A further analysis of why pulmonary venous pressure rises after the onset of LV dysfunction
Bibliographic record
Abstract
Based on a dynamic computational model of the circulation, Burkhoff and Tyberg (Am J Physiol Heart Circ Physiol 265: H1819-H1828, 1993) concluded that the rise in pulmonary venous pressure (Pvp) with left ventricular (LV) dysfunction requires a decrease in vascular capacitance and transfer of unstressed volume to stressed volume (nu). We argue that the values they used for venous resistance (Rvs), venous compliance (Cvs), and nu were too low, and changing these values significantly changes the conclusion. We used a computational model of the circulation that was similar to theirs, but we made Rvs four times higher (0.06 versus 0.015 mmHg.s.ml(-1)), Cvs larger (110 versus 70 ml/mmHg), and nu larger (1,400 versus 750 ml); all other parameters, including those for the heart, were essentially the same. We simulated left ventricular dysfunction by decreasing end-systolic elastance (Eeslv) as they did and examined changes in cardiac output, arterial blood pressure, and Pvp. We then examined the effect of changes in Rvs, heart rate, and nu when Eeslv was depressed with and without pericardial constraint. In contrast to their findings, with our parameters the model predicts that decreasing Eeslv substantially increases Pvp. Furthermore, increasing systemic vascular resistance or decreasing Rvs or heart rate produces large increases in Pvp when Eeslv is reduced. Pericardial constraint limits the changes in Pvp. In conclusion, when Rvs and Cvs are increased, baseline nu must be higher to maintain normal cardiac output. This increased volume can shift between compartments under flow conditions and account for the increase in Pvp with decreased left ventricular function even without recruitment of unstressed volume.
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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 | 0.000 |
| 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 | 0.000 | 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".