Evidence map›Paper›PMID 36505947›Full record

ArticleAntimicrobial stewardship & healthcare epidemiology : ASHE2022

The effectiveness of coronavirus disease 2019 (COVID-19) vaccine in the prevention of post-COVID-19 conditions: A systematic literature review and meta-analysis.

Alexandre R Marra, Takaaki Kobayashi, Hiroyuki Suzuki, Mohammed Alsuhaibani, Shinya Hasegawa, Joseph Tholany, Eli Perencevich, Aline Miho Maezato, Victoria Catharina Volpe Ricardo, Jorge L Salinas and 2 more

Abstract read
In one paragraph

Article in Antimicrobial stewardship & healthcare epidemiology : ASHE, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 6 pooled it
–field-weighted citation impact
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

20 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  4. Definitions and symptoms of the post-COVID syndrome: an updated systematic umbrella review.European archives of psychiatry and clinical neuroscience · 2025
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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

12 authors.

Alexandre R MarraDepartment of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, United States.ORCID https://orcid.org/0000-0002-7577-7688
Takaaki KobayashiDepartment of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, United States.ORCID https://orcid.org/0000-0003-4751-6859
Hiroyuki SuzukiDepartment of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, United States.
Mohammed AlsuhaibaniDepartment of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, United States.
Shinya HasegawaDepartment of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, United States.ORCID https://orcid.org/0000-0001-7167-270X
Joseph TholanyDepartment of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, United States.ORCID https://orcid.org/0000-0003-4415-4573
Eli PerencevichDepartment of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, United States.
Aline Miho MaezatoFaculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.
Victoria Catharina Volpe RicardoFaculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.
Jorge L SalinasStanford University, Stanford, California, United States.
Michael B EdmondWest Virginia University School of Medicine, Morgantown, West Virginia, United States.
Luiz Vicente RizzoFaculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Although multiple studies have revealed that coronavirus disease 2019 (COVID-19) vaccines can reduce COVID-19-related outcomes, little is known about their impact on post-COVID-19 conditions. We performed a systematic literature review and meta-analysis on the effectiveness of COVID-19 vaccination against post-COVID-19 conditions (ie, long COVID). Methods: We searched PubMed, CINAHL, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science from December 1, 2019, to April 27, 2022, for studies evaluating COVID-19 vaccine effectiveness against post-COVID-19 conditions among individuals who received at least 1 dose of Pfizer/BioNTech, Moderna, AstraZeneca, or Janssen vaccine. A post-COVID-19 condition was defined as any symptom that was present 3 or more weeks after having COVID-19. Editorials, commentaries, reviews, study protocols, and studies in the pediatric population were excluded. We calculated the pooled diagnostic odds ratios (DORs) for post-COVID-19 conditions between vaccinated and unvaccinated individuals. Vaccine effectiveness was estimated as 100% × (1 - DOR). Results: In total, 10 studies with 1,600,830 individuals evaluated the effect of vaccination on post-COVID-19 conditions, of which 6 studies were included in the meta-analysis. The pooled DOR for post-COVID-19 conditions among individuals vaccinated with at least 1 dose was 0.708 (95% confidence interval (CI), 0.692-0.725) with an estimated vaccine effectiveness of 29.2% (95% CI, 27.5%-30.8%). The vaccine effectiveness was 35.3% (95% CI, 32.3%-38.1%) among those who received the COVID-19 vaccine before having COVID-19, and 27.4% (95% CI, 25.4%-29.3%) among those who received it after having COVID-19. Conclusions: COVID-19 vaccination both before and after having COVID-19 significantly decreased post-COVID-19 conditions for the circulating variants during the study period although vaccine effectiveness was low.

Identifiers

PMID36505947
PMCPMC9726631

What OpenQuestion holds

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Registered trials

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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.