Echocardiographic severity grading in aortic stenosis: no holy grail, only lessons towards patient individualisation
Bibliographic record
Abstract
The term ‘severe aortic stenosis (AS)’ carries a hefty prognostic connotation; it should oblige diligent workup, cautious interval follow-up or intervention on the patient.1 Trained as problem solvers, we aspire to develop a ‘theory of everything’ for diagnosis and management of complex illness, and AS has not escaped our efforts. For example, until recently, a patient with normal left ventricular EF unable to generate a mean gradient (MG) >40 mm Hg (or peak velocity >4 m/s) across a calcified and restricted aortic valve was deemed not to harbour severe AS. We now know that this oversimplification may exclude from potentially life-saving intervention a number of ‘paradoxical low-flow’ patients with substantial AS who despite having a normal EF and MG <40 mm Hg, have the same or worse prognosis as patients who generate the time-honoured ‘cut-off’ gradient.2 Thus, flow-dependent echocardiographic parameters (peak velocity and MG), despite having excellent correlation between them1 and proven prognostic value,3 do not always reflect disease severity. Interestingly, the aortic valve area (AVA), a flow-independent parameter, remains abnormally decreased (<1 cm2) in most of these ‘paradoxical low-flow’ patients, serving as a clue for their diagnosis.4 Paradoxical low-flow is partly to blame for the parameter inconsistencies found in echocardiographic severe-AS grading (defined as MG <40 mm Hg and AVA <1 cm2).5 The prevalence of severe-AS grading inconsistencies has now been studied in over 11 000 patients,1 ,5 and one out of three patients exhibits inconsistent severe-AS grading. However, there are also a significant number of patients without paradoxical low-flow (normal flow) and normal EF who also have ‘discordant’ severe AS1 with MG <40 mm Hg and AVA <1 cm2, and the opposite as …
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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) | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".