Closing the Knowledge Gap: Hepatitis B Reactivation in Immunosuppression
Bibliographic record
Abstract
Background The usage of immunosuppressive medications (ISMs), and specifically disease-modifying antirheumatic drugs (DMARDs), in a wide range of internal medicine subspecialties, has increased the risk of hepatitis B virus reactivation (HBVr). We assessed the understanding of HBVr using a Canada-wide survey. Methods An electronic survey was sent to 521 members of the Canadian Rheumatology Association (CRA). The questions focused on the knowledge of screening, monitoring, and management of patients with chronic or past infection with hepatitis B virus (HBV) in the setting of starting ISMs. The results were compared to the American Gastroenterology Association (AGA) guidelines. Results A total of 142 respondents were included in the analysis (response rate = 27.3%). Over 50% of the respondents would order unnecessary tests such as anti-HBs or anti-HBc for monitoring a HBsAg positive patient on an ISMs. There were 43% of responders who answered incorrectly to starting antiviral prophylaxis for HBsAg positive patients on synthetic DMARDs (sDMARDs). Conclusion There are some knowledge gaps amongst physicians managing rheumatology patients with chronic or past infection with HBV in the setting of ISMs. The AGA guidelines were summarized and incorporated into a user-friendly guide.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".