Evidence map›Paper›PMID 35078982›Full record

ArticleNature communications2022

Immunoglobulin signature predicts risk of post-acute COVID-19 syndrome.

Carlo Cervia, Yves Zurbuchen, Patrick Taeschler, Tala Ballouz, Dominik Menges, Sara Hasler, Sarah Adamo, Miro E Raeber, Esther Bächli, Alain Rudiger and 6 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 141 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
141citing papers in PubMed, 7 pooled it
28.7field-weighted citation impact, top 1% 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

141 citing papers in PubMed, 7 syntheses or guidelines pooled it, 235 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Global prevalence of post-COVID-19 condition: a systematic review and meta-analysis of prospective evidence.Health promotion and chronic disease prevention in Canada : research, policy and practice · 2025
    Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Trial
  9. Observational
  10. Review
  11. Review
  12. Article
  13. Observational
  14. Review
  15. Article
  16. Article
  17. A Predictive Model for the Development of Long COVID in Children.International journal of environmental research and public health · 2025
    Article
  18. Review
  19. Review
  20. Article

81 more citing papers are in PubMed but not listed here.

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

16 authors at 4 institutions in 1 country.

Carlo CerviaDepartment of Immunology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.ORCID 0000-0001-7120-8739
Yves ZurbuchenDepartment of Immunology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.ORCID 0000-0001-5387-9950
Patrick TaeschlerDepartment of Immunology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Tala BallouzEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
Dominik MengesEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0001-5970-1846
Sara HaslerDepartment of Immunology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.ORCID 0000-0001-7357-9090
Sarah AdamoDepartment of Immunology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.ORCID 0000-0002-6161-3156
Miro E RaeberDepartment of Immunology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.ORCID 0000-0003-2609-0246
Esther BächliClinic for Internal Medicine, Uster Hospital, Uster, Switzerland.
Alain RudigerDepartment of Medicine, Limmattal Hospital, Schlieren, Switzerland.
Melina Stüssi-HelblingClinic for Internal Medicine, City Hospital Triemli Zurich, Zurich, Switzerland.
Lars C HuberClinic for Internal Medicine, City Hospital Triemli Zurich, Zurich, Switzerland.
Jakob NilssonDepartment of Immunology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Ulrike HeldEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0003-3105-5840
Milo A PuhanEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0003-4721-1879
Onur BoymanDepartment of Immunology, University Hospital Zurich, University of Zurich, Zurich, Switzerland. onur.boyman@uzh.ch.ORCID 0000-0001-8279-5545
University of Zurich · CHTriemli Hospital · CHSpital Limmattal · CHSpital Uster · CH

Funding

Gottfried und Julia Bangerter-Rhyner-Stiftung (Bangerter-Stiftung) YTCR 32/18Schweizerische Akademie der Medizinischen Wissenschaften (Swiss Academy of Medical Sciences) 323530-177975Schweizerische Akademie der Medizinischen Wissenschaften (Swiss Academy of Medical Sciences) 323530-191220Schweizerische Akademie der Medizinischen Wissenschaften (Swiss Academy of Medical Sciences) 323530-191230Schweizerische Akademie der Medizinischen Wissenschaften (Swiss Academy of Medical Sciences) YTCR 32/18Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) 310030-200669Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) 4078P0-198431Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) NRP 78 Implementation Programme
6 · The paper itself

Abstract

Following acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) a significant proportion of individuals develop prolonged symptoms, a serious condition termed post-acute coronavirus disease 2019 (COVID-19) syndrome (PACS) or long COVID. Predictors of PACS are needed. In a prospective multicentric cohort study of 215 individuals, we study COVID-19 patients during primary infection and up to one year later, compared to healthy subjects. We discover an immunoglobulin (Ig) signature, based on total IgM and IgG3 levels, which - combined with age, history of asthma bronchiale, and five symptoms during primary infection - is able to predict the risk of PACS independently of timepoint of blood sampling. We validate the score in an independent cohort of 395 individuals with COVID-19. Our results highlight the benefit of measuring Igs for the early identification of patients at high risk for PACS, which facilitates the study of targeted treatment and pathomechanisms of PACS.

Indexed as

AdultAgedAntibodies, ViralCohort StudiesCoughCOVID-19DyspneaFatigueFemaleFeverHumansImmunoglobulin GImmunoglobulin MMaleMiddle AgedPost-Acute COVID-19 SyndromeAntibodies, ViralImmunoglobulin GImmunoglobulin M

Identifiers

PMID35078982
PMCPMC8789854
OpenAlexW4225342167

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.