Clinical value of stress transaortic flow rate during dobutamine echocardiography in low-gradient aortic stenosis
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: None. BACKGROUND/INTRODUCTION The clinical value of rest transaortic flow rate (FR) has been shown previously in low-gradient aortic stenosis (LGAS) for the prediction of outcome. However limited data exists on the prognostic value of stress FR in LGAS following low-dose dobutamine stress echocardiography (LDDSE). PURPOSE We aimed to assess the value of stress FR in patients with LGAS in the diagnosis of AS severity and the prediction of mortality. METHODS This is a multi-centre cohort study of patients with low left ventricular ejection fraction (LVEF) and LGAS (aortic valve area –AVA <1cm²) who underwent LDDSE. RESULTS Of the 287 patients (mean age: 75.1 ±10 years, males: 71%) over the mean follow-up of 24 ±30 months there were 127 (44.3%) deaths and 147 (51.2%) patients underwent aortic valve intervention. Lower stress FR was independently associated with increased risk of mortality (HR= 0.99, 95%CI= 0.99-0.999, p= 0.02) after adjusting for age, chronic kidney disease, presence of symptoms (NYHA II-IV), aortic valve intervention, rest LVEF and guideline-defined severe AS (AV mean gradient- AVMG ≥40mmHg with AVA <1cm² at peak stress). The minimum cut-off for prediction of mortality was stress FR 210ml/sec. Among the different criteria of AS severity during stress, i.e. guideline-defined criterion, or stress AVMG ≥40mmHg, or stress AVA <1cm² at stress FR ≥210ml/s, only the latter was independently associated with mortality (HR= 1.81, 95%CI= 1.04-3.2, p= 0.04) (Table 1) and was the parameter of AS severity that predicted improved outcome following aortic valve intervention (p <0.005) (Figure 1). Guideline-defined stroke volume flow reserve did not predict mortality. CONCLUSIONS Assessment of stress FR during LDDSE is important for the detection of both AS severity and flow reserve. Table 1 Multivariable analysis for prediction of all-cause mortality (N = 287) for the different criteria of aortic stenosis HR 95%CI p Age 1 0.98-1.03 0.84 Chronic kidney disease 1..84 1.13-2.99 0.01 Aortic valve intervention 0.37 0.22-0.61 <0.005 Presence of symptoms (NYHA II-IV) 1.87 0.66-5.31 0.24 Rest LVEF (by 1%) increase 0.97 0.95-1 0.06 Stress AVA < 1cm² with stress AVMG≥40mmHg 1.02 0.31-3.34 0.97 Stress AVMG≥40mmHg 0.57 0.2-1.59 0.28 Stress AVA < 1cm² at stress FR≥210mmHg 1.81 1.04-3.2 0.04 Abstract Figure 1
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".