Evidence map›Paper›PMID 37243006›Full record

ReviewVaccines2023

Adjuvants for COVID-19 Vaccines.

Javier Castrodeza-Sanz, Iván Sanz-Muñoz, Jose M Eiros

Open access · goldAbstract readReview
In one paragraph

Review in Vaccines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
6.0field-weighted citation impact, top 3% 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

11 citing papers in PubMed, 32 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. New COVID-19 vaccination recommendations in Spain: Optimizing for next seasons.Enfermedades infecciosas y microbiologia clinica · 2025
    Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. 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

3 authors at 2 institutions in 1 country.

Javier Castrodeza-SanzNational Influenza Centre, 47005 Valladolid, Spain.
Iván Sanz-MuñozNational Influenza Centre, 47005 Valladolid, Spain.ORCID 0000-0003-4725-6663
Jose M EirosNational Influenza Centre, 47005 Valladolid, Spain.ORCID 0000-0002-5357-6340
Hospital Clínico Universitario de Valladolid · ESInstituto de Estudios de Ciencias de la Salud de Castilla y León · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent decades, the improvement of traditional vaccines has meant that we have moved from inactivated whole virus vaccines, which provoke a moderate immune response but notable adverse effects, to much more processed vaccines such as protein subunit vaccines, which despite being less immunogenic have better tolerability profiles. This reduction in immunogenicity is detrimental to the prevention of people at risk. For this reason, adjuvants are a good solution to improve the immunogenicity of this type of vaccine, with much better tolerability profiles and a low prevalence of side effects. During the COVID-19 pandemic, vaccination focused on mRNA-type and viral vector vaccines. However, during the years 2022 and 2023, the first protein-based vaccines began to be approved. Adjuvanted vaccines are capable of inducing potent responses, not only humoral but also cellular, in populations whose immune systems are weak or do not respond properly, such as the elderly. Therefore, this type of vaccine should complete the portfolio of existing vaccines, and could help to complete vaccination against COVID-19 worldwide now and over the coming years. In this review we analyze the advantages and disadvantages of adjuvants, as well as their use in current and future vaccines against COVID-19.

Indexed as

adjuvantsCOVID-19immune responsevaccines

Identifiers

PMID37243006
PMCPMC10222622
OpenAlexW4367055451

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.