Steatotic liver disease arising in an asymptomatic 20-year-old man with panhypopituitarism and elevated transaminases
Bibliographic record
Abstract
Background: Steatotic liver disease (SLD) may be caused by cardiometabolic risk factors, drugs/toxins, viral hepatitis, genetic diseases, malnutrition, or panhypopituitarism. SLD can advance to steatohepatitis with resulting lipid accumulation, inflammation, and hepatocellular damage. SLD is associated with pituitary dysfunction, in particular growth hormone deficiency, as insulin resistance leads to lipid buildup and oxidative stress. Growth hormone replacement may improve liver steatosis and fibrosis in patients with hypopituitarism. Case: We report a case of a 20-year-old man who was referred to Hepatology with abnormal liver enzymes. He had panhypopituitarism from a resected pituitary mass, for which he was treated with levothyroxine, hydrocortisone, growth hormone, and testosterone. He presented with elevated liver enzymes, normal liver function, obesity, dyslipidemia, and had no extrahepatic manifestations of chronic liver disease. Work-up for secondary causes of liver disease, including infectious, autoimmune, drug-induced, and genetic causes, were negative. An abdominal ultrasound revealed moderate hepatic steatosis with mild hepatomegaly and splenomegaly. His liver enzymes remained elevated, and his biochemical liver function remained normal despite withdrawal of hepatotoxic medications. Liver biopsy showed grade II/III steatohepatitis with stage III-IV fibrosis. The biopsy results suggested that panhypopituitarism, with growth hormone deficiency and related metabolic dysfunction, caused his liver disease. Conclusions: This is a unique case of an aggressive form of SLD due to panhypopituitarism, and treating growth hormone deficiency with hormone replacement did not improve liver enzymes or liver damage. Physicians should recognize SLD as a serious complication of panhypopituitarism and resulting growth hormone deficiency and follow patients closely given the risk of disease progression.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".