Herpes simplex virus hepatitis in a renal transplant recipient seronegative pre-transplant
Bibliographic record
Abstract
BACKGROUND: Herpes simplex virus (HSV) is a rare cause of acute viral hepatitis but has high mortality rates and primarily affects immunocompromised hosts. We report a case of HSV hepatitis in a 20-year-old female kidney transplant recipient who had 1000-fold elevations in transaminases on post-transplant day 14, and the strategies employed for diagnoses and treatment. METHODS: Routine laboratory, serological, and molecular viral testing was completed, and she underwent a bone marrow given initial suspicion of hemophagocytic lymphohistiocytosis (HLH). HSV serologic results and high transaminases triggered a liver biopsy. RESULTS: The patient presented with elevated transaminases (ALT 1731 U/L and AST 1400) and ferritin (1431 ug/L). Transaminases and ferritin peaked with an ALT of 6609 U/L, AST of 6525 U/L, and ferritin > 50000 ug/L. Bone marrow biopsy revealed no definitive HLH. HSV-DNA PCR of blood was positive, and she was empirically started on intravenous acyclovir 10mg/kg t.i.d. Liver biopsy confirmed the histological diagnosis of HSV hepatitis. CONCLUSIONS: Given the high mortality rates associated with HSV hepatitis, it is crucial to determine pre-transplant HSV status, initiate appropriate antiviral prophylaxis, and to have a low threshold for investigating for HSV hepatitis and initiating treatment in patients with a suspected diagnosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".