The Advent of Semi-Elective Lung Transplantation—Prolonged Static Cold Storage at 10°C
Bibliographic record
Abstract
Since the early days of clinical lung transplantation the preservation of donor organs has become a fairly standardized procedure and most centers do follow similar processes. This includes the use of low-potassium high dextran flush solutions and static cold storage (SCS) in a cooler filled with ice. Depending on the length of SCS, organs usually arrive at the recipient hospital at a temperature of 0°C-4°C. The question of the optimal storage temperature for donor lung preservation has been revisited as data from large animal experiments demonstrated that organs stored at 10°C experience less mitochondrial damage. Thus, prolonged cold ischemic times can be better tolerated at 10°C-even in pre-damaged organs. The clinical applicability of these findings was demonstrated in an international multi-center observational study including three high-volume lung transplant centers. Total clinical preservation times of up to 24 hrs have been successfully achieved in organs stored at 10°C without hampering primary organ function and short-term outcomes. Currently, a randomized-controlled trial (RCT) is recruiting patients with the aim to compare standard SCS on ice with prolonged SCS protocol at 10°C. If, as anticipated, this RCT confirms data from previous studies, lung transplantation could indeed become a semi-elective procedure.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".