Evidence map›Paper›PMID 32962703›Full record

ArticleRespiratory research2020

Inflammatory phenotyping predicts clinical outcome in COVID-19.

H Burke, A Freeman, D C Cellura, B L Stuart, N J Brendish, S Poole, F Borca, H T T Phan, N Sheard, S Williams and 5 more

Open access · goldAbstract read
In one paragraph

Article in Respiratory research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 7% 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

64 citing papers in PubMed, 1 synthesis or guideline pooled it, 98 citations in OpenAlex.

  1. Pathophysiological Mechanisms in Long COVID: A Mixed Method Systematic Review.International journal of environmental research and public health · 2024
    Pooled it
  2. Trial
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  13. SARS-CoV-2 Lurking and Lingering in the Depths of Lungs.American journal of respiratory and critical care medicine · 2024
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  15. Observational
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  17. Role ofSaudi journal of biological sciences · 2023
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4 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

15 authors at 3 institutions in 1 country.

H BurkeSchool of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, Southampton, SO16 6YD, UK. H.Burke@soton.ac.uk.
A FreemanSchool of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, Southampton, SO16 6YD, UK.
D C CelluraSchool of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, Southampton, SO16 6YD, UK.
B L StuartSouthampton Clinical Trials Unit, University of Southampton, Southampton, UK.
N J BrendishSchool of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, Southampton, SO16 6YD, UK.
S PooleSchool of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, Southampton, SO16 6YD, UK.
F BorcaUniversity Hospitals Southampton NHS Foundation Trust, Southampton, UK.
H T T PhanSouthampton Clinical Trials Unit, University of Southampton, Southampton, UK.
N SheardUniversity Hospitals Southampton NHS Foundation Trust, Southampton, UK.
S WilliamsUniversity Hospitals Southampton NHS Foundation Trust, Southampton, UK.
C M SpallutoSchool of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, Southampton, SO16 6YD, UK.
K J StaplesSchool of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, Southampton, SO16 6YD, UK.
T W ClarkSchool of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, Southampton, SO16 6YD, UK.
T M A WilkinsonSchool of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, Southampton, SO16 6YD, UK.
REACT COVID investigators
Southampton General Hospital · GBUniversity Hospital Southampton NHS Foundation Trust · GBUniversity of Southampton · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has led to more than 760,000 deaths worldwide (correct as of 16th August 2020). Studies suggest a hyperinflammatory response is a major cause of disease severity and death. Identitfying COVID-19 patients with hyperinflammation may identify subgroups who could benefit from targeted immunomodulatory treatments. Analysis of cytokine levels at the point of diagnosis of SARS-CoV-2 infection can identify patients at risk of deterioration.

methodsWe used a multiplex cytokine assay to measure serum IL-6, IL-8, TNF, IL-1β, GM-CSF, IL-10, IL-33 and IFN-γ in 100 hospitalised patients with confirmed COVID-19 at admission to University Hospital Southampton (UK). Demographic, clinical and outcome data were collected for analysis.

resultsAge > 70 years was the strongest predictor of death (OR 28, 95% CI 5.94, 139.45). IL-6, IL-8, TNF, IL-1β and IL-33 were significantly associated with adverse outcome. Clinical parameters were predictive of poor outcome (AUROC 0.71), addition of a combined cytokine panel significantly improved the predictability (AUROC 0.85). In those ≤70 years, IL-33 and TNF were predictive of poor outcome (AUROC 0.83 and 0.84), addition of a combined cytokine panel demonstrated greater predictability of poor outcome than clinical parameters alone (AUROC 0.92 vs 0.77).

conclusionsA combined cytokine panel improves the accuracy of the predictive value for adverse outcome beyond standard clinical data alone. Identification of specific cytokines may help to stratify patients towards trials of specific immunomodulatory treatments to improve outcomes in COVID-19.

Indexed as

Hospital MortalityAge FactorsAnalysis of VarianceArea Under CurveClinical Laboratory TechniquesCohort StudiesCoronavirus InfectionsCOVID-19COVID-19 TestingCytokinesFemaleHospitalizationHospitals, UniversityHumansIncidenceInflammation MediatorsCytokinesInflammation MediatorsCOVID-19IL-33Point-of-care testingSARS-CoV-2TNF-α

Identifiers

PMID32962703
PMCPMC7506817
OpenAlexW3088315869

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.