Post-immunisation fever and the antibody response to measles-containing vaccines
Bibliographic record
Abstract
Fever is a common adverse event following measles vaccination, more frequent among older children and those receiving Measles-Mumps-Rubella-Varicella vaccine vs. Measles-Mumps-Rubella vaccine, two factors associated with a better antibody response. However, the role of fever in the immunogenicity of measles-containing vaccines (MCV) is unclear. We performed a post-hoc pooled analysis of data of 5 216 11 to 22 month-old children receiving MCV from 2004 to 2012 in Europe and USA to evaluate the association between post-immunisation fever and antibody response, measured by geometric mean concentrations (GMCs). We further evaluated fever as an effect modifier or a mediator in the associations between the type of MCV or the age at first vaccination and vaccine immunogenicity. After the first dose, fever was associated with 60% higher GMCs (95% CI 1.51-1.68). For children vaccinated at ⩾12 months, the fever did not modify and minimally mediated (2% to 3%) the association between age and antibody response. Fever mediated 18% of the association between type of MCV and GMCs. In a model including fever, age and type of vaccine, fever was the strongest predictor of GMCs. These results suggest that fever is associated with a stronger measles antibody response independently of age and type of MCV.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.000 |
| 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".