Alternative Approaches to the Assessment of the Systemic Circulation and Left Ventricular Performance: A Proof-of-Concept Study
Bibliographic record
Abstract
BackgroundThe purpose of this article is to examine the systemic circulation and left ventricular (LV) performance by alternative, nonconventional approaches: systemic vascular conductance (GSV) and the head-capacity relation (ie, the relation between LV pressure and cardiac output), respectively; in so doing, we aspired to present a novel and improved interpretation of integrated cardiovascular function.MethodsIn 16 open-chest, anaesthetized pigs, we measured LV pressure (PLV), central aortic pressure (PAo), and central venous pressure (PCV) and aortic flow (QAo). We calculated heart rate (HR), stroke volume, cardiac index (CI = cardiac output/body weight), mean PLV (P¯LV), and the average arteriovenous pressure difference (ΔP=P¯Ao−P¯CV); GSV = CI/(P¯Ao−P¯CV). We studied the effects of changing loading conditions with the administration of phenylephrine (ΔP¯Ao ≥ +25 mm Hg), isoproterenol (ΔHR ∼+25%), sodium nitroprusside (ΔP¯Ao ≥ −25 mm Hg), and proximal aortic constriction (to maximize developed PLV and minimize QAo).ResultsSodium nitroprusside and isoproterenol increased GSV compared with phenylephrine and constriction. A maximum head-capacity curve was derived from pooled data using nonlinear regression on the maximum P¯LV values in QAo bins 12.5 mL/min/kg wide. The head-capacity relation and the plots of conductance were combined using CI as a common axis, which illustrated that CI is the output of the heart and the input of the circulation.ConclusionsThus, at a given CI, GSV determines the driving pressure and, thereby, PAo. We also demonstrated how decreases in GSV compensate for arterial hypotension by restoring the arteriovenous pressure difference and arterial pressure.
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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) | 0.000 | 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".