Aortic Valve Replacement vs Clinical Surveillance in Asymptomatic Severe Aortic Stenosis
Bibliographic record
Abstract
BACKGROUND: Current guidelines recommend a strategy of clinical surveillance (CS) for patients with asymptomatic severe aortic stenosis (AS) and a normal left ventricular ejection fraction. OBJECTIVES: The aim of this study was to conduct a study-level meta-analysis of randomized controlled trials (RCTs) evaluating the effect of early aortic valve replacement (AVR) compared with CS in patients with asymptomatic severe AS. METHODS: Studies were quantitatively assessed in a meta-analysis using random-effects modeling. Prespecified outcomes included all-cause and cardiovascular mortality, unplanned cardiovascular or heart failure (HF) hospitalization, and stroke. The meta-analysis is registered at the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY202490002). RESULTS: = 50%; P = 0.23) were observed with early AVR compared with CS, although there was a high degree of heterogeneity among studies. CONCLUSIONS: In this meta-analysis of 4 RCTs, early AVR was associated with a significant reduction in unplanned cardiovascular or HF hospitalization and stroke and no differences in all-cause and cardiovascular mortality compared with CS.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.015 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".