Aortic Valve Neocuspidization (Ozaki Procedure) in Patients with Small Aortic Annulus (≤21 mm): A Multicenter Study
Bibliographic record
Abstract
Background Patients with aortic stenosis (AS) and small aortic annulus (SAA) who undergo surgical aortic valve replacement (SAVR) are more likely to receive smaller prostheses, predisposing them to prosthesis patient-mismatch (PPM). Since the Ozaki Procedure (aortic valve neocuspidization – AVNeo) has proved promising, we aimed to assess its immediate results in this scenario. Methods AVNeo was performed in 106 consecutive patients from January 2017 to March 2019 at three centers. The records were prospectively collected and reviewed retrospectively. Most of the patients were older than 60 years and 97.2% had AS. Preoperative echocardiography showed an average peak pressure gradient of 64.9 ± 20.7 mmHg and a mean pressure gradient of 46.0 ± 12.2 mm Hg for patients with AS and an annular diameter of 19.8 ± 1.1 mm for all patients. EOA and indexed EOA (iEOA) averaged 0.7 ± 0.2 cm 2 and 0.4 ± 0.2 cm 2 /m 2 before surgery, respectively. Results There was no conversion to SAVR. Four patients needed reoperation for bleeding, but none needed reoperation due to early infective endocarditis. Median intensive care unit and hospital length of stay were 1.5 ± 1.2 and 13.7 ± 5.1 days, respectively. There were two in-hospital deaths due to non-cardiac causes. Postoperative peak pressure gradient averaged 11.8 ± 5.9 mmHg and mean pressure gradient averaged 7.3 ± 3.5 mmHg, which means statistically significant average decreases of 58.1 and 38.7 mmHg, respectively. Postoperative EOA and iEOA averaged 2.5 ± 0.4 cm 2 and 1.3 ± 0.3 cm 2 /m 2 , which means statistically significant average increases of 1.8 cm 2 and 0.9 cm 2 /m 2 , respectively. Conclusions AVNeo is feasible and reproducible with good immediate results. Our findings show that AVNeo produces immediate postoperative low-pressure gradients, larger EOA, and minimal regurgitation of the aortic valve.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".