Clinical sepsis phenotypes in critically ill COVID-19 patients
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...
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| Published in: | Critical care (London, England) Vol. 26; no. 1; pp. 1 - 6 |
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| Main Authors: | , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
London
BioMed Central
09.08.2022
BioMed Central Ltd Springer Nature B.V BMC |
| Subjects: | |
| ISSN: | 1364-8535, 1466-609X, 1364-8535, 1366-609X, 1466-609X |
| Online Access: | Get full text |
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| Summary: | 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. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 1364-8535 1466-609X 1364-8535 1366-609X 1466-609X |
| DOI: | 10.1186/s13054-022-04118-6 |