Abstract 12935: Lack of Correlation Between Echocardiographic Parameters and Cardiac Hemodynamics in Patients With Severe Aortic Stenosis
Bibliographic record
Abstract
Introduction: Aortic stenosis (AS) affects ~10% of population over 65 years of age. Severe AS is defined as mean trans-aortic pressure gradient (MG) of ≥40 mmHg and/or aortic valve area (AVA) of <1.0 cm 2 . Patients’ symptoms correlate with cardiac output, and the ability to augment with exercise. However, the relationship between AVA/MG and stroke volume/cardiac output is not well defined. Hypothesis: We aimed to identify the relationship between conventional echocardiography-based parameters (i.e., AVA/MG) and non-echocardiography-based hemodynamics in AS. Methods: Consecutive patients with severe symptomatic AS undergoing TAVI between June and September 2020 at St. Boniface Hospital in Manitoba, Canada were recruited. Hemodynamics was measured using whole-body impedance-based Non-Invasive Cardiac System (NICaS). Evaluated hemodynamics include stroke volume index (Svi), cardiac output (CO), cardiac index (CI), and total peripheral resistance (TPR) and were compared to conventional parameters. Results: Thirty patients (37% females; mean age 79.0 ± 1.7 years) were enrolled. Average MG was 41.8 ± 2.2 mmHg (16.94 - 70.0) and mean AVA was 0.81 ± 0.04 cm 2 (0.30 - 1.10). A linear regression model revealed a poor correlation between AVA and both Svi and CI (r 2 =0.012 and 0.025, respectively). Similarly, MG correlated poorly with Svi and CI (r 2 =0.017 and 0.024, respectively). Interestingly, 60% patients displayed a low-flow state (defined as Svi <35 ml/m 2 ), despite a normal left ventricular ejection fraction (EF >50%, r 2 =0.011). Conclusions: There is incongruence between hemodynamics and conventional parameters defining severe AS. A subset of patients have low-flow state, despite normal left ventricular function. It is plausible that some of these patients, based on their hemodynamics, may benefit from valvular intervention earlier, even at a lower MG. Long-term hemodynamic assessment may guide identification of outcomes in AS patients post-TAVI.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".