Assessment of left ventricular diastolic suction in dogs using wave-intensity analysis
Bibliographic record
Abstract
Two apparently different types of mechanisms have emerged to explain diastolic suction (DS), that property of the left ventricle (LV) that tends to cause it to refill itself during early diastole independent of any force from the left atrium (LA). By means of the first mechanism, DS depends on decreased elastance [e.g., the relaxation time constant (tau)] and, by the second, end-systolic volume (V(LVES)). We used wave-intensity analysis (WIA) to measure the total energy transported by the backward expansion wave (I(W-)) during LV relaxation in an attempt to reconcile these mechanisms. In six anesthetized, open-chest dogs, we measured aortic, LV (P(LV)), LA (P(LA)), and pericardial pressures and LV volume by orthogonal ultrasonic crystals. Mitral velocity was measured by Doppler echocardiography, and aortic velocity was measured by an ultrasonic flow probe. Heart rate was controlled by pacing, V(LVES) by volume loading, and tau by isoproterenol or esmolol administration. I(W-) was found to be inversely related to tau and V(LVES). Our measure of DS, the energy remaining after mitral valve opening, I(W-DS), was also found to be inversely related to tau and V(LVES) and was approximately 10% of the total "aspirating" energy generated by LV relaxation (i.e., I(W-)). The size of the Doppler (early filling) E wave depended on I(W-DS) in addition to I(W+), the energy associated with LA decompression. We conclude that the energy of the backward-going wave generated by the LV during relaxation depends on both the rate at which elastance decreases (i.e., tau) and V(LVES). WIA provides a new approach for assessing DS and reconciles those two previously proposed mechanisms. The E wave depends on DS in addition to LA decompression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".