Primary Non-Function of Hepatic Allograft With Preexisting Microvesicular Steatosis/Foamy Degeneration and Mild Large-Droplet Macrovesicular Steatosis
Bibliographic record
Abstract
It has been established that more than mild large-droplet macrovesicular steatosis (LD-MAS) is associated with increased risk of graft non-function. In contrast, even severe small-droplet macrovesicular steatosis (SD-MAS) has been found to be less prognostically significant. It remains unclear if a donor liver with diffuse microvesicular steatosis is associated with an increased risk of graft dysfunction. A 56-year-old male with alcoholic cirrhosis was transplanted with a liver from a 42-year-old overweight male donor after brain death. The frozen section of the donor liver biopsy taken at harvest showed diffusely enlarged clear/foamy hepatocytes and mild LD-MAS (about 5-10% of total tissue). The reperfusion liver biopsy taken at time 0 of transplantation showed hemorrhage, pale and enlarged hepatocytes, and mild LD-MAS (about 10% of total tissue) with lipopeliosis. The graft became non-functional, and the patient was re-transplanted 24 h after the initial transplantation. Histologic examination of the failed liver allograft showed extensive hemorrhagic necrosis, neutrophilic inflammation, diffuse microvesicular steatosis, and large extracellular fat droplets (about 20% of total tissue). This case demonstrates that precautions are needed to avoid using livers with diffuse and severe microvesicular steatosis.
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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 | 0.001 |
| 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".