Evidence map›Paper›PMID 34855834›Full record

ArticlePloS one2021

Serial measurement of cytokines strongly predict COVID-19 outcome.

Hasan Selcuk Ozger, Resul Karakus, Elif Nazli Kuscu, Umit Emin Bagriacik, Nihan Oruklu, Melek Yaman, Melda Turkoglu, Gonca Erbas, Aysegul Yucel Atak, Esin Senol

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 11% 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

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  19. Role of Innate and Adaptive Cytokines in the Survival of COVID-19 Patients.International journal of molecular sciences · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Hasan Selcuk OzgerDepartment of Infectious Diseases and Clinical Microbiology, Faculty of Medicine, Gazi University, Ankara, Turkey.ORCID 0000-0003-3894-0092
Resul KarakusDepartment of Immunology, Faculty of Medicine, Gazi University, Ankara, Turkey.ORCID 0000-0003-2654-6119
Elif Nazli KuscuDepartment of Infectious Diseases and Clinical Microbiology, Faculty of Medicine, Gazi University, Ankara, Turkey.
Umit Emin BagriacikDepartment of Immunology, Faculty of Medicine, Gazi University, Ankara, Turkey.
Nihan OrukluDepartment of Immunology, Faculty of Medicine, Gazi University, Ankara, Turkey.
Melek YamanDepartment of Immunology, Faculty of Medicine, Gazi University, Ankara, Turkey.
Melda TurkogluDepartment of Internal Medicine and Intensive Care, Faculty of Medicine, Gazi University, Ankara, Turkey.
Gonca ErbasDepartment of Radiology, Faculty of Medicine, Gazi University, Ankara, Turkey.
Aysegul Yucel AtakDepartment of Immunology, Faculty of Medicine, Gazi University, Ankara, Turkey.
Esin SenolDepartment of Infectious Diseases and Clinical Microbiology, Faculty of Medicine, Gazi University, Ankara, Turkey.
Gazi University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeCytokines are major mediators of COVID-19 pathogenesis and several of them are already being regarded as predictive markers for the clinical course and outcome of COVID-19 cases. A major pitfall of many COVID-19 cytokine studies is the lack of a benchmark sampling timing. Since cytokines and their relative change during an infectious disease course is quite dynamic, we evaluated the predictive value of serially measured cytokines for COVID-19 cases.

methodsIn this single-center, prospective study, a broad spectrum of cytokines were determined by multiplex ELISA assay in samples collected at admission and at the third day of hospitalization. Appropriateness of cytokine levels in predicting mortality were assessed by receiver-operating characteristic (ROC) analyses for both sampling times in paralel to conventional biomarkers.

resultsAt both sampling points, higher levels of IL-6, IL-7, IL-10, IL-15, IL-27 IP-10, MCP-1, and GCSF were found to be more predictive for mortality (p<0.05). Some of these cytokines, such as IL-6, IL-10, IL-7 and GCSF, had higher sensitivity and specificity in predicting mortality. AUC values of IL-6, IL-10, IL-7 and GCSF were 0.85 (0.65 to 0.92), 0.88 (0.73 to 0.96), 0.80 (0.63 to 0.91) and 0.86 (0.70 to 0.95), respectively at hospital admission. Compared to hospital admission, on the 3rd day of hospitalization serum levels of IL-6 and, IL-10 decreased significantly in the survivor group, unlike the non-survivor group (IL-6, p = 0.015, and IL-10, p = 0.016).

conclusionOur study results suggest that single-sample-based cytokine analyzes can be misleading and that cytokine levels measured serially at different sampling times provide a more precise and accurate estimate for the outcome of COVID-19 patients.

Indexed as

AgedAged, 80 and overChemokine CCL2Chemokine CXCL10COVID-19CytokinesEnzyme-Linked Immunosorbent AssayFemaleGranulocyte Colony-Stimulating FactorHumansInterleukin-10Interleukin-15Interleukin-27Interleukin-6Interleukin-7MaleCCL2 protein, humanChemokine CCL2Chemokine CXCL10CytokinesGranulocyte Colony-Stimulating FactorInterleukin-10Interleukin-15Interleukin-27Interleukin-6Interleukin-7

Identifiers

PMID34855834
PMCPMC8639000
OpenAlexW3217315984

What OpenQuestion holds

Textmetadata
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.