Clustering ICU patients with sepsis based on the patterns of their circulating biomarkers: A secondary analysis of the CAPTAIN prospective multicenter cohort study

• Published in: PloS one 2022-10, Vol.17 (10), p.e0267517-e0267517
• Main Authors: Misset, Benoît, Philippart, François, Fitting, Catherine, Bedos, Jean-Pierre, Diehl, Jean-Luc, Hamzaoui, Olfa, Annane, Djillali, Journois, Didier, Parlato, Marianna, Moucadel, Virginie, Cavaillon, Jean-Marc, Coste, Joël
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; Anesthesia & intensive care; Anesthésie & soins intensifs; Anti-inflammatory agents; Bacterial infections; Biological markers; Biology and Life Sciences; Biomarkers; Care and treatment; Clinical trials; Cluster Analysis; Clustering; Cohort analysis; Cohort Studies; Critically ill; Diagnosis; Ecology, environment; Health; Human health sciences; Humans; Infections; Inflammation; Intensive care; Intensive Care Units; Life Sciences; Medicine and Health Sciences; Methods; Middle Aged; Mortality; Multidisciplinary; Patients; Physical Sciences; Pneumonia; Principal components analysis; Prospective Studies; Research and Analysis Methods; Sciences de la santé humaine; Secondary analysis; Sepsis; Sepsis/diagnosis; Sepsis/therapy; Services; Subgroups
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0267517

Although sepsis is a life-threatening condition, its heterogeneous presentation likely explains the negative results of most trials on adjunctive therapy. This study in patients with sepsis aimed to identify subgroups with similar immune profiles and their clinical and outcome correlates. A secondary analysis used data of a prospective multicenter cohort that included patients with early assessment of sepsis. They were described using Predisposition, Insult, Response, Organ failure sepsis (PIRO) staging system. Thirty-eight circulating biomarkers (27 proteins, 11 mRNAs) were assessed at sepsis diagnosis, and their patterns were determined through principal component analysis (PCA). Hierarchical clustering was used to group the patients and k-means algorithm was applied to assess the internal validity of the clusters. Two hundred and three patients were assessed, of median age 64.5 [52.0-77.0] years and SAPS2 score 55 [49-61] points. Five main patterns of biomarkers and six clusters of patients (including 42%, 21%, 17%, 9%, 5% and 5% of the patients) were evidenced. Clusters were distinguished according to the certainty of the causal infection, inflammation, use of organ support, pro- and anti-inflammatory activity, and adaptive profile markers. In this cohort of patients with suspected sepsis, we individualized clusters which may be described with criteria used to stage sepsis. As these clusters are based on the patterns of circulating biomarkers, whether they might help to predict treatment responsiveness should be addressed in further studies.