Evidence map›Paper›PMID 32633840›Full record

ReviewJournal of medical virology2021

The variability of the serological response to SARS-corona virus-2: Potential resolution of ambiguity through determination of avidity (functional affinity).

Georg Bauer

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of medical virology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
1.3field-weighted citation impact, top 11% 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

37 citing papers in PubMed, 58 citations in OpenAlex.

  1. Review
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  4. Avidity maturation of anti-spike IgG after vaccination in COVID-19 convalescent vs COVID-19 naïve patients.APMIS : acta pathologica, microbiologica, et immunologica Scandinavica · 2025
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  16. Antibody response to SARS-CoV-2 for more than one year - kinetics and persistence of detection are predominantly determined by avidity progression and test design.Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology · 2022
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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

1 author at 1 institution in 1 country.

Georg BauerInstitute of Virology, Medical Center, University of Freiburg, Freiburg, Germany.ORCID 0000-0003-3134-3885
University of Freiburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data on the serological response toward severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 16 recent reports were analyzed and a high degree of variability was shown. Immunoglobulin M (IgM) responses were either found earlier than IgG, or together with IgG, later than IgG, or were missing. Therefore, clear distinctions between early, intermediate, and past infections are obviously not possible merely on the basis of IgM and IgG determinations. A review of publications on the serology of other virus groups shows that variable IgM responses can be found as well and therefore are not unique for SARS-CoV-2 infections. A model to explain this variability is proposed. The inclusion of avidity determination into regular diagnostic procedures has allowed to resolve such "atypical" serological constellations. The potential use of avidity determination for the diagnosis of COVID-19, for risk assessment, epidemiological studies, analysis of cross reactions, as well as for the control of vaccination programs is suggested and discussed.

Indexed as

Serologic TestsAntibodies, ViralAntibody AffinityCOVID-19COVID-19 Serological TestingHumansSARS-CoV-2Antibodies, ViralaffinityavidityIgGSARS-CoV-2serologyvariability

Identifiers

PMID32633840
PMCPMC7361859
OpenAlexW3040048637

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.