P5356Left atrial deformation in patients with moderate to severe aortic stenosis and heart failure
Bibliographic record
Abstract
Background: Presence of heart failure (HF) in patients with moderate to severe aortic stenosis (AS) is related to diastolic dysfunction. Left atrial (LA) deformation, a novel technique, may be more closely associated with HF than E/e' ratio. The aim of this study was to compare the association of both methods with the presence of HF in patients with AS. Methods: 71 patients with moderate to severe AS (<1.5cm2) and preserved left ventricular (LV) ejection fraction were included. The presence of HF was defined as NYHA≥2 and NT-proBNP≥360pg/mL. LA deformation was evaluated using speckle tracking analysis. Functional capacity was assessed using 6-minute walk test distance and 5 meters gait speed. Results: Patients with HF were significantly older (78±6 vs 67±13, p=0.001) with higher NT-proBNP level (954±833 vs 219±269pg/mL, p<0.001). AS severity, LV function or E/e' ratio were not associated with HF (Table 1). LA late diastolic strain, systolic and early and late diastolic strain rates (contractile, reservoir and conduit function) were significantly worse in HF patients. Patients with HF walked a significantly shorter 6-minute walk distance compared to asymptomatic (Δ 64m, p=0.020) with a significantly slower 5 meters gait speed (1.5±0.6 vs 2.0±0.8m/s, p=0.007). Statistically significant correlations were found between LA systolic strain and NT-proBNP (r=-0.388, p=0.002), 6-minute walk test distance (r=0.420, p=0.001) and 5 meters gait speed (r=0.420, p=0.001).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".