The implementation of physiological afterload during ex situ heart perfusion augments prediction of posttransplant function
Bibliographic record
Abstract
Ex situ heart perfusion (ex situ heart perfusion) is an emerging technique that aims to increase the number of organs available for transplantation by augmenting both donor heart preservation and evaluation. Traditionally, ex situ heart perfusion has been performed in an unloaded Langendorff mode, though more recently groups have begun to use pump-supported working mode (PSWM) and passive afterload working mode (PAWM) to enable contractile evaluation during ex situ heart perfusion. To this point, however, neither the predictive effectiveness of the two working modes nor the predictive power of individual contractile parameters has been analyzed. In this article, we use our previously described system to analyze the predictive relevance of a multitude of contractile parameters measured in each working mode. Ten porcine hearts were excised and perfused ex situ in Langendorff mode for 4 h, evaluated using pressure-volume catheterization in both PSWM and PAWM, and transplanted into size-matched recipient pigs. After 3 h, hearts were weaned from cardiopulmonary bypass and evaluated. When correlating posttransplant measurements to their ex situ counterparts, we report that parameters measured in both modes show sufficient power (Spearman rank coefficient > 0.7) in predicting global posttransplant function, characterized by cardiac index and preload recruitable stroke work. For the prediction of specific posttransplant systolic and diastolic function, however, a large discrepancy between the two working modes was observed. With 9 of 10 measured posttransplant parameters showing stronger correlation with counterparts measured in PAWM, it is concluded that PAWM allows for a more detailed and nuanced prediction of posttransplant function than can be made in PSWM. NEW & NOTEWORTHY Ex situ heart perfusion has been proposed as a means to augment the organ donor pool by improving organ preservation and evaluation between donation and transplantation. Using our multimodal perfusion system, we analyzed the impact of using a “passive afterload working mode” for functional evaluation as compared with the more traditional “pump-supported working mode.” Our data suggests that passive afterload working mode allows for a more nuanced prediction of posttransplant function in porcine hearts.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".