Smaller Bioprosthetic Valves May Be Associated with Worse Clinical Outcomes and Reduced Freedom from Reoperation in sAVR
Bibliographic record
Abstract
BACKGROUND: Surgical bioprosthetic aortic valve replacement is a ubiquitous procedure, with several factors identified in affecting outcomes. We hypothesize that smaller valves may be associated with worse outcomes and decreased freedom from clinical events, and a shift in implanting larger valves whenever possible may confer benefit to the patient. METHODS: A narrative review of the literature was conducted using a systematic search strategy to evaluate studies examining the relationship between bioprosthetic valve size and outcomes. Inclusion criteria focused on studies reporting paired data on valve size and clinical endpoints in surgical AVR. RESULTS: Among the 15 reviewed studies, smaller valve sizes were consistently associated with higher post-operative transvalvular gradients (6/7 studies) and increased reintervention rates (5/8 studies). Associations with accelerated structural valve degeneration (SVD) (3/5 studies) and reduced survival (8/11 studies) were also observed, although heterogeneity in study design and follow-up durations limited definitive conclusions. CONCLUSION: Our findings suggest that larger valve sizes may improve freedom from SVD, reduce reintervention rates, and enhanced survival. This may also justify the slight increased risk of enlarging the aortic root to accommodate a larger bioprosthetic valve prosthesis. Further high-quality, controlled studies are needed to clarify the independent impact of valve size on long-term outcomes and guide surgical decision-making.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| 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".