Clinical Phenotyping for Prognosis and Immunotherapy Guidance in Bacterial Sepsis and COVID-19.
COVID-19
immunotherapy
mortality
phenotypes
sepsis
Journal
Critical care explorations
ISSN: 2639-8028
Titre abrégé: Crit Care Explor
Pays: United States
ID NLM: 101746347
Informations de publication
Date de publication:
Sep 2024
Sep 2024
Historique:
medline:
12
9
2024
pubmed:
12
9
2024
entrez:
12
9
2024
Statut:
epublish
Résumé
It is suggested that sepsis may be classified into four clinical phenotypes, using an algorithm employing 29 admission parameters. We applied a simplified phenotyping algorithm among patients with bacterial sepsis and severe COVID-19 and assessed characteristics and outcomes of the derived phenotypes. Retrospective analysis of data from prospective clinical studies. Greek ICUs and Internal Medicine departments. We analyzed 1498 patients, 620 with bacterial sepsis and 878 with severe COVID-19. We implemented a six-parameter algorithm (creatinine, lactate, aspartate transaminase, bilirubin, C-reactive protein, and international normalized ratio) to classify patients with bacterial sepsis intro previously defined phenotypes. Patients with severe COVID-19, included in two open-label immunotherapy trials were subsequently classified. Heterogeneity of treatment effect of anakinra was assessed. The primary outcome was 28-day mortality. The algorithm validated the presence of the four phenotypes across the cohort of bacterial sepsis and the individual studies included in this cohort. Phenotype α represented younger patients with low risk of death, β was associated with high comorbidity burden, and δ with the highest mortality. Phenotype assignment was independently associated with outcome, even after adjustment for Charlson Comorbidity Index. Phenotype distribution and outcomes in severe COVID-19 followed a similar pattern. A simplified algorithm successfully identified previously derived phenotypes of bacterial sepsis, which were predictive of outcome. This classification may apply to patients with severe COVID-19 with prognostic implications.
Identifiants
pubmed: 39263383
doi: 10.1097/CCE.0000000000001153
pii: CCE-D-24-00170
pmc: PMC11390041
doi:
Substances chimiques
Interleukin 1 Receptor Antagonist Protein
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1153Informations de copyright
Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.