TY - JOUR
T1 - Clinical sepsis phenotypes in critically ill COVID-19 patients
AU - Bruse, Niklas
AU - Kooistra, Emma J.
AU - Jansen, Aron
AU - van Amstel, Rombout B. E.
AU - de Keizer, Nicolette F.
AU - Kennedy, Jason N.
AU - Seymour, Christopher
AU - van Vught, Lonneke A.
AU - Pickkers, Peter
AU - Kox, Matthijs
N1 - Funding Information: This work was funded by The Netherlands Organisation for Health Research and Development (ZonMw) COVID-19 Programme in the bottom-up focus area 1 “Predictive diagnostics and treatment” for theme 3 “Risk analysis and prognostics” (project number 10430 01 201 0011: IRIS). Furthermore, it was supported by a Clinical Research Award from the European Society of Intensive Care Medicine (ESICM, awarded to MK). The funders had no role in the design of the study or writing the manuscript. Publisher Copyright: © 2022, The Author(s).
PY - 2022/12/1
Y1 - 2022/12/1
N2 - Background: A 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. Methods: We 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. Results: Phenotype 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. Conclusions: Classification of critically ill COVID-19 patients into clinical phenotypes may aid prognostication, prediction of treatment efficacy, and facilitation of personalized medicine.
AB - Background: A 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. Methods: We 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. Results: Phenotype 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. Conclusions: Classification of critically ill COVID-19 patients into clinical phenotypes may aid prognostication, prediction of treatment efficacy, and facilitation of personalized medicine.
KW - COVID-19
KW - Dexamethasone
KW - Personalized medicine
KW - Phenotypes
KW - Sepsis
UR - http://www.scopus.com/inward/record.url?scp=85135603181&partnerID=8YFLogxK
U2 - https://doi.org/10.1186/s13054-022-04118-6
DO - https://doi.org/10.1186/s13054-022-04118-6
M3 - Article
C2 - 35945618
SN - 1466-609X
VL - 26
JO - Critical Care
JF - Critical Care
IS - 1
M1 - 244
ER -