Low-flow, Low-gradient Severe Aortic Stenosis: A Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Aortic stenosis (AS) is a common valve pathology experienced by patients worldwide. There are limited population-based studies assessing its prevalence; however, epidemiological studies emphasize that the burden of disease is growing. Recognizing AS relies on accurate clinical assessment and diagnostic investigations. Patients who develop severe AS are often referred to the heart team for assessment of aortic valve intervention. Although echocardiography has traditionally been used to screen and monitor the progression of AS, there can be discordance between measurements in a low-flow state. Such patients may have truly severe AS and potentially derive long-term benefit from aortic valve intervention. Accurately identifying these patients with the use of ancillary testing has been the focus of research for several years. In this article, we discuss the contemporary approaches and challenges in identifying and managing patients with low-flow, low-gradient severe AS.
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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) | 0.002 | 0.004 |
| 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) | 0.001 | 0.005 |
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 it