Usefulness of Aortic Valve Calcification in Patients With Low-Flow Aortic Stenosis
Bibliographic record
Abstract
BACKGROUND: Aortic valve calcification (AVC) has been shown to be a powerful assessment of aortic stenosis (AS) severity and a predictor of adverse outcomes. However, its accuracy in patients with low-flow AS has not yet been proven. The objective of the study was to assess the predictive value of AVC in patients with classical low-flow (CLF, that is, low-flow reduced left ventricular ejection fraction) or paradoxical low-flow (PLF, that is, low-flow preserved left ventricular ejection fraction) AS. METHODS: We prospectively included 641 patients, 319 (49.8%) with CLF-AS and 322 (50.2%) with PLF-AS, who underwent Doppler echocardiography and multidetector computed tomography. AVC ratio (AVCratio) was calculated as AVC divided by the sex-specific AVC threshold for AS severity; AVC score ≥2000 Agatston units in male patients and ≥1200 Agatston units in female patients. The primary end point of the study was all-cause mortality regardless of treatment. RESULTS: Sex-specific AVC thresholds identified AS severity correctly in 137 (87%) of the patients. During a median follow-up of 4.9 (4.3–5.9) years, there were 265 deaths. After comprehensive adjustment, AVCratio was associated with all-cause mortality in patients with CLF-AS (adjusted hazard ratio, 1.25 [95% CI, 1.01–1.56]; P =0.046) and PLF-AS (adjusted hazard ratio, 1.51 [95% CI, 1.14–2.00]; P =0.004). There was an interaction ( P =0.001) between AVC and AS flow patterns (ie, CLF versus PLF) with regard to the prediction of mortality. The best AVCratio threshold to predict mortality was different in patients with CLF-AS (AVCratio ≥0.7) and PLF-AS (AVCratio ≥1). After a comprehensive analysis, AVCratio as a dichotomic variable was associated with all-cause mortality in all groups ( P ≤0.001). The addition of AVCratio to the models improved all models’ predictive value (all net reclassification index >18%; all P ≤0.05). CONCLUSIONS: In patients with CLF-AS or PLF-AS, AVC is a major predictor of mortality. Thus, AVC should be used in low-flow patients to assess AS severity and stratify risk. Importantly, in patients with reduced left ventricular ejection fraction, a nonsevere AS (ie, AVC 70% of severe) could be associated with reduced survival.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".