A novel echocardiographic hemodynamic index for predicting outcome of aortic stenosis patients following transcatheter aortic valve replacement
Bibliographic record
Abstract
OBJECTIVE: Transcatheter aortic valve replacement (TAVR) reduces left ventricular (LV) afterload and improves prognosis in aortic stenosis (AS) patients. However, LV afterload consists of both valvular and arterial loads, and the benefits of TAVR may be attenuated if the arterial load dominates. We proposed a new hemodynamic index, the Relative Valve Load (RVL), a ratio of mean gradient (MG) and valvuloarterial impedance (Zva), to describe the relative contribution of the valvular load to the global LV load, and examined whether RVL predicted patient outcome following TAVR. METHODS: A total of 258 patients with symptomatic severe AS (indexed aortic valve area (AVA)<0.6cm2/m2, AR≤2+) underwent successful TAVR at the University of Ottawa Heart Institute and had clinical follow-up to 1-year post-TAVR. Pre-TAVR MG, AVA, percent stroke work loss (%SWL), Zva and RVL were measured by echocardiography. The primary endpoint was all cause mortality at 1-year post TAVR. RESULTS: There were 53 deaths (20.5%) at 1-year. RVL≤7.95ml/m2 had a sensitivity of 60.4% and specificity of 75.1% for identifying all cause mortality at 1-year post-TAVR and provided better specificity than MG<40 mmHg, AVA>0.75cm2, %SWL≤25% and Zva>5mmHg/ml/m2 despite equivalent or better sensitivity. In multivariable Cox analysis, RVL≤7.95ml/m2 was an independent predictor of all cause mortality (HR 3.2, CI 1.8-5.9; p<0.0001). RVL≤7.95ml/m2 was predictive of all cause mortality in both low flow and normal flow severe AS. CONCLUSIONS: RVL is a strong predictor of all-cause mortality in severe AS patients undergoing TAVR. A pre-procedural RVL≤7.95ml/m2 identifies AS patients at increased risk of death despite TAVR and may assist with decision making on the benefits of TAVR.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".