A cross‐species validation of single‐beat metrics of cardiac contractility
Bibliographic record
Abstract
The assessment of left ventricular (LV) contractility in animal models is useful in various experimental paradigms, yet obtaining such measures is inherently challenging and surgically invasive. In a cross-species study using small and large animals, we comprehensively tested the agreement and validity of multiple single-beat surrogate metrics of LV contractility against the field-standard metrics derived from inferior vena cava occlusion (IVCO). Fifty-six rats, 27 minipigs and 11 conscious dogs underwent LV and arterial catheterization and were assessed for a range of single-beat metrics of LV contractility. All single-beat metrics were tested for the various underlying assumptions required to be considered a valid metric of cardiac contractility, including load-independency, sensitivity to inotropic stimulation, and ability to diagnose contractile dysfunction in cardiac disease. Of all examined single-beat metrics, only LV maximal pressure normalized to end-diastolic volume (EDV), end-systolic pressure normalized to EDV, and the maximal rate of rise of the LV pressure normalized to EDV showed a moderate-to-excellent agreement with their IVCO-derived reference measure and met all the underlying assumptions required to be considered as a valid cardiac contractile metric in both rodents and large-animal models. Our findings demonstrate that single-beat metrics can be used as a valid, reliable method to quantify cardiac contractile function in basic/preclinical experiments utilizing small- and large-animal models KEY POINTS: Validating and comparing indices of cardiac contractility that avoid caval occlusion would offer considerable advantages for the field of cardiovascular physiology. We comprehensively test the underlying assumptions of multiple single-beat indices of cardiac contractility in rodents and translate these findings to pigs and conscious dogs. We show that when performing caval occlusion is unfeasible, single-beat metrics can be utilized to accurately quantify cardiac inotropic function in basic and preclinical research employing various small and large animal species. We report that maximal left-ventricular (LV)-pressure normalized to end-diastolic volume (EDV), LV end-systolic pressure normalized to EDV and the maximal rate of rise of the LV pressure waveform normalized to EDV are the best three single-beat metrics to measure cardiac inotropic function in both small- and large-animal models.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".