Plasma-supplemented red cell concentrates as alternatives to whole blood in porcine ex vivo heart perfusion
Bibliographic record
Abstract
BACKGROUND: Normothermic ex vivo organ perfusion holds promise for increasing the organ donor pool; however, standard use of autologous whole blood (WB) presents logistical and functional challenges. This study compared red cell concentrate (RCC)-, rejuvenated RCC-, and WB-based perfusates over a 4-hour ex vivo heart perfusion (EVHP) to assess blood quality and its impact on myocardial function. METHODS: Porcine WB was leukodepleted and hypothermically stored until perfusion. RCCs were divided into five perfusate groups (n = 3, unless otherwise indicated): (A) WB with 14-day-stored RCCs (n = 2), (B) 14-day-stored RCCs alone, (C) 14-day-stored RCCs with plasma, (D) day-14 rejuvenated RCCs, perfused on day 14 of storage with plasma, (E) day-14 rejuvenated RCCs, perfused on day 21 of storage with plasma. All groups were compared to WB (n = 5). At the start and after four hours of perfusion, measurements of coronary flow, cardiac index, oxygen extraction, oxygen consumption, metabolites, red blood cell (RBC) indices, hemolysis, extracellular potassium, methemoglobin, p50, morphology, osmotic fragility, and deformability were collected. RESULTS: Plasma-containing perfusates showed increased coronary flow, cardiac index, and initial oxygen consumption. After four hours, glucose concentrations in RCC-based solutions decreased, while hemolysis increased in most groups. Both rejuvenated RCC groups had lower extracellular potassium concentrations and improved oxygen affinity. WB-based perfusates demonstrated better RBC deformability and reduced fragility. CONCLUSIONS: Plasma is crucial for maintaining perfusate and myocardial quality in porcine EVHP models. RCC-based perfusates alongside plasma offer comparable quality to WB, potentially addressing some of the logistical challenges faced by EVHP, though this remains to be translated to humans.
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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) | 0.000 | 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 | 0.000 |
| 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".