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Record W2991522534 · doi:10.1542/peds.2019-0630

Measles Antibody Levels in Young Infants

2019· article· en· W2991522534 on OpenAlexaffabout
Michelle Science, Rachel Savage, Alberto Severini, Elizabeth McLachlan, Stephanie L. Hughes, Callum Arnold, Susan E. Richardson, Natasha S. Crowcroft, Shelley L. Deeks, Scott A. Halperin, Kevin A. Brown, Todd F. Hatchette, Jonathan B. Gubbay, Tony Mazzulli, Shelly Bolotin

Bibliographic record

VenuePEDIATRICS · 2019
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsMount Sinai HospitalPublic Health OntarioHospital for Sick ChildrenIzaak Walton Killam Health CentreUniversity of ManitobaNova Scotia Health AuthorityPublic Health Agency of CanadaUniversity Health NetworkDalhousie UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineMeaslesMeasles vaccineOdds ratioPediatricsPoisson regressionLogistic regressionGestational ageConfidence intervalImmunityVaccinationImmunologyAntibodyPregnancyImmune systemPopulationInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Infants are often assumed to be immune to measles through maternal antibodies transferred during pregnancy and, in many countries, receive their first measles-containing vaccine at 12 to 15 months. Immunity may wane before this time in measles-eliminated settings, placing infants at risk for measles and complications. We investigated humoral immunity to measles in infants <12 months of age in Ontario, Canada. METHODS: We selected sera collected at a tertiary pediatric hospital from infants <12 months who were born at ≥37 weeks' gestational age. We excluded infants with conditions that affect antibody levels. We selected ≤25 sera from 8 predetermined age bands and tested them for measles-neutralizing antibody using the plaque-reduction neutralization test. We calculated the proportion immune at each age band, and predictors of infant susceptibility were assessed by using multivariable logistic regression and Poisson regression. RESULTS: Of 196 infant sera, 56% (110 of 196) were from boys, and 35% (69 of 196) were from infants with underlying medical conditions. In the first month, 20% (5 of 25) of infants had antibodies below the protective threshold, which increased to 92% (22 of 24) by 3 months. By 6 months, all infants had titers below the protective threshold. In a multivariable analysis, infant age was the strongest predictor of susceptibility (odds ratio = 2.13 for each additional month increase; 95% confidence interval: 1.52-2.97). CONCLUSIONS: Most infants were susceptible to measles by 3 months of age in this elimination setting. Our findings inform important policy discussions relating to the timing of the first dose of measles-containing vaccine and infant postexposure prophylaxis recommendations.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.007
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.018
GPT teacher head0.314
Teacher spread0.297 · 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

Citations48
Published2019
Admission routes2
Has abstractyes

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