Beat-by-beat volume calibration refines pressure-volume derived indices of left ventricular function in the rat
Bibliographic record
Abstract
Objective: Cardiac pressure-volume studies have advanced much of our understanding of mammalian cardiovascular physiology. Using admittance or conductance technology, the advantage of this technology over other methods to assess cardiovascular function is the ability to derive beat-by-beat pressure-volume loops and generate estimations of myocardial work (stroke work), as well as load-independent systolic (i.e., contractility) and diastolic (i.e., compliance) function from a caval occlusion. While these catheters are capable of extremely accurate recordings of cardiac pressure, volume measurement relies on a series of calibration steps that are oft-performed in isolation or at discrete timepoints. We propose a novel method that enables the refinement of ventricular volume measurement by enabling a beat-by-beat calibration of stroke volume (SV) at baseline and, most importantly, during caval occlusion where both the shape and characteristics of the ventricle are dynamically changing. Hypothesis: We hypothesised that beat-by-beat calibration of SV has a significant effect on PV-catheter derived indices of left ventricle (LV) function. Methodology: Data were collected from 10 rodents that were intubated, ventilated, and urethane anesthetized. We placed an admittance pressure-volume catheter (1.6F Scisense, Transonic Systems, Inc.) into the LV via an apical approach following thoracotomy, a perivascular flow probe (Transonic Systems, Inc.) was placed around the ascending aorta, a blood pressure catheter in the iliac artery, femoral venous lines for fluid/drug infusions, and an arterial line for blood gas analysis. We then assessed baseline and load-independent systolic function using the admittance catheter with and without beat-by-beat volume corrections obtained by integration of the perivascular flow data. Results: Firstly, we confirmed that the standard metrics of load-independent systolic function were increased in response to dobutamine (β1 agonist) and reduced in response to esmolol (β1 blocker). We then found that beat-by-beat volume correction from the perivascular flow probe increased baseline measures of SV and stroke work (SW). Comparing indices of load-independent systolic function calculated from corrected vs. uncorrected values of SV and SW, we found that beat-by-beat volume correction resulted in no significant change in d P/dtmax- V ed (P=0.339) but a significant increase in PRSW (from 116±18 to 129±20 mmHg, P=0.020). Conclusions: Standard approaches to PV studies are able to accurately discern changes in contractile state. However, beat-by-beat calibration of the volume signal improves the absolute determination of volume indices and therefore influences derived measures of contractility. This research was funded by an NSERC Alliance grant to CRW and Mitacs Accelerate Postdoctoral Fellowship to OHW. This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".