Evidence map›Paper›PMID 29423318›Full record

ReviewNPJ vaccines2018

Pregnancy and infection: using disease pathogenesis to inform vaccine strategy.

Meghan S Vermillion, Sabra L Klein

Open access · goldAbstract readReview
In one paragraph

Review in NPJ vaccines, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 41 citations in OpenAlex.

  1. Article
  2. Pathogenesis of viral infections during pregnancy.Clinical microbiology reviews · 2024
    Review
  3. Observational
  4. Article
  5. Article
  6. Review
  7. Feto-placental Unit: From Development to Function.Advances in experimental medicine and biology · 2023
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Review
  16. COVID-19 vaccine testing in pregnant females is necessary.The Journal of clinical investigation · 2021
    Review
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Meghan S Vermillion1W. Harry Feinstone Department of Molecular Microbiology and Immunology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 USA.
Sabra L Klein1W. Harry Feinstone Department of Molecular Microbiology and Immunology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205 USA.
Johns Hopkins University · US

Funding

Training Program in Cellular and Molecular MedicineT32GM008752 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI RAO, RAJINI · 2000 to 2019
$11.7M
Training Veterinarians for Careers in Biomedical ResearchT32OD011089 · OD · JOHNS HOPKINS UNIVERSITY · PI JOSEPH L MANKOWSKI · 2012 to 2026
$6.7M
NIGMS NIH HHS T32 GM008752NIH HHS T32 OD011089
6 · The paper itself

Abstract

Vaccination is the mainstay of preventative medicine for many infectious diseases. Pregnant women, unborn fetuses, and neonates represent three at-risk populations that can be simultaneously protected by strategic vaccination protocols. Because the pathogenesis of different infectious microbes varies based on tissue tropism, timing of infection, and host susceptibility, the goals of immunization are not uniform across all vaccines. Mechanistic understanding of infectious disease pathogenesis and immune responses is therefore essential to inform vaccine design and the implementation of appropriate immunization protocols that optimize protection of pregnant women, fetuses, and neonates.

Identifiers

PMID29423318
PMCPMC5794984
OpenAlexW2796627031

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.