Clinical Phenotyping for Prognosis and Immunotherapy Guidance in Bacterial Sepsis and COVID-19
Year: 2024
Type: article
Abstract: OBJECTIVES: 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. DESIGN: Retrospective analysis of data from prospective clinical studies. SETTING: Greek ICUs and Internal Medicine departments. PATIENTS AND INTERVENTIONS: 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. MEASUREMENTS AND MAIN RESULTS: 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. CONCLUSIONS: 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.
Source: Critical Care Explorations
Authors: Eleni Karakike, Simeon Metallidis, Garyfallia Poulakou, Maria Kosmidou, Nikolaos K. Gatselis, Vasileios Petrakis, Nikoletta Rovina, Eleni Gkeka, Styliani Sympardi, Ilias Papanikolaou, Ioannis Koutsodimitropoulos, Vasiliki Tzavara, Georgios Adamis, Konstantinos Tsiakos, Vasilios Koulouras, Eleni Mouloudi, Eleni Antoniadou, Gykeria Vlachogianni, Souzana Anisoglou, Nikolaos Markou, Antonia Koutsoukou, Periklis Panagopoulos, Haralampos Milionis, George N. Dalekos, Miltiades Kyprianou, Evangelos J. Giamarellos-Bourboulis
Institutions: National and Kapodistrian University of Athens, Aristotle University of Thessaloniki, University of Ioannina, University Hospital of Ioannina, University of Thessaly, University Hospital of Larissa, University Hospital of Alexandroupolis, AHEPA University Hospital, Thriasio General Hospital of Elefsina, Corfu General Clinic, General Hospital of Athens G. Genimatas, Ippokrateio General Hospital of Thessaloniki, Theageneio General Hospital, Hellenic Institute for the Study of Sepsis
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,600
OpenAlex ID: W4402406333