clinical studies on the Perceval sutureless valve for surgical aortic valve replacement (SAVR) and raise a point of discussion for further expansion of its use when compared with stented bioprostheses (SB) and transcatheter aortic valve replacement (TAVR). Methods: We reviewed clinical trials and retrospective studies published up to date and compared the outcomes in terms of mortality, myocardial infarction (MI) stroke, paravalvular leak (PVL), permanent pacemaker implantation (PPI), bleeding and long-term outcomes. Results: Clinical studies showed that 30-day mortality ranged from 0–4% for Perceval and 2.9–7% for TAVR. The incidence of PVL (Perceval 1.9–19.4 vs. TAVR 9–53.5%), PPI (Perceval 2–11.2 vs. TAVR 4.9–25.5%), stroke (Perceval 0 vs. TAVR 0–2.8%), MI (Perceval 0 vs. TAVR 0–3.5%), were all higher in the TAVR group. Compared to other SB, mortality ranged from 0–6.4% for Perceval and 0–5.9% for SB. The incidence of PVR (Perceval 1–19.4 vs. SB 0–1%), PPI (Perceval 2–10.7 vs. SB 1.8–8.5%), stroke (Perceval 0–3.7 vs. SB 1.8–7.3%) and MI (Perceval 0–7.8 vs. SB 0–4.3%) were comparable among the groups. In patients with a bicuspid aortic valve, mortality rate was (0–4%) and PVL incidence was (0–2.3%). However, there was a high incidence of PPI (0–20%), and stroke (0–8%). Long-term survival ranged between 96.7–98.6%. Conclusions: The Perceval bioprosthesis has proved to be a reliable prosthesis for surgical aortic valve replacement due to its implantation speed, the reduced cardiopulmonary bypass time, the reduced aortic cross-clamp time and the shorter intensive care unit and hospital 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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".