MétaCan
Menu
Back to cohort
Record W2600363044 · doi:10.1097/qco.0000000000000372

Placental transfer of antibody and its relationship to vaccination in pregnancy

2017· review· en· W2600363044 on OpenAlexaff
Anna Calvert, Christine E. Jones

Bibliographic record

VenueCurrent Opinion in Infectious Diseases · 2017
Typereview
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicinePregnancyVaccinationObstetricsAntibodyGynecologyVirologyImmunology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Vaccination in pregnancy boosts maternal vaccine-specific antibody concentration and therefore increases transplacental transfer of antibody to optimize protection of the infant. The purpose of this review is to describe what is known about placental transfer of antibody in the context of vaccination in pregnancy, focussing on the recent literature and areas of debate, particularly about the timing of vaccination. RECENT FINDINGS: There is a debate about the timing of pertussis vaccination in pregnancy with some studies reporting that vaccination in the third trimester results in higher pertussis antigen-specific IgG concentrations in cord blood and others finding that the concentration is higher following vaccination in the second trimester. The impact of timing of vaccination on antibody avidity in cord blood has also been investigated and one study suggests that avidity may be increased following vaccination at 27-30 gestational weeks compared with later vaccination. SUMMARY: Understanding placental transfer of antibody is vital in informing maternal vaccination strategy. There has been recent research about the timing of pertussis vaccination in pregnancy that has implications for the timing of both current and future vaccines to be used in pregnancy.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.879
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.109
GPT teacher head0.416
Teacher spread0.307 · 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.

Study designOther design
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

Citations51
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in Infectious DiseasesSame topicBacterial Infections and VaccinesFrench-language works237,207