S'abonner

Biological responses to COVID-19: Insights from physiological and blood biomarker profiles - 27/05/21

Doi : 10.1016/j.retram.2021.103276 
Rosita Zakeri a, b, 1, Andrew Pickles c, d, 1, Ewan Carr c, Daniel M. Bean c, e, Kevin O’Gallagher a, Zeljko Kraljewic c, Tom Searle c, d, Anthony Shek f, James B Galloway g, James T.H. Teo b, f, Ajay M. Shah a, b, Richard J.B. Dobson c, d, h, i, Rebecca Bendayan c, d,
a King's College London British Heart Foundation Centre of Excellence, School of Cardiovascular Medicine & Sciences, London, SE5 9NU, UK 
b King’s College Hospital NHS Foundation Trust, London, UK 
c Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK 
d NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, London, UK 
e Health Data Research UK London, University College London, London, UK 
f Department of Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK 
g Centre for Rheumatic Diseases, King’s College London, London, UK 
h Institute of Health Informatics, University College London, London, UK 
i NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, UK 

Corresponding author at: Department of Biostatistics & Health Informatics SGDP Centre, IoPPN, Box PO 80, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK.Department of Biostatistics & Health Informatics SGDP CentreIoPPN, Box PO 80, De Crespigny Park, Denmark HillLondonSE5 8AFUK

Bienvenue sur EM-consulte, la référence des professionnels de santé.
Article gratuit.

Connectez-vous pour en bénéficier!

Abstract

Background

Understanding the spectrum and course of biological responses to coronavirus disease 2019 (COVID-19) may have important therapeutic implications. We sought to characterise biological responses among patients hospitalised with severe COVID-19 based on serial, routinely collected, physiological and blood biomarker values.

Methods and findings

We performed a retrospective cohort study of 1335 patients hospitalised with laboratory-confirmed COVID-19 (median age 70 years, 56 % male), between 1st March and 30th April 2020. Latent profile analysis was performed on serial physiological and blood biomarkers. Patient characteristics, comorbidities and rates of death and admission to intensive care, were compared between the latent classes. A five class solution provided the best fit. Class 1 “Typical response” exhibited a moderately elevated and rising C-reactive protein (CRP), stable lymphopaenia, and the lowest rates of 14-day adverse outcomes. Class 2 “Rapid hyperinflammatory response” comprised older patients, with higher admission white cell and neutrophil counts, which declined over time, accompanied by a very high and rising CRP and platelet count, and exibited the highest mortality risk. Class 3 “Progressive inflammatory response” was similar to the typical response except for a higher and rising CRP, though similar mortality rate. Class 4 “Inflammatory response with kidney injury” had prominent lymphopaenia, moderately elevated (and rising) CRP, and severe renal failure. Class 5 “Hyperinflammatory response with kidney injury” comprised older patients, with a very high and rising CRP, and severe renal failure that attenuated over time. Physiological measures did not substantially vary between classes at baseline or early admission.

Conclusions and relevance

Our identification of five distinct classes of biomarker profiles provides empirical evidence for heterogeneous biological responses to COVID-19. Early hyperinflammatory responses and kidney injury may signify unique pathophysiology that requires targeted therapy.

Le texte complet de cet article est disponible en PDF.

Abbreviations : ARDS, BAME, CKD, COPD, COVID-19, CRP, DBP, EHR, HF, ICU, IHD, NLP, REML, RT-PCR, SBP

Keywords : Biomarkers, Classes, Inflammation, SARS-CoV-2


Plan


© 2021  Publié par Elsevier Masson SAS.
Ajouter à ma bibliothèque Retirer de ma bibliothèque Imprimer
Export

    Export citations

  • Fichier

  • Contenu

Vol 69 - N° 2

Article 103276- mai 2021 Retour au numéro
Article précédent Article précédent
  • A novel tumor inhibitory hybridoma monoclonal antibody with dual specificity for HER3 and HER2
  • Danesh Hassani, Mohammad Mehdi Amiri, Mehdi Mohammadi, Parisa Yousefi, Mohammad Ali Judaki, Maryam Mobini, Forough Golsaz-Shirazi, Mahmood Jeddi-Tehrani, Fazel Shokri
| Article suivant Article suivant
  • Correlation analysis between virtual and Complement-Dependent-Cytotoxicity crossmatch in a monocenter retrospective series of 118 allografted patients
  • Roberto Crocchiolo, Sonia Lo Po', Daniela Lumia, Giuliana Lando, Giorgia Cornacchini, Lara Crucitti, Maria Teresa Pugliano, Elisabetta Volpato, Irene Cuppari, Elisabetta Sommaruga, Maria Grazia Pipitone, Sara Labate, Giovanni Grillo, Elisa Zucchetti, Silvano Rossini

Bienvenue sur EM-consulte, la référence des professionnels de santé.

Mon compte


Plateformes Elsevier Masson

Déclaration CNIL

EM-CONSULTE.COM est déclaré à la CNIL, déclaration n° 1286925.

En application de la loi nº78-17 du 6 janvier 1978 relative à l'informatique, aux fichiers et aux libertés, vous disposez des droits d'opposition (art.26 de la loi), d'accès (art.34 à 38 de la loi), et de rectification (art.36 de la loi) des données vous concernant. Ainsi, vous pouvez exiger que soient rectifiées, complétées, clarifiées, mises à jour ou effacées les informations vous concernant qui sont inexactes, incomplètes, équivoques, périmées ou dont la collecte ou l'utilisation ou la conservation est interdite.
Les informations personnelles concernant les visiteurs de notre site, y compris leur identité, sont confidentielles.
Le responsable du site s'engage sur l'honneur à respecter les conditions légales de confidentialité applicables en France et à ne pas divulguer ces informations à des tiers.


Tout le contenu de ce site: Copyright © 2024 Elsevier, ses concédants de licence et ses contributeurs. Tout les droits sont réservés, y compris ceux relatifs à l'exploration de textes et de données, a la formation en IA et aux technologies similaires. Pour tout contenu en libre accès, les conditions de licence Creative Commons s'appliquent.