Prognostic value of aortic valve calcification in non-severe aortic stenosis with preserved ejection fraction
Bibliographic record
Abstract
AIMS: Aortic valve calcification (AVC) is prognostic in patients with aortic stenosis (AS). We assessed the AVC prognostic value in non-severe AS patients. METHODS AND RESULTS: We conducted a retrospective study of 395 patients with non-severe AS, LVEF ≥ 50%. The Agatston method was used for CT AVC assessment. The log-rank test determined the best AVC cut-offs for survival under medical surveillance: 1185 arbitrary unit (AU) in men and 850 AU in women, lower than the established cut-offs for severe AS (2064 AU in men and 1274 AU in women). Patients were divided into 3 AVC groups based on these cut-offs: low (<1185 AU in men and <850 AU in women), sub-severe (1185-2064 AU in men and 850-1274 AU in women), and severe (>2064 AU in men and >1274 AU in women). Of 395 patients (mean age 73 ± 12 years, 60.5% men, aortic valve area 1.23 ± 0.30 cm2, mean pressure gradient 28 ± 8 mmHg), 218 underwent aortic valve intervention (AVI) and 158 deaths occurred during follow-up, 82 before AVI. Median survival time under medical surveillance was 2.1 (0.7-4.9) years. Compared with the low AVC group, both sub-severe and severe AVC groups had higher risk for all-cause death under medical surveillance after comprehensive adjustment including echocardiographic AS severity and coronary artery calcium score (all P ≤ 0.006); while mortality risk was similar between sub-severe and severe AVC groups (all P ≥ 0.2). This mortality risk pattern persisted in the overall survival analysis after adjustment for AVI. AVI was protective of all-cause death in the sub-severe and severe AVC (all P ≤ 0.01), but not in the low AVC groups. CONCLUSION: Sub-severe AVC is a robust risk stratification parameter in patients with non-severe AS and may inform AVI timing.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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".