Evidence mapPaperPMID 38839796Full record

ArticleScientific reports2024

Longitudinal soluble marker profiles reveal strong association between cytokine storms resulting from macrophage activation and disease severity in COVID-19 disease.

Krista E van Meijgaarden, Suzanne van Veen, Roula Tsonaka, Paula Ruibal, Anna H E Roukens, Sesmu M Arbous, Judith Manniën, Suzanne C Cannegieter, Tom H M Ottenhoff, Simone A Joosten and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Immune Dysregulation After COVID-19: Longitudinal Analysis up to 9 Months.International journal of molecular sciences · 2026
    Article
  3. Review
  4. Review
  5. 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

12 authors.

Krista E van Meijgaarden *Department of Infectious Diseases, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.
Suzanne van Veen *Department of Infectious Diseases, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.
Roula Tsonaka *Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
Paula RuibalDepartment of Infectious Diseases, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.
Anna H E RoukensDepartment of Infectious Diseases, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.
Sesmu M ArbousDepartment of Intensive Care Medicine, Leiden University Medical Center, Leiden, The Netherlands.
Judith ManniënDepartment of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
Suzanne C CannegieterDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Tom H M OttenhoffDepartment of Infectious Diseases, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.
Simone A JoostenDepartment of Infectious Diseases, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands. S.a.joosten@lumc.nl.
BEAT-COVID group
COVID-19 LUMC group

Funding

Leiden University Fund Crowdfunding Wake Up To Corona
6 · The paper itself

Abstract

SARS-CoV2 infection results in a range of disease severities, but the underlying differential pathogenesis is still not completely understood. At presentation it remains difficult to estimate and predict severity, in particular, identify individuals at greatest risk of progression towards the most severe disease-states. Here we used advanced models with circulating serum analytes as variables in combination with daily assessment of disease severity using the SCODA-score, not only at single time points but also during the course of disease, to correlate analyte levels and disease severity. We identified a remarkably strong pro-inflammatory cytokine/chemokine profile with high levels for sCD163, CCL20, HGF, CHintinase3like1 and Pentraxin3 in serum which correlated with COVID-19 disease severity and overall outcome. Although precise analyte levels differed, resulting biomarker profiles were highly similar at early and late disease stages, and even during convalescence similar biomarkers were elevated and further included CXCL3, CXCL6 and Osteopontin. Taken together, strong pro-inflammatory marker profiles were identified in patients with COVID-19 disease which correlated with overall outcome and disease severity.

Indexed as

BiomarkersCOVID-19Macrophage ActivationSeverity of Illness IndexAdultAgedC-Reactive ProteinCytokine Release SyndromeCytokinesFemaleHumansMaleMiddle AgedPentraxinsSARS-CoV-2Serum Amyloid P-ComponentBiomarkersC-Reactive ProteinCytokinesPentraxinsSerum Amyloid P-Component

Identifiers

PMID38839796
PMCPMC11153563

What Socratic 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 Socratic graph.