Determinants of symptoms and exercise capacity in aortic stenosis: a comparison of resting haemodynamics and valve compliance during dobutamine stress
Bibliographic record
Abstract
AIMS: Valve compliance might determine the onset of symptoms better than resting measures of aortic stenosis. This study compared valve compliance measured by dobutamine stress echocardiography with resting haemodynamic variables against the end-point of symptoms at low workload during exercise testing. METHODS AND RESULTS: Echocardiography was performed at rest and during each stage of a dobutamine stress test in 65 asymptomatic patients with moderate or severe aortic stenosis. Each patient also completed a modified Bruce treadmill exercise test. During dobutamine stress, peak transaortic velocity increased by 1.0 (0.4) m/s and effective orifice area by 0.25 (0.22) cm(2). Valve compliance was 0.23 (0.10) cm(2)/100ml.s(-1), and was independent of baseline effective orifice area. In the 19 patients limited by symptoms on exercise testing, valve compliance was significantly lower (0.19 (0.09) cm(2)/100ml.s(-1)) than in those who remained asymptomatic (0.25 (0.10) cm(2)/100ml.s(-1), p=0.03). Effective orifice area at peak stress was also lower (1.0 (0.3) vs 1.2 (0.4) cm(2), p=0.03), but there were no significant differences in resting measures of effective orifice area, transaortic velocity, or mean pressure drop. CONCLUSIONS: Effective orifice area is flow-dependent in patients with moderate and severe aortic stenosis with preserved left ventricular function. Exertional symptoms are better predicted by compliance than resting effective orifice area, mean pressure drop or peak transaortic velocity.
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 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 | 0.000 | 0.003 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".