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Record W3047550025 · doi:10.1542/peds.2019-3579

Interference With Pertussis Vaccination in Infants After Maternal Pertussis Vaccination

2020· review· en· W3047550025 on OpenAlexafffundabout
Bahaa Abu-Raya, Kathryn M. Edwards

Bibliographic record

VenuePEDIATRICS · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsMedicineDiphtheriaTetanusVaccinationPertussis vaccineImmunizationWhooping coughPediatricsPregnancyImmunologyAntibody

Abstract

fetched live from OpenAlex

* Abbreviations: aP — : acellular pertussis DTaP — : diphtheria-tetanus-acellular pertussis DTwP — : diphtheria, tetanus, and whole-cell pertussis HIC — : high-income country LMICs — : low- and middle-income countries WHO — : World Health Organization Pertussis is a major public health concern. In 2014, 24 million cases and 160 000 deaths from pertussis in children <5 years were estimated worldwide, with nearly one-third of the cases occurring in Africa.1 Vaccination with an acellular pertussis (aP)–containing vaccine in pregnancy prevents severe pertussis in young infants and has been recommended in an increasing number of high-income countries (HICs). We have recently discussed optimal strategies for vaccination in pregnancy to maximize protection against infections in infancy.2 However, pertussis vaccination in pregnancy reduces infants’ primary immune responses to diphtheria-tetanus-acellular pertussis (DTaP) vaccines, leading to lower antibody levels to some pertussis antigens, when compared with infants of unvaccinated mothers.3 This is termed “interference” and has been shown primarily in studies from HICs that used DTaP formulations for infant immunization, but its clinical implications are unknown. Fewer data are available on the potential interference with diphtheria, tetanus, and whole-cell pertussis (DTwP) vaccines for infant immunization, the vaccines used almost exclusively in low- and middle-income countries (LMICs). An earlier study that we conducted in the United States revealed interference with DTwP vaccines, but not with DTaP vaccines, in infants with higher maternally derived antibody levels before primary vaccination.4 In a recent study conducted in Pakistan, the authors found no correlation between preexisting anti-pertussis antibody levels at delivery and infants’ anti-pertussis antibody levels after primary vaccination with DTwP vaccines.5 However, women in these 2 studies did … Address correspondence to Bahaa Abu-Raya, MD, British Columbia Children’s Hospital Research Institute, The University of British Columbia, 950 W 28th Ave, Vancouver, BC V5Z 4H4, Canada. E-mail: baburaya{at}bcchr.ubc.ca

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.278
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations15
Published2020
Admission routes3
Has abstractyes

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