Experimental Investigation of the Effect of Heart Rate on Flow in the Left Ventricle in Health and Disease—Aortic Valve Regurgitation
Bibliographic record
Abstract
There is much debate in the literature surrounding the effects of heart rate on aortic regurgitation (AR). Despite the contradictory information, it is still widely believed that an increase in heart rate is beneficial due to the disproportionate shortening of the duration of diastole relative to systole, permitting less time for the left ventricle to fill from regurgitation. This in vitro work investigates how a change in heart rate affects the left ventricular fluid dynamics in the absence and presence of acute AR. The experiments are performed on a novel double-activation left heart simulator previously used for the study of chronic AR. The intraventricular velocity fields are acquired via time-resolved planar particle image velocimetry (PIV) in a clinically relevant plane. Considering fluid dynamic factors, an increase in heart rate was observed to have a limited benefit in the case of mild AR and a detrimental effect for more severe AR. With increasing heart rate, mild AR was associated with a decrease in regurgitant volume, a negligible change in regurgitant volume per diastolic second, and a limited reduction in the fraction of retained regurgitant inflow. More severe AR was accompanied by an increase in both regurgitant volume and the fraction of retained regurgitant inflow, implying a less effective pumping efficiency and a longer relative residence time of blood in the ventricle. Globally, the left ventricle's capacity to compensate for the increase in energy dissipation associated with an increase in heart rate diminishes considerably with severity, a phenomenon which may be exploited further as a method of noninvasive assessment of the severity of AR. These findings may affect the clinical belief that tachycardia is preferred in acute AR and should be investigated further in the clinical setting.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".