| Autor: |
Liam Townsend, Adam H. Dyer, Aifric Naughton, Sultan Imangaliyev, Jean Dunne, Rachel Kiersey, Dean Holden, Aoife Mooney, Deirdre Leavy, Katie Ridge, Jamie Sugrue, Mubarak Aldoseri, Jo Hannah Kelliher, Martina Hennessy, Declan Byrne, Paul Browne, Christopher L. Bacon, Catriona Doyle, Ruth O’Riordan, Anne-Marie McLaughlin, Ciaran Bannan, Ignacio Martin-Loeches, Arthur White, Rachel M. McLoughlin, Colm Bergin, Nollaig M. Bourke, Cliona O’Farrelly, Niall Conlon, Clíona Ní Cheallaigh |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Heliyon, Vol 8, Iss 4, Pp e09230- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2405-8440 |
| DOI: |
10.1016/j.heliyon.2022.e09230 |
| Popis: |
SARS-CoV-2 infection causes a wide spectrum of disease severity. Identifying the immunological characteristics of severe disease and the risk factors for their development are important in the management of COVID-19. This study aimed to identify and rank clinical and immunological features associated with progression to severe COVID-19 in order to investigate an immunological signature of severe disease. One hundred and eight patients with positive SARS-CoV-2 PCR were recruited. Routine clinical and laboratory markers were measured, as well as myeloid and lymphoid whole-blood immunophenotyping and measurement of the pro-inflammatory cytokines IL-6 and soluble CD25. All analysis was carried out in a routine hospital diagnostic laboratory. Univariate analysis demonstrated that severe disease was most strongly associated with elevated CRP and IL-6, loss of DLA-DR expression on monocytes and CD10 expression on neutrophils. Unbiased machine learning demonstrated that these four features were strongly associated with severe disease, with an average prediction score for severe disease of 0.925. These results demonstrate that these four markers could be used to identify patients developing severe COVID-19 and allow timely delivery of therapeutics. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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