6099Impact of aortic valve replacement on outcomes of patients with low-flow, low-gradient moderate aortic stenosis
Bibliographic record
Abstract
Abstract Background Aortic valve replacement (AVR) is recommended for patients with low-flow, low-gradient (LFLG) and true-severe aortic stenosis (TSAS). However, there is very few data on the potential benefit of AVR in patients with LFLG pseudo-severe (i.e. moderate) AS (PSAS). Methods Consecutive patients with aortic valve area ≤0.6 cm2/m2, mean gradient <40 mmHg were prospectively recruited in a multicenter observational cohort study. The patients were categorized in TSAS vs. PSAS using previously reported thresholds of flow-independent parameters of AS severity (projected valve area at normal flow rate ≤1.0 cm2 and/or aortic valve calcium score by CT >1200 AU in women and >2000 AU in men). To account for between-treatment-group differences, inverse probability-of-treatment weighting was combined to Cox proportional hazards regression. Results Among the 430 patients included in this study, 297 (69%) were classified as TSAS and 274 (57%) underwent AVR. Of note, 21% of the patients treated by AVR were classified as PSAS. In patients managed conservatively (ConsRx), 52% had PSAS and 48% TSAS. During a median follow-up of 28 months [8–60], 198 patients died. The adjusted weighted hazard ratio (awHR) of death associated with AVR as compared to ConsRx was 0.42 [0.24–0.73] (p<0.0001, Figure1-Panel-A). This survival benefit associated with AVR was observed not only in patients with TSAS but also in those with PSAS (awHR: 0.29 [0.12–0.70]; p=0.006, Figure1-Panel-B). Figure 1 Conclusion The results of this study suggest that AVR is associated with a survival benefit not only in LFLG patients with TSAS but also in those with PSAS. Randomized trials are needed to confirm the benefit of AVR in patients with moderate AS and depressed LV systolic function. Acknowledgement/Funding Canadian Institute of Health Research
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".