Evidence map›Paper›PMID 34012444›Full record

ArticleFrontiers in immunology2021

Immunological Biomarkers of Fatal COVID-19: A Study of 868 Patients.

Esperanza Martín-Sánchez, Juan José Garcés, Catarina Maia, Susana Inogés, Ascensión López-Díaz de Cerio, Francisco Carmona-Torre, Marta Marin-Oto, Félix Alegre, Elvira Molano, Mirian Fernandez-Alonso and 17 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.1field-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

15 citing papers in PubMed, 33 citations in OpenAlex.

  1. Review
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  7. COVID-19: Using high-throughput flow cytometry to dissect clinical heterogeneity.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2023
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  9. Observational
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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

27 authors at 4 institutions in 2 countries.

Esperanza Martín-SánchezHematology Department, Clínica Universidad de Navarra, Pamplona, Spain.
Juan José GarcésHematology Department, Clínica Universidad de Navarra, Pamplona, Spain.
Catarina MaiaHematology Department, Clínica Universidad de Navarra, Pamplona, Spain.
Susana InogésCentro de Investigación Biomédica en Red, Pamplona, Spain.
Ascensión López-Díaz de CerioCentro de Investigación Biomédica en Red, Pamplona, Spain.
Francisco Carmona-TorreInternal Medicine Department, Clínica Universidad de Navarra, Pamplona, Spain.
Marta Marin-OtoNeumology Department, Clínica Universidad de Navarra, Pamplona, Spain.
Félix AlegreInternal Medicine Department, Clínica Universidad de Navarra, Pamplona, Spain.
Elvira MolanoInternal Medicine Department, Clínica Universidad de Navarra, Madrid, Spain.
Mirian Fernandez-AlonsoImmune and Infectious Inflammatory Diseases Research, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain.
Cristina PerezHemato-Oncology Department, Centro de Investigación Médica Aplicada (CIMA), Pamplona, Spain.
Cirino BottaHematology Department, Hospital "Annunziata", Cosenza, Italy.
Aintzane ZabaletaHematology Department, Clínica Universidad de Navarra, Pamplona, Spain.
Ana Belen AlcaideNeumology Department, Clínica Universidad de Navarra, Pamplona, Spain.
Manuel F LandechoInternal Medicine Department, Clínica Universidad de Navarra, Pamplona, Spain.
Marta RuaMicrobiology Department, Clínica Universidad de Navarra, Pamplona, Spain.
Teresa Pérez-WarnisherNeumology Department, Clínica Universidad de Navarra, Madrid, Spain.
Laura BlancoHemato-Oncology Department, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain.
Sarai SarvideHemato-Oncology Department, Centro de Investigación Médica Aplicada (CIMA), Pamplona, Spain.
Amaia Vilas-ZornozaHemato-Oncology Department, Centro de Investigación Médica Aplicada (CIMA), Pamplona, Spain.
Diego AlignaniHematology Department, Clínica Universidad de Navarra, Pamplona, Spain.
Cristina MorenoHematology Department, Clínica Universidad de Navarra, Pamplona, Spain.
Iñigo PinedaInternal Medicine Department, Clínica Universidad de Navarra, Pamplona, Spain.
Miguel SogbeInternal Medicine Department, Clínica Universidad de Navarra, Pamplona, Spain.
Josepmaria ArgemiInternal Medicine Department, Clínica Universidad de Navarra, Pamplona, Spain.
Bruno PaivaHematology Department, Clínica Universidad de Navarra, Pamplona, Spain.
José Ramón YusteInternal Medicine Department, Clínica Universidad de Navarra, Pamplona, Spain.
Clinica Universidad de Navarra · ESCentro de Investigación Biomédica en Red · ESNavarre Institute of Health Research · ESOspedale Annunziata di Cosenza · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Information on the immunopathobiology of coronavirus disease 2019 (COVID-19) is rapidly increasing; however, there remains a need to identify immune features predictive of fatal outcome. This large-scale study characterized immune responses to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection using multidimensional flow cytometry, with the aim of identifying high-risk immune biomarkers. Holistic and unbiased analyses of 17 immune cell-types were conducted on 1,075 peripheral blood samples obtained from 868 COVID-19 patients and on samples from 24 patients presenting with non-SARS-CoV-2 infections and 36 healthy donors. Immune profiles of COVID-19 patients were significantly different from those of age-matched healthy donors but generally similar to those of patients with non-SARS-CoV-2 infections. Unsupervised clustering analysis revealed three immunotypes during SARS-CoV-2 infection; immunotype 1 (14% of patients) was characterized by significantly lower percentages of all immune cell-types except neutrophils and circulating plasma cells, and was significantly associated with severe disease. Reduced B-cell percentage was most strongly associated with risk of death. On multivariate analysis incorporating age and comorbidities, B-cell and non-classical monocyte percentages were independent prognostic factors for survival in training (n=513) and validation (n=355) cohorts. Therefore, reduced percentages of B-cells and non-classical monocytes are high-risk immune biomarkers for risk-stratification of COVID-19 patients.

Indexed as

Adaptive ImmunityAdultAgedAged, 80 and overBiomarkersB-LymphocytesCOVID-19FemaleHumansImmunity, InnateLymphopeniaMaleMiddle AgedMonocytesPrognosisSARS-CoV-2BiomarkersbiomarkersCOVID-19flow cytometrylymphopeniaoutcomeSARS-CoV-2survival

Identifiers

PMID34012444
PMCPMC8126711
OpenAlexW3158579087

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.