tetano
Editor, Senior Moderator
Crit Care
. 2022 Aug 9;26(1):244.
doi: 10.1186/s13054-022-04118-6.
Clinical sepsis phenotypes in critically ill COVID-19 patients
Niklas Bruse[SUP] 1 [/SUP], Emma J Kooistra[SUP] 1 [/SUP], Aron Jansen[SUP] 1 [/SUP], Rombout B E van Amstel[SUP] 2 [/SUP], Nicolette F de Keizer[SUP] 3 4 5 [/SUP], Jason N Kennedy[SUP] 6 [/SUP], Christopher Seymour[SUP] 6 [/SUP], Lonneke A van Vught[SUP] 2 [/SUP], Peter Pickkers[SUP] 1 [/SUP], Matthijs Kox[SUP] 7 [/SUP]
Affiliations
Abstract
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.
Keywords: COVID-19; Dexamethasone; Personalized medicine; Phenotypes; Sepsis.
. 2022 Aug 9;26(1):244.
doi: 10.1186/s13054-022-04118-6.
Clinical sepsis phenotypes in critically ill COVID-19 patients
Niklas Bruse[SUP] 1 [/SUP], Emma J Kooistra[SUP] 1 [/SUP], Aron Jansen[SUP] 1 [/SUP], Rombout B E van Amstel[SUP] 2 [/SUP], Nicolette F de Keizer[SUP] 3 4 5 [/SUP], Jason N Kennedy[SUP] 6 [/SUP], Christopher Seymour[SUP] 6 [/SUP], Lonneke A van Vught[SUP] 2 [/SUP], Peter Pickkers[SUP] 1 [/SUP], Matthijs Kox[SUP] 7 [/SUP]
Affiliations
- PMID: 35945618
- DOI: 10.1186/s13054-022-04118-6
Abstract
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.
Keywords: COVID-19; Dexamethasone; Personalized medicine; Phenotypes; Sepsis.