Value of liver biopsy in anorexia nervosa‐related transaminitis: A case study and literature review
Bibliographic record
Abstract
Abstract Anorexia nervosa (AN) is a complex eating disorder that affects multiple organs. 60% of patients have liver injury with transaminitis. The mechanism of liver injury in AN remains unclear. We present a case of a 19‐year‐old female with AN was admitted to our hospital with marked transaminitis but near normal liver histology on biopsy. Her transaminitis eventually improved as she regained weight. We also conducted a literature review of similar cases to delineate the clinicopathologic spectrum of liver injury in AN patients. English published cases of adult AN patients with elevated transaminases who underwent a liver biopsy or autopsy were selected. 32 cases (including ours). All except four patients were female, with median age of 26.5 years and median body mass index 11.9 kg/m2. Presentations mainly included hypoglycemic coma and weight loss. 63% of patients had severe transaminitis (AST >15x ULN). Other lab findings included elevated international normalized ratio (72%) and hypoalbuminemia (47%). Microscopically, all cases showed intact hepatic architecture. Fibrosis was reported in 12 cases and necroinflamfmation in 8, but only half of each had severe transaminitis. AN patients display a wide spectrum of liver histopathology which often does not correlate with the degree of transaminitis. In severe persistent AN‐related transaminitis, liver biopsy is useful to assess the degree of liver injury and to exclude other potential etiologies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".