Hemodynamic performance of the St. Jude Medical Epic Supra aortic stented valve.
Bibliographic record
Abstract
BACKGROUND AND AIM OF THE STUDY: The study aim was to evaluate the hemodynamic performance of the St. Jude Medical Epic Supra bioprosthesis during the early six-month follow up period, and to confirm the safety and efficacy of the valve by collecting details of adverse events and NYHA functional classification. METHODS: Fifty-seven patients undergoing aortic valve replacement (AVR) with the Epic Supra valve between September 2007 and January 2009 at three centers in Canada were evaluated for the study. The subjects were monitored preoperatively, at discharge, and at six months postoperatively. Echocardiographic data were available from 50 subjects at the six-month follow up. In order to prevent observer variability, all echocardiograms were sent to an independent Echocardiography Core Laboratory (ECL) for interpretation of the data. RESULTS: The mean subject age was 74 years. Concomitant coronary artery bypass grafting (CABG) was performed in 44% of the procedures. The mean pressure gradients were 11.2, 12.5, 10.8, 8.4 and 11.3 mmHg, respectively, for valves sized 19 mm (n = 2), 21 mm (n = 20), 23 mm (n = 22), 25 mm (n = 5) and 27 mm (n = 1). The average effective orifice areas (EOAs) were 1.44, 1.57, 1.69, 1.93 and 1.81 cm2 for the .valves sized 19, 21, 23, 25 and 27 mm, respectively. CONCLUSION: The results of the six-month echocardiographic follow up indicated that the Epic Supra valve offered excellent hemodynamic performance in the 21, 23 and 25 mm sizes. However, additional data are still required for the 19 and 27 mm valves to characterize their performance. The mean gradients and EOA-values were comparable to those of other supra-annular stented tissue valves. The EOA index indicated an absence of prosthesis-patient mismatch, with values in all subjects at or near 0.85 cm2/m2. The percentage of subjects without aortic insufficiency (AI) at follow up was 92%; only four subjects showed trivial AI.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".