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- Niklas Bruse, Emma J Kooistra, Aron Jansen, Rombout B E van Amstel, Nicolette F de Keizer, Jason N Kennedy, Christopher Seymour, Lonneke A van Vught, Peter Pickkers, and Matthijs Kox.
- Department of Intensive Care Medicine, Radboud University Medical Center, Postbus 9101, 6500 HB, Nijmegen, The Netherlands.
- Crit Care. 2022 Aug 9; 26 (1): 244.
BackgroundA greater understanding of disease heterogeneity may facilitate precision medicine for coronavirus disease 2019 (COVID-19). Previous work identified four distinct clinical phenotypes associated with outcome and treatment responses in non-COVID-19 sepsis patients, but it is unknown if and how these phenotypes are recapitulated in COVID-19 sepsis patients.MethodsWe applied the four non-COVID-19 sepsis phenotypes to a total of 52,274 critically ill patients, comprising two cohorts of COVID-19 sepsis patients (admitted before and after the introduction of dexamethasone as standard treatment) and three non-COVID-19 sepsis cohorts (non-COVID-19 viral pneumonia sepsis, bacterial pneumonia sepsis, and bacterial sepsis of non-pulmonary origin). Differences in proportions of phenotypes and their associated mortality were determined across these cohorts.ResultsPhenotype distribution was highly similar between COVID-19 and non-COVID-19 viral pneumonia sepsis cohorts, whereas the proportion of patients with the δ-phenotype was greater in both bacterial sepsis cohorts compared to the viral sepsis cohorts. The introduction of dexamethasone treatment was associated with an increased proportion of patients with the δ-phenotype (6% vs. 11% in the pre- and post-dexamethasone COVID-19 cohorts, respectively, p < 0.001). Across the cohorts, the α-phenotype was associated with the most favorable outcome, while the δ-phenotype was associated with the highest mortality. Survival of the δ-phenotype was markedly higher following the introduction of dexamethasone (60% vs 41%, p < 0.001), whereas no relevant differences in survival were observed for the other phenotypes among COVID-19 patients.ConclusionsClassification of critically ill COVID-19 patients into clinical phenotypes may aid prognostication, prediction of treatment efficacy, and facilitation of personalized medicine.© 2022. The Author(s).
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