Evidence map›Paper›PMID 37393304›Full record

SynthesisBMC infectious diseases2023

Long-term evaluation of the seroprevalence of SARS-CoV-2 IgG and IgM antibodies in recovered patients: a meta-analysis.

Qiu Li, Lu Chen, Fen Li, An He

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

4 authors.

Qiu LiLaboratory Medicine Center, Chenzhou First People's Hospital, Chenzhou, 423000, P.R. China.
Lu ChenBaoshan Community Hospital, Chenzhou, 424400, P.R. China.
Fen LiLaboratory Medicine Center, Chenzhou First People's Hospital, Chenzhou, 423000, P.R. China.
An HeLaboratory Medicine Center, Chenzhou First People's Hospital, Chenzhou, 423000, P.R. China. 41325777@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Estimating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) -specific immunoglobulin G (IgG) immunoglobulin M (IgM) antibodies are increasingly important for tracking the spread of infection and defining herd immunity barrier and individual immunization levels in the ongoing coronavirus disease 2019 (COVID-19) pandemic. Therefore, we conducted the present systematic review and meta-analysis to evaluate the seroprevalence of SARS-CoV-2 IgM and IgG antibodies of recovered COVID-19 patients in long-term follow-up studies. A systematic search of the MEDLINE, Embase, COVID-19 Primer, PubMed, CNKI, and the Public Health England library databases was conducted. Twenty-fourth eligible studies were included. Meta-analysis showed that 27% (95%CI: 0.04-0.49) and 66% (95%CI:0.47-0.85) were seropositive for SARS-CoV-2 IgM and IgG, respectively, while in long-term 12 months following up studies, the seroprevalences of IgM antibody (17%) decreased and IgG antibody (75%) was higher than 6 months follow-up patients. However, due to the limited number of relevant studies, the high level of heterogeneity, and the large gap in studies conducted, the findings of our study may not accurately reflect the true seroprevalence status of SARS-CoV-2 infection. Nevertheless, sequential vaccination or booster immunization is considered to be a necessary long-term strategy to sustain the fight against the pandemic.

Indexed as

COVID-19SARS-CoV-2HumansImmunization, SecondaryImmunoglobulin GImmunoglobulin MSeroepidemiologic StudiesImmunoglobulin GImmunoglobulin MCOVID-19IgGIgMRecovered patientsSARS-CoV-2Seroprevalence

Identifiers

PMID37393304
PMCPMC10314509

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.