Normothermic Ex Situ Heart Perfusion in Working Mode: Assessment of Cardiac Function and Metabolism
Bibliographic record
Abstract
The current standard method for organ preservation (cold storage, CS), exposes the heart to a period of cold ischemia that limits the safe preservation time and increases the risk of adverse post-transplantation outcomes. Moreover, the static nature of CS does not allow for organ evaluation or intervention during the preservation interval. Normothermic ex situ heart perfusion (ESHP) is a novel method for preservation of the donated heart that minimizes cold ischemia by providing oxygenated, nutrient-rich perfusate to the heart. ESHP has been shown to be non-inferior to CS in the preservation of standard-criteria donor hearts and has also facilitated the clinical transplantation of the hearts donated after the circulatory determination of death. Currently, the only available clinical ESHP device perfuses the heart in an unloaded, non-working state, limiting assessments of myocardial performance. Conversely, ESHP in working mode provides the opportunity for comprehensive evaluation of cardiac performance by assessment of functional and metabolic parameters under physiologic conditions. Moreover, earlier experimental studies have suggested that ESHP in working mode may result in improved functional preservation. Here, we describe the protocol for ex situ perfusion of the heart in a large mammal (porcine) model, which is reproducible for different animal models and heart sizes. The software program in this ESHP apparatus allows for real-time and automated control of the pump speed to maintain desired aortic and left atrial pressure and evaluates a variety of functional and electrophysiological parameters with minimal need for supervision/manipulation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 0.001 |
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".