Predictors of Mortality and Outcomes of Therapy in Low-Flow Severe Aortic Stenosis
Bibliographic record
Abstract
BACKGROUND: The prognosis and treatment of patients with low-flow (LF) severe aortic stenosis are controversial. METHODS AND RESULTS: The Placement of Aortic Transcatheter Valves (PARTNER) trial randomized patients with severe aortic stenosis to medical management versus transcatheter aortic valve replacement (TAVR; inoperable cohort) and surgical aortic valve replacement versus TAVR (high-risk cohort). Among 971 patients with evaluable echocardiograms (92%), LF (stroke volume index ≤35 mL/m(2)) was observed in 530 (55%); LF and low ejection fraction (<50%) in 225 (23%); and LF, low ejection fraction, and low mean gradient (<40 mm Hg) in 147 (15%). Two-year mortality was significantly higher in patients with LF compared with those with normal stroke volume index (47% versus 34%; hazard ratio, 1.5; 95% confidence interval, 1.25-1.89; P=0.006). In the inoperable cohort, patients with LF had higher mortality than those with normal flow, but both groups improved with TAVR (46% versus 76% with LF and 38% versus 53% with normal flow; P<0.001). In the high-risk cohort, there was no difference between TAVR and surgical aortic valve replacement. In patients with paradoxical LF and low gradient (preserved ejection fraction), TAVR reduced 1-year mortality from 66% to 35% (hazard ratio, 0.38; P=0.02). LF was an independent predictor of mortality in all patient cohorts (hazard ratio, ≈1.5), whereas ejection fraction and gradient were not. CONCLUSIONS: LF is common in severe aortic stenosis and independently predicts mortality. Survival is improved with TAVR compared with medical management and similar with TAVR and surgical aortic valve replacement. A measure of flow (stroke volume index) should be included in the evaluation and therapeutic decision making of patients with severe aortic stenosis. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrial.gov. Unique identifier: NCT0053089.4.
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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) | 0.000 | 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) | 0.000 | 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".