Evidence map›Paper›PMID 34398806›Full record

ArticleImmunoHorizons2021

Specific COVID-19 Symptoms Correlate with High Antibody Levels against SARS-CoV-2.

Maya F Amjadi, Sarah E O'Connell, Tammy Armbrust, Aisha M Mergaert, Sandeep R Narpala, Peter J Halfmann, S Janna Bashar, Christopher R Glover, Anna S Heffron, Alison Taylor and 6 more

Open access · goldAbstract read
In one paragraph

Article in ImmunoHorizons, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.7field-weighted citation impact, top 13% 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

15 citing papers in PubMed, 29 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 2 institutions in 1 country.

Maya F AmjadiDepartment of Medicine, University of Wisconsin-Madison, Madison, WI.ORCID 0000-0003-3825-3495
Sarah E O'ConnellVaccine Immunology Program, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD.
Tammy ArmbrustDepartment of Pathobiological Sciences, School of Veterinary Medicine, Influenza Research Institute, University of Wisconsin-Madison, Madison, WI.
Aisha M MergaertDepartment of Medicine, University of Wisconsin-Madison, Madison, WI.ORCID 0000-0002-8177-9161
Sandeep R NarpalaVaccine Immunology Program, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD.
Peter J HalfmannDepartment of Pathobiological Sciences, School of Veterinary Medicine, Influenza Research Institute, University of Wisconsin-Madison, Madison, WI.
S Janna BasharDepartment of Medicine, University of Wisconsin-Madison, Madison, WI.
Christopher R GloverDepartment of Medicine, University of Wisconsin-Madison, Madison, WI.ORCID 0000-0003-3369-7257
Anna S HeffronDepartment of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI.ORCID 0000-0001-7555-4137
Alison TaylorVaccine Immunology Program, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD.ORCID 0000-0002-2319-8481
Britta FlachVaccine Immunology Program, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD.
David H O'ConnorDepartment of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI.
Yoshihiro KawaokaDepartment of Pathobiological Sciences, School of Veterinary Medicine, Influenza Research Institute, University of Wisconsin-Madison, Madison, WI.
Adrian B McDermottVaccine Immunology Program, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD.
Ajay K SethiDepartment of Population Health Sciences, University of Wisconsin-Madison, Madison, WI; and.ORCID 0000-0002-5537-9586
Miriam A ShelefDepartment of Medicine, University of Wisconsin-Madison, Madison, WI; mshelef@medicine.wisc.edu.ORCID 0000-0002-8842-0303
University of Wisconsin–Madison · USNational Institutes of Health · US

Funding

INTEGRATED TRAINING FOR PHYSICIAN-SCIENTISTST32GM008692 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI BURKARD, MARK E · 1998 to 2020
$10.3M
Biology of Aging and Age-Related Diseases Training GrantT32AG000213 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Rozalyn M. Anderson, Sanjay Asthana · 1991 to 2026
$9.9M
RESEARCH TRAINING IN HEMATOLOGYT32HL007899 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI Jane Ellen Churpek · 1998 to 2026
$8.2M
Integrated Training For Physician-ScientistsT32GM140935 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Anna Huttenlocher, Jeniel E Nett · 2021 to 2026
$6.5M
Parasitology and Vector Biology Training ProgramT32AI007414 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI Lyric Colleen Bartholomay · 1992 to 2026
$4.5M
NHLBI NIH HHS T32 HL007899NIAID NIH HHS T32 AI007414NIA NIH HHS T32 AG000213NIGMS NIH HHS T32 GM008692NIGMS NIH HHS T32 GM140935
6 · The paper itself

Abstract

Lasting immunity will be critical for overcoming COVID-19. However, the factors associated with the development of high titers of anti-SARS-CoV-2 Abs and how long those Abs persist remain incompletely defined. In particular, an understanding of the relationship between COVID-19 symptoms and anti-SARS-CoV-2 Abs is limited. To address these unknowns, we quantified serum anti-SARS- CoV-2 Abs in clinically diverse COVID-19 convalescent human subjects 5 wk (

Indexed as

AdultAntibodies, NeutralizingAntibodies, ViralCohort StudiesCOVID-19FemaleHospitalizationHumansImmunoglobulin GLinear ModelsMaleMiddle AgedMultivariate AnalysisPandemicsSARS-CoV-2Severity of Illness IndexAntibodies, NeutralizingAntibodies, ViralImmunoglobulin G

Identifiers

PMID34398806
PMCPMC8452279
OpenAlexW3172914906

What OpenQuestion holds

Textmetadata
LicenceTDM
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.