Evaluation of target temperature on effectiveness of myocardial preservation during hypothermic machine perfusion
Bibliographic record
Abstract
Background: Ex-situ heart perfusion (ESHP) has been proposed as an optimal method for preserving donated hearts prior to transplantation. Hypothermic oxygenated perfusion (HOP) is a simple method from a device design perspective, with enhanced safety compared to normothermic perfusion in the event of device failure. However, the optimal temperature for cardiac HOP has yet to be determined. We evaluated the effectiveness of 12-hour HOP using University of Wisconsin Machine Perfusion Solution (UWMPS) in different temperatures compared to static cold storage (SCS) for 6 hours followed by simulated transplantation. Additionally, we sought to determine the impact of oxygen supplementation in hypothermic ESHP in the heart function preservation. Methods: = 35) randomized into 3 preservation therapies: 6 hours-SCS; 12 hours-HOP and 12 hours hypothermic non-oxygenated perfusion (HNOP-without oxygen supplementation). For either HOP or HNOP groups, 3 temperatures were tested (5°C; 10°C; 15°C). After the preservation period, hearts had their function assessed in a normothermic perfusion machine capable of working mode, simulating transplantation. Results: < 0.05). The HNOP hearts presented similar cardiac function results compared to SCS. Conclusions: HOP for 12 hours had better heart function preservation than SCS for 6 hours. Even HNOP had similar results compared to SCS. Greater edema formation in ESHP hearts did not affect heart function. Hypothermic ESHP safely enhances function preservation compared to SCS.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".