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Updated: Jun 6, 2025
A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Phenotypic Characterization of Intensive Care Patients With Infections: A Pilot Study of Host and Pathogen-Based
André Oliveira1, Ana Rita Fernandes2, Tânia F Mendes3
1Intensive Care Department, Hospital Vila Franca de XIra, Lisbon, PRT.
Introduction:
Sepsis is a prevalent, albeit complex, disorder among critically ill patients and a "one-size-fits-all" approach does not seem applicable. Host intrinsic characteristics and microorganisms' particularities may influence response to therapy and outcomes. Attempting to group patients and microorganism characteristics may be an important step in developing and facilitating personalized infection treatment plans. This work intends to identify infected patients' clusters using clinical data that includes infection determinants: the isolated pathogen and the site of infection.
Methods:
In this retrospective analysis, we included patients with a microbiologically documented infection and non-infected controls. Patients admitted between January 2015 and December 2019 in the intensive care unit (ICU) were included (aged 17-95 years). Those with isolated microorganisms during their ICU stay were further analyzed using cluster analysis (hierarchical clustering and K-means; SPSS version 25.0). Four primary outcomes were addressed: ICU and hospital mortality rate and ICU and hospital length of stay (LOS).
Results:
This study included 1,923 patients, of whom 721 (37.5%) had at least one microbiological isolate during their ICU stay. Patients with at least one isolate identification were older (mean age 67.7 years vs. 65 years; p < 0.001) and had a higher ICU and hospital mortality (20.3% vs. 24.3%, p = 0.041; 26.9% vs. 38.4%, p < 0.001), as well as a longer LOS (median hospital LOS 8 vs. 18 days; p < 0.001) than patients without microorganisms identified. Patients with at least one isolated microorganism were divided into five different clusters. Notable differences were found in their ICU and hospital trajectories between clusters.
Conclusion:
The cluster analysis approach provided valuable insights into the complex interplay between bacterial virulence, infection site, and patient outcomes in critical care medicine. Patients infected with bacteraemia by Gram-positive bacteria (cluster 2) or Enterobacteriaceae (Cluster 5) and fungal isolation in respiratory samples (Cluster 3) should prompt more aggressive clinical interventions, as these patients are more prone to die in the hospital.
