Hemodynamic Performance of Stentless Versus Stented Valves: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Several trials have compared stentless with stented valves following aortic valve replacement (AVR). The goal of this review was to systematically locate, critically appraise, and quantitatively combine results to determine if stentless valves improve cardiac hemodynamics. METHODS: We performed an unrestricted search of Pubmed Medline, EMBASE, CINAHL, the Cochrane databases, and EBM reviews. Article reference lists and online abstracts from major North American conferences were also searched. We included randomized trials of adults undergoing AVR that compared stentless and stented valves. Blinded reviewers performed assessment of trials for inclusion and trial quality. Two individuals performed data extraction independently. Kappa statistics were used to assess reviewer agreement. A random effects model was employed for statistical analyses. Assessments were made for postoperative, early, and late outcomes. Heterogeneity was explored with sensitivity analyses. RESULTS: Eight studies were identified for inclusion in the primary analysis, with four others included in sensitivity analyses. Baseline comparisons between groups revealed no differences. Our primary analyses revealed no differences between groups for assessments of LV mass or mean transvalvular gradients. Secondary analyses showed stentless valves to have lower peak gradients. Sensitivity analyses were supportive of our primary results. Heterogeneity was observed in some comparisons and sensitivity analyses failed to completely explain this heterogeneity. CONCLUSIONS: Stentless valves did not display hemodynamic benefit in terms of LV mass regression or postoperative mean gradients, but do appear to display superior hemodynamics in terms of peak gradients. Further well-designed and adequately powered trials are required to fully address this question.
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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 | 0.022 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.034 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".