Abstract 19826: Utility of Stroke Volume Index for Stratification of Patients With Low Gradient Severe Aortic Stenosis and Normal Left Ventricular Ejection Fraction
Bibliographic record
Abstract
Background: Decision of intervention for low gradient severe aortic stenosis (AS) with normal left ventricular ejection fraction (LVEF) is clinically challenging. The study was to determine the impact of stroke volume index (SVi) on prognosis in patients (pts) with AS. Methods: We examined 410 pts with moderate or severe AS and normal EF (≥50%). Pts were divided into four groups based on aortic valve area (AVA), mean pressure gradient (MPG) and SVi: Group I: low flow low gradient severe AS (AVA≤1.0cm 2 , MPG<40mmHg and SVi<35mL/m 2 , n=75); Group II: normal flow low gradient severe AS (AVA≤1.0cm 2 , MPG<40mmHg and SVi≥35mL/m 2 , n=97); Group III: severe AS with matched gradient-AVA (AVA≤1.0cm 2 and MPG≥40mmHg, n=88); Group IV: moderate AS (AVA>1.0cm 2 and MPG>20mmHg, <40 mmHg, n=150). Aortic valve gradients, AVA and SVi were assessed by echocardiography. Clinical charts were reviewed. Mean follow-up duration was 3.2±1.6 years. Results: Group I had higher prevalence of atrial fibrillation, more pronounced LV hypertrophy, lower SVi, smaller AVA, higher valvuloarterial impedance (Zva) (Table) and lower 3-year cumulative survival compared to Group II and Group IV (61% vs. 75% and 80%, p=0.004). Group II had a 3-year cumulative survival similar to moderate AS (75% vs. 80%, p>0.05). In pts with medical management, Group I and Group III had lower 3-year cumulative survival in comparison with Group II and Group IV (48% and 56% vs. 73% and 76%, p=0.001). Multivariate analysis showed SVi was a strong predictor of mortality in low gradient severe AS (HR 0.95, CI: 0.91-0.99, P=0.02). However, in gradient-AVA matched severe AS and moderate AS, SVi was not associated with mortality (p>0.05). Conclusions: Without AS intervention, low flow low gradient severe AS with normal EF carries poor prognosis similar to high gradient AS, but normal flow low gradient AS does not, suggesting that SVi may be used to identify the pts benefiting most from AS intervention in pts with low gradient AS.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
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".