The Aortic Magna Ease Bioprosthesis: Exploring Hemodynamic Performance Across Sexes and Prosthesis Sizes
Bibliographic record
Abstract
Objective This study aims to assess the incidence of prosthesis–patient mismatch (PPM), the hemodynamic performance, as well as the clinical outcomes of the Carpentier-Edwards Magna Ease (CEME) bioprosthesis in the aortic position while addressing sex-based disparities and variations in valve size. Methods Between 2012 and 2022, 1062 patients underwent an AVR with a CEME bioprosthesis in two high-volume cardiac surgery centers. Predicted PPM was assessed using manufacturer and Lancellotti et al. chart values, alongside measured values. Echocardiographic measurements were evaluated over a 5-year period. Results Predicted PPM based on the manufacturer chart was noted in 2.1% of women and 0.28% of men ( P < .001). When employing definitions by Lancellotti et al., PPM was detected in 45% of females and 18% of males ( P < .001). Notable differences were observed in terms of severe measured PPM in favor of male patients (F: 30%, M: 17%, P < .01). Regarding prosthesis sizes, the comparison of PPM from the manufacturer's chart with Lancellotti et al. values revealed significant disparities: 2% versus 58% in the 19 to 21 mm group, 0.27% versus 13% in the 23 mm group, and 0% versus 1.1% in the ≥25 mm valve sizes ( P < .001). Measured severe PPM was encountered in 30% of patients with 19 to 21 mm prosthesis, 20% in the 23 mm group and 12% in the >25 mm prosthesis. Despite these differences, mortality rates remained comparable across sexes and valve sizes. Conclusion Female patients and those with 19 to 21 mm prostheses experience more severe PPM compared to men or individuals with larger valves. In this contemporary cohort, PPM does not impact short-term mortality.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".