Determinants of Long-term Protection After Hepatitis B Vaccination in Infancy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it