Critical Care Explorations (Sep 2024)

Clinical Phenotyping for Prognosis and Immunotherapy Guidance in Bacterial Sepsis and COVID-19

  • Eleni Karakike, MD, PhD,
  • Simeon Metallidis, MD, PhD,
  • Garyfallia Poulakou, MD, PhD,
  • Maria Kosmidou, MD, PhD,
  • Nikolaos K. Gatselis, MD, PhD,
  • Vasileios Petrakis, MD, PhD,
  • Nikoletta Rovina, MD, PhD,
  • Eleni Gkeka, MD, PhD,
  • Styliani Sympardi, MD, PhD,
  • Ilias Papanikolaou, MD, PhD,
  • Ioannis Koutsodimitropoulos, MD, PhD,
  • Vasiliki Tzavara, MD, PhD,
  • Georgios Adamis, MD, PhD,
  • Konstantinos Tsiakos, MD,
  • Vasilios Koulouras, MD, PhD,
  • Eleni Mouloudi, MD, PhD,
  • Eleni Antoniadou, MD, PhD,
  • Gykeria Vlachogianni, MD, PhD,
  • Souzana Anisoglou, MD, PhD,
  • Nikolaos Markou, MD, PhD,
  • Antonia Koutsoukou, MD, PhD,
  • Periklis Panagopoulos, MD, PhD,
  • Haralampos Milionis, MD, PhD,
  • George N. Dalekos, MD, PhD,
  • Miltiades Kyprianou,
  • Evangelos J. Giamarellos-Bourboulis, MD, PhD

DOI
https://doi.org/10.1097/CCE.0000000000001153
Journal volume & issue
Vol. 6, no. 9
p. e1153

Abstract

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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.