Evidence map›Paper›PMID 38871772›Full record

ArticleScientific reports2024

Serum cytokine dysregulation signatures associated with COVID-19 outcomes in high mortality intensive care unit cohorts across pandemic waves and variants.

Henrike Maaß, Mario Ynga-Durand, Marko Milošević, Fran Krstanović, Marina Pribanić Matešić, Iva Žuža, Stipan Jonjić, Ilija Brizić, Alan Šustić, Frank Bloos and 3 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 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  10. Utility of Protein Markers in COVID-19 Patients.International journal of molecular sciences · 2025
    Review
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  12. Article
  13. Review
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

13 authors.

Henrike Maaß *Department of Viral Immunology, Helmholtz Center for Infection Research, Braunschweig, Germany.
Mario Ynga-Durand *Department of Viral Immunology, Helmholtz Center for Infection Research, Braunschweig, Germany.
Marko MiloševićDepartment of Anesthesiology, Faculty of Medicine, Reanimation, Intensive Care and Emergency Medicine, University of Rijeka, Rijeka, Croatia.
Fran KrstanovićFaculty of Medicine, Center for Proteomics, University of Rijeka, Rijeka, Croatia.
Marina Pribanić MatešićFaculty of Medicine, Center for Proteomics, University of Rijeka, Rijeka, Croatia.
Iva ŽužaDepartment of Radiology, Clinical Hospital Centre Rijeka, Rijeka, Croatia.
Stipan JonjićFaculty of Medicine, Center for Proteomics, University of Rijeka, Rijeka, Croatia.
Ilija BrizićFaculty of Medicine, Center for Proteomics, University of Rijeka, Rijeka, Croatia.
Alan ŠustićDepartment of Anesthesiology, Faculty of Medicine, Reanimation, Intensive Care and Emergency Medicine, University of Rijeka, Rijeka, Croatia.
Frank BloosDepartment of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Jena, Germany.
SepNet Critical Care Trials Group
Alen ProtićDepartment of Anesthesiology, Faculty of Medicine, Reanimation, Intensive Care and Emergency Medicine, University of Rijeka, Rijeka, Croatia.
Luka Čičin-ŠainDepartment of Viral Immunology, Helmholtz Center for Infection Research, Braunschweig, Germany. Luka.Cicin-Sain@helmholtz-hzi.de.

Funding

Croatian Science Foundation IP-CORONA-04-2073Helmholtz Association EU partnering grant PIE-0008Helmholtz Association's Initiative and Networking Fund KA1-Co-02 "COVIPA"RESIST Excellence cluster EXC 2155, project B6
6 · The paper itself

Abstract

The aim of this study was to characterize the systemic cytokine signature of critically ill COVID-19 patients in a high mortality setting aiming to identify biomarkers of severity, and to explore their associations with viral loads and clinical characteristics. We studied two COVID-19 critically ill patient cohorts from a referral centre located in Central Europe. The cohorts were recruited during the pre-alpha/alpha (November 2020 to April 2021) and delta (end of 2021) period respectively. We determined both the serum and bronchoalveolar SARS-CoV-2 viral load and identified the variant of concern (VoC) involved. Using a cytokine multiplex assay, we quantified systemic cytokine concentrations and analyzed their relationship with clinical findings, routine laboratory workup and pulmonary function data obtained during the ICU stay. Patients who did not survive had a significantly higher systemic and pulmonary viral load. Patients infected with the pre-alpha VoC showed a significantly lower viral load in comparison to those infected with the alpha- and delta-variants. Levels of systemic CTACK, M-CSF and IL-18 were significantly higher in non-survivors in comparison to survivors. CTACK correlated directly with APACHE II scores. We observed differences in lung compliance and the association between cytokine levels and pulmonary function, dependent on the VoC identified. An intra-cytokine analysis revealed a loss of correlation in the non-survival group in comparison to survivors in both cohorts. Critically ill COVID-19 patients exhibited a distinct systemic cytokine profile based on their survival outcomes. CTACK, M-CSF and IL-18 were identified as mortality-associated analytes independently of the VoC involved. The Intra-cytokine correlation analysis suggested the potential role of a dysregulated systemic network of inflammatory mediators in severe COVID-19 mortality.

Indexed as

COVID-19Critical IllnessCytokinesIntensive Care UnitsSARS-CoV-2AgedBiomarkersCohort StudiesFemaleHumansMaleMiddle AgedPandemicsViral LoadBiomarkersCytokinesBiomarkerCOVID-19CytokinesMortalitySARS-CoV-2Variant of concern

Identifiers

PMID38871772
PMCPMC11176334

What OpenQuestion holds

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LicenceCC BY
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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.