Hepatitis B Virus Reactivation with Immunosuppression: A Hidden Threat?
Bibliographic record
Abstract
Hepatitis B virus (HBV) reactivation in the setting of immunosuppressive therapy is an increasingly recognized and preventable cause of elevated liver enzymes and clinical hepatitis in treated patients. However, not all immunosuppressive therapies confer the same risk. The purpose of this article was to review the literature on risks of HBV reactivation associated with immunosuppressive agents and propose a management algorithm. We searched Google Scholar, PubMed, and MEDLINE for studies related to hepatitis B reactivation and various immunosuppressive agents. The risk of HBV reactivation was found to differ by agent and depending on whether a patient had chronic HBV (HBsAg+) or past HBV (HBsAg-, anti-HBc+). The highest risk of reactivation (>10%) was associated with anti-CD20 agents and hematopoietic stem cell transplants. Multiple societies recommend HBV-specific anti-viral prophylaxis for patients with positive HBsAg prior to the initiation of immunosuppressive therapy, while the guidance for HBsAg- patients is more variable. Clinicians should check HBV status prior to beginning an immune-suppressive therapy. Patients with positive HBsAg should be initiated on antiviral prophylaxis in the majority of cases, whereas HBsAg- individuals should be evaluated on a case-by-case basis. Further research is required to determine the optimum duration of therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".