Eight-year hemodynamic follow-up after aortic valve replacement with the Toronto SPV stentless aortic valve.
Bibliographic record
Abstract
The hemodynamic performance of stentless aortic bioprostheses has been well described during the first few months after surgery. The purpose of the present study was to describe the hemodynamic performance of the Toronto SPV valve (St. Jude Medical, Inc, St. Paul, MN) in a multicenter trial through 8 years. The long-term study of the Toronto SPV valve includes 447 consecutive patients from 6 investigative centers. Echocardiographic follow-up was performed at specified intervals, with quantitative analysis performed at a centralized core laboratory. Mean transvalvular gradient decreased significantly between discharge and 6 months, between 6 months and 1 year, and between 1 year and 2 years after surgery, without further significant change. The effective orifice area increased significantly early after surgery and continued to increase through 6-year follow-up. The left ventricular (LV) stroke volume increased progressively from discharge through 6-year follow-up. The LV mass index decreased significantly from discharge through 3 years after surgery and stabilized through 5 years. There was a gradual increase in LV outflow tract diameter between 1 year and 6 years after surgery. The prevalence of any aortic regurgitation (AR) (including trivial) and > or = mild AR increased significantly between discharge and 6-year to 8-year follow-up. However, the prevalence of > or = moderate AR remained very low at 6 years (2.6%) and 8 years (4.5%) after surgery. In conclusion, the Toronto SPV stentless tissue aortic valve is associated with excellent hemodynamics early after surgery and through 8 years after surgery. LV mass decreases early, and returns to within the range of normal by 1 year after surgery. There is evidence of continued LV mass regression involving the LV outflow tract, potentially contributing to a small but significant late improvement in hemodynamics. The prevalence of significant AR remains low through 8 years.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".