Assessment of aortic stenosis severity: when the gradient does not fit with the valve area: Figure 1
Bibliographic record
Abstract
In this issue of Heart , Minners et al 1 ( see page 1463 ) provide an extension of their previous work2 where they retrospectively analysed the data of their Doppler-echocardiography laboratory and reported that there is a discrepancy in the criteria of aortic valve area (AVA; 40 mm Hg) proposed in the guidelines to define severe aortic stenosis (AS).2 In the present study1 they present data obtained by cardiac catheterisation in a subset of the previous series.2 The main findings of this study are: (1) when using the framework of the current guidelines, inconsistent grading of AS (ie, AVA <1.0 cm2 but gradient ≤40 mm Hg) occurred in 36% of patients with preserved left ventricular (LV) systolic function (LV ejection fraction (LVEF) ≥50%), and this proportion was similar irrespective of the method used to assess stenosis severity (ie, Doppler-echocardiography vs cardiac catheterisation); and (2) the proportion of patients with reduced stroke volume (stroke volume index ≤35 ml/m2) despite apparently normal LV systolic function was substantially higher in the subset of patients with inconsistent grading (52%) than in those with consistent grading (29%). This latter finding lends further support to the concept that discordance between AVA and gradient is often due to paradoxical low-flow AS, a disease pattern recently described by our group.3 We indeed reported that an important proportion of patients with severe AS may paradoxically have a low flow and thus often a low gradient, despite the presence of normal LVEF.3 When compared with patients with normal LV outflow, patients with paradoxical low flow are characterised by a higher prevalence of women and concomitant hypertension, older age, a higher degree of LV concentric remodelling, impaired LV filling, smaller end-diastolic volume and reduced mid-wall and longitudinal shortening. These patients also have markedly increased global …
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".