A Post-Licensure Evaluation of the Safety of Live Attenuated Influenza Vaccine in U.S. Children 5-17 Years of Age
Bibliographic record
Abstract
Background • The safety of live attenuated influenza vaccine (LAIV) has been evaluated in 26,031 children enrolled in placeboand trivalent inactivated influenza vaccine (TIV)–controlled clinical trials and a community-based open-label study.1,2 • LAIV was initially approved in the United States in 2003 for eligible individuals 5–49 years of age; the age indication was lowered to include children as young as 2 years in 2007. • As part of a postlicensure commitment to the US Food and Drug Administration, MedImmune conducted a postmarketing evaluation of the safety of LAIV in 60,000 LAIV recipients 5–49 years of age, including approximately 20,000 individuals in each of 3 age cohorts (5–8 y, 9–17 y, and 18–49 y). • LAIV is also approved in other countries for use in eligible individuals aged 2–49 years (2–17 y in the European Union and 2–59 y in Canada). Objective • To evaluate the postlicensure safety of LAIV among US children aged 5–8 and 9–17 years Methods • Safety data were prospectively collected from a Kaiser Permanente Health Plan database of 4 million members in Northern California, Hawaii, and Colorado; members received LAIV and TIV as part of routine care. • Rates of medically attended events (MAEs) and serious adverse events (SAEs) were assessed in eligible children 5–17 years of age receiving LAIV from October 2003–March 2008; comparators were multiple nonrandomized controls, including self-control, matched unvaccinated controls, and matched TIV recipients. • Subjects were matched based on age, sex, and previous healthcare use. • Children at high risk (eg, those with underlying medical conditions for whom LAIV was not recommended) were excluded from analysis. • MAEs were identified in the clinic, emergency department, and hospital. • All MAEs and SAEs through 42 days postvaccination and all hospitalizations and deaths through 6 months postvaccination were analyzed (Table 1).
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How this classification was reachedexpand
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".