Clinical and Echocardiographic Correlates of Plasma B-type Natriuretic Peptide Levels in Patients with Aortic Valve Stenosis and Normal Left Ventricular Ejection Fraction
Bibliographic record
Abstract
BACKGROUND: Several studies suggest that BNP testing may help define the timing of aortic valve surgery in patients with aortic valve stenosis (AVS) prior onset of overt LV systolic dysfunction. The aim of this study was to identify clinical and echocardiographic correlates of plasma BNP levels in a large cohort of patients with AVS and preserved LV ejection fraction. METHOD AND RESULTS: One hundred thirty-five consecutive patients were prospectively included in the present study (Mean age 73 ± 13 years old, 66 (49%) male). Eighty-nine patients (66%) had severe AVS (aortic valve area <0.6 cm(2) /m(2) BSA). Plasma BNP levels, clinical and comprehensive Doppler echocardiography evaluation was performed in all patients. Independent clinical correlates of plasma BNP levels (R(2) = 0.19) were older age (P < 0.0001) and presence of AVS symptoms (P = 0.004). Independent echocardiographic correlates of plasma BNP levels (R(2) = 0.38) were E/Ea ratio (P = 0.01), LV mass index (P = 0.018), left atrial surface (P < 0.0001) and systolic pulmonary artery pressure (sPAP; P = 0.004). Overall, independent correlates of plasma BNP levels (R(2) = 0.47) were older age (P = 0.001), known coronary artery disease (P = 0.047), increased LV mass index (P = 0.001), left atrial enlargement (P = 0.002), and increased sPAP (P = 0.003). CONCLUSIONS: In patients with AVS and normal LV ejection fraction, plasma BNP predominantly reflects the clinical and echocardiographic consequences of afterload burden imposed on the left ventricle rather than the severity of valve stenosis, per se.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".