Determinants of Long-term Protection After Hepatitis B Vaccination in Infancy
Bibliographic record
Abstract
BACKGROUND: The duration of protection after hepatitis B vaccination in early infancy is unclear and may be related to vaccination schedule, dosage, vaccine type and population characteristics. Factors potentially influencing waning immunity were assessed. METHODS: A systematic review was performed. The main outcomes were prevalence of anti-hepatits B antibodies ≥ 10 mIU/mL after primary or booster vaccination. Factors potentially influencing protection were assessed in an adjusted random-effects meta-analysis model by age for both outcomes. Results of both meta-analyses were combined in a prognostic model. RESULTS: Forty-six studies reporting on the anti-hepatits B antibodies ≥ 10 mIU/mL 5 to 20 years after primary immunization and 29 on booster response were identified. The adjusted meta-analyses identified maternal carrier status (odds ratio [OR]: 2.37 [1.11; 5.08]), lower vaccine dosage than presently recommended (OR: 0.14 [0.06; 0.30]) and gap time between last and preceding dose of the primary vaccine series (OR: 0.44 [0.22; 0.86]) as determinants for persistence of anti-hepatits B antibodies ≥ 10. A lower vaccine dosage was also associated with failure to respond to booster (OR: 0.20 [0.10; 0.38]). The prognostic model predicted long-term protection of 90% [77%; 100%] at the age of 17 years for offspring of noncarrier mothers vaccinated with a presently recommended dose and vaccination schedule. CONCLUSIONS: Based on meta-analyses, predictors of waning immunity after hepatitis B vaccination in infancy could be identified. A prognostic model for long-term protection after hepatitis B vaccination in infancy was developed.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".