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Record W2074937710 · doi:10.1007/s10096-012-1595-9

The safety and efficacy of live attenuated influenza vaccine in young children with asthma or prior wheezing

2012· article· en· W2074937710 on OpenAlexaboutno aff
Christopher S. Ambrose, Filip Dubovsky, Tingting Yi, Robert B. Belshe, Shai Ashkenazi

Bibliographic record

VenueEuropean Journal of Clinical Microbiology & Infectious Diseases · 2012
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLive attenuated influenza vaccineMedicineAsthmaVaccinationPediatricsInfluenza vaccineIrritabilityImmunologyInternal medicine

Abstract

fetched live from OpenAlex

In the European Union and Canada, an Ann Arbor strain live attenuated influenza vaccine (LAIV) is approved for use in children aged 2-17 years, including those with mild to moderate asthma or prior wheezing. The safety and efficacy of LAIV versus trivalent inactivated influenza vaccine (TIV) in children with asthma aged 6-17 years have been demonstrated. However, few data are available for children younger than 6 years of age with asthma or prior wheezing. Safety and efficacy data were collected for children aged 2-5 years with asthma or prior wheezing from two randomized, multinational trials of LAIV and TIV (N = 1,940). Wheezing, lower respiratory illness, and hospitalization were not significantly increased among children receiving LAIV compared with TIV. Increased upper respiratory symptoms and irritability were observed among LAIV recipients (p < 0.05). Relative efficacies were consistent with the results observed in the overall study populations, which demonstrated fewer cases of culture-confirmed influenza illness in LAIV compared with TIV recipients. Study results support the safety and efficacy of LAIV among children aged 2-17 years with mild to moderate asthma or a history of wheezing. Data regarding LAIV use are limited among individuals with severe asthma or active wheezing within the 7 days before vaccination.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.372
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations37
Published2012
Admission routes1
Has abstractyes

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