Liver transplantation for Gaucher disease presenting as neonatal cholestasis: Case report and literature review
Bibliographic record
Abstract
BACKGROUND: We present a rare case of neonatal cholestasis in a female infant with Gaucher Disease (GD), who received liver transplantation. We review the relevant literature on similar disease presentations. METHODS: A chart review of the index case was performed. PubMed and Medline databases were searched to identify other cases. RESULTS: A 4-day-old female was referred with conjugated hyperbilirubinemia. Physical examination revealed icterus with hepatosplenomegaly and normal neurologic examination. The diagnosis of GD was confirmed through liver biopsy, low glucocerebrosidase enzyme activity, and two pathogenic mutations in GBA gene. Despite early initiation of ERT, the patient had worsening of her liver failure and underwent a left lateral segment liver transplant from a living donor at 7 months of age. She experienced improvement of her liver enzymes and coagulation, but passed away at 8 months due to the late onset of neurologic involvement. Nine other cases of GD presenting with neonatal cholestasis have been reported. Forty-four percent (4/9) of cases received ERT and none were considered for transplant. Overall, the literature suggests a poor prognosis with death reported in 77% (7/9) cases. CONCLUSIONS: Neonatal presentation of GD represents a poor prognosis despite early initiation of treatment. Diagnosis remains a challenge as the presentation is rare and multiple tests such as BM biopsy, liver biopsy with both light and electron microscopy, enzymology, and genetic testing may need to be completed to reach a diagnosis. Neurological sequelae may manifest later making the decision to proceed with liver transplantation a difficult one.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| 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".