Operative outcome of patients at low, intermediate, high and ‘very high’ surgical risk undergoing isolated aortic valve replacement with sutureless and rapid deployment prostheses: results of the SURD-IR registry
Bibliographic record
Abstract
OBJECTIVES: The ideal strategy for the treatment of severe aortic valve stenosis in patients of varying risk categories has become a debated topic in the last years: should the transcatheter or surgical approach be adopted? The aim of this study was to evaluate the outcomes of low-, intermediate-, high- and very high-risk patients undergoing sutureless, rapid deployment aortic valve replacement. METHODS: From 2007 to 2017, data on a total of 3651 patients were collected from the Sutureless and Rapid Deployment Aortic Valve Replacement International Registry (SURD-IR). Of these, 2057 patients who underwent primary isolated aortic valve replacement were considered for this analysis and classified as being at low (EuroSCORE <5; n = 500), intermediate (EuroSCORE 5-10; n = 901), high (EuroSCORE 11-20; n = 500) and very high (EuroSCORE >20; n = 156) preoperative risk. RESULTS: Overall, a less invasive approach was used in 74.1% of patients and represented the most frequent (>50%) approach in all risk categories. The Perceval prosthesis was used more frequently than other devices, especially in patients at high and very high risk. Hospital mortality was 1.6%, 0.8%, 1.9% and 2.7% in low-, intermediate-, high- and very high-risk patients, respectively, with no significant differences among subgroups. Similarly, postoperative complication rates were similar across the different risk categories. CONCLUSIONS: Surgical aortic valve replacement using sutureless, rapid deployment biological valve prostheses is associated with excellent results and represents a safe and effective treatment option for patients with severe aortic valve stenosis. This seems to be particularly true in patients with a higher risk profile.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".