Maintaining Hepatitis B Protection in Immunocompromised Pediatric Rheumatology and Inflammatory Bowel Disease Patients
Bibliographic record
Abstract
Objective Hepatitis B virus (HBV) infection remains a significant public health challenge, particularly for immunocompromised patients. Our aim was to evaluate the serologic immunity in immunocompromised rheumatology and inflammatory bowel disease (IBD) patients, assess factors for serologic nonimmunity, and evaluate their response to 1 HBV booster dose. Methods Immunocompromised rheumatology and IBD patients with completed HBV screening were identified. A chart review was performed to collect demographics, clinical information, baseline HBV serology results, and serologic response to booster vaccination. Serologic nonimmunity was defined as a negative/indeterminate hepatitis B surface antibody (anti-HBs) level. Results Among 580 patients, 71% were nonimmune. The highest portion of nonimmune patients were 11–18 years old ( P = 0.004). There was no significant difference between immune and nonimmune patients with regards to diagnosis ( P = 0.34), age at diagnosis ( P = 0.64), duration of treatment ( P = 0.07), or type of medications ( P = 0.08). Sixty-two percent of those who received a booster vaccine were rescreened, and most (68%) seroconverted. In those 18 years or older, only half seroconverted. Conclusion Results of this study support the benefit of HBV screening in immunosuppressed patients. Beginning at age 11 years, most patients lacked serologic immunity to HBV. Seroconversion for most patients 11–18 years occurred after 1 booster vaccine. Thus, for immunocompromised patients without recent HBV serologic data, obtaining the HBV serology beginning at age 11 years might be considered. Those 18 years and older were least likely to seroconvert after 1 booster, indicating that they may benefit from receiving the 3-dose HBV vaccine series.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".