Chronic Hepatitis E Virus Infection: A Red Flag for Undiagnosed Hematological Malignancy?
Bibliographic record
Abstract
Hepatitis E virus (HEV) is known to be able to establish chronic infection in a subset of patients who are immunosuppressed. We present a case of a patient who was initially diagnosed with a chronic HEV infection which subsequently revealed a hematological malignancy. We believe this to be the first case in which the finding of chronic HEV infection has led directly to the finding of an underlying cause of immune compromise. A 66-year-old female of Northern European origin presented to gastroenterology with right upper quadrant pain and weight loss. The cause was initially unclear despite investigations. The following year she was diagnosed with chronic HEV infection. As chronic HEV is not recognized in patients without underlying immune compromise, she was thoroughly investigated for a cause and was found to have extra-nodal marginal zone lymphoma of mucosa-associated lymphoid tissue type. HEV was successfully eradicated using ribavirin. Combination chemotherapy was given for lymphoma and she made a good recovery, with resolution of her previous gastrointestinal symptoms. This reinforces the understanding that chronic HEV infection does not occur in immunocompetent patients and that a finding of chronic HEV infection in a patient without a pre-existing reason for immune compromise should be followed with a thorough search for the underlying cause. Clin Infect Immun. 2020;5(2):45-48 doi: https://doi.org/10.14740/cii108
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".