Mid-term outcomes of the COMMENCE trial investigating mitral valve replacement using a bioprosthesis with a novel tissue
Bibliographic record
Abstract
Objective: Novel tissue leaflets (RESILIA tissue) may improve durability of bioprosthetic heart valves. The COMMENCE trial is an ongoing prospective study to evaluate valve replacement using RESILIA tissue. This report describes mid-term outcomes in the mitral cohort of COMMENCE. Methods: Adult patients requiring mitral valve replacement were enrolled in a prospective, single-arm trial at 17 sites in the United States and Canada. An independent clinical events committee adjudicated safety events using definitions from established guidelines, and hemodynamic performance was evaluated by an independent echocardiographic core laboratory. Results: Eighty-two patients (median age 70 years) successfully underwent mitral valve replacement with the study valve. Five-year event-free probabilities for all-cause mortality, structural valve deterioration, and reoperation were 79.9%, 98.7%, and 97.1%, respectively. Hemodynamic valve function measurements were stable through the 5-year follow-up period; valvular leaks were infrequently observed and primarily clinically insignificant/mild. Conclusions: Mitral valve replacement patients implanted with a RESILIA tissue bioprosthesis had a good safety profile and clinically stable hemodynamic performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".