Durability of bioprosthetic aortic valves in patients under the age of 60 years – rationale and design of the international INDURE registry
Bibliographic record
Abstract
BACKGROUND: There is an ever-growing number of patients requiring aortic valve replacement (AVR). Limited data is available on the long-term outcomes and structural integrity of bioprosthetic valves in younger patients undergoing surgical AVR. METHODS: The INSPIRIS RESILIA Durability Registry (INDURE) is a prospective, open-label, multicentre, international registry with a follow-up of 5 years to assess clinical outcomes of patients younger than 60 years who undergo surgical AVR using the INSPIRIS RESILIA aortic valve. INDURE will be conducted across 20-22 sites in Europe and Canada and intends to enrol minimum of 400 patients. Patients will be included if they are scheduled to undergo AVR with or without concomitant root replacement and/or coronary bypass surgery. The primary objectives are to 1) determine VARC-2 defined time-related valve safety at one-year (depicted as freedom from events) and 2) determine freedom from stage 3 structural valve degeneration (SVD) presenting as morphological abnormalities and severe haemodynamic valve degeneration at 5 years. Secondary objectives include the assessment of the haemodynamic performance of the valve, all stages of SVD, potential valve-in-valve procedures, clinical outcomes (in terms of New York Heart Association [NYHA] function class and freedom from valve-related rehospitalisation) and change in patient quality-of-life. DISCUSSION: INDURE is a prospective, multicentre registry in Europe and Canada, which will provide much needed data on the long-term performance of bioprosthetic valves in general and the INSPIRIS RESILIA valve in particular. The data may help to gather a deeper understanding of the longevity of bioprosthetic valves and may expand the use of bioprosthetic valves in patients under the age of 60 years. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03666741 (registration received September, 12th, 2018).
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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 | 0.032 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".