Bibliographic record
Abstract
PURPOSE OF REVIEW: Valve replacement improves symptoms and survival in symptomatic severe aortic stenosis. Low-flow, low-gradient aortic stenosis, however, is an especially challenging subset as valve replacement has a significant risk, and may fail to alleviate symptoms or improve left ventricular function. This article reviews the potential problems in evaluating aortic stenosis severity in low-flow, low-gradient aortic stenosis, the utility of dobutamine challenge to identify patients most likely to benefit from surgery, and the factors predicting patient outcome. RECENT FINDINGS: Low-flow, low-gradient aortic stenosis consists of a heterogeneous group of patients with 'true' severe aortic stenosis, in whom afterload mismatch results from a severely stenotic valve; and 'pseudo-severe' aortic stenosis, where the valve is only mildly or moderately stenotic, but appears severe due to limitations in determining disease severity under low-flow conditions. Valve replacement is likely to benefit the former group, but may have little benefit to the latter. Dobutamine challenge can distinguish 'true' and 'pseudo-severe' aortic stenosis, and can evaluate contractile reserve, one of the strongest predictors of patient outcome. Strategies to avoid prosthesis-patient mismatch should be considered to optimize postoperative outcome. SUMMARY: Dobutamine challenge can identify low-flow, low-gradient aortic stenosis patients most likely to benefit from valve replacement and provides important prognostic information on the operative risks and long-term outcome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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 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".