Minimally invasive aortic valve replacement with sutureless and rapid deployment valves: a report from an international registry (Sutureless and Rapid Deployment International Registry)†
Bibliographic record
Abstract
OBJECTIVES: The impact of sutureless and rapid deployment (SURD) valves on the clinical outcomes of patients undergoing minimally invasive aortic valve replacement (MI-AVR) has still to be defined. The aim of this study was to assess clinical characteristics and in-hospital results of patients receiving SURD-AVR through less invasive approaches in the large population of the Sutureless and Rapid Deployment International Registry (SURD-IR). METHODS: Of the 1935 patients who received primary isolated SURD-AVR between 2009 and 2018, a total of 1418 (73.3%) underwent MI interventions and were included in this analysis. SURD-AVR was performed using upper ministernotomy in 56.4% (n = 800) of cases and anterior right thoracotomy in 43.6% (n = 618). Perceval S was implanted in 1011 (71.3%) patients and Edwards Intuity or Intuity Elite in 407 (28.7%) patients. RESULTS: Overall in-hospital mortality and stroke rates were 1.7% and 2%, respectively. A definitive pacemaker implantation was reported in 9% of cases and significantly decreased over the observational period, from 20.6% to 5.6% (P = 0.002). The Perceval valve was associated with shorter operative times and was more frequently implanted in patients receiving anterior right thoracotomy incision. The Intuity valve was preferred in younger patients and revealed superior postoperative haemodynamic results. CONCLUSIONS: SURD-AVR was largely performed through less invasive approaches and can be considered as a primary indication in MI surgery. In the SURD-IR cohort, MI SURD-AVR using both Perceval and Intuity valves appeared a safe and reproducible procedure associated with promising early results.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".