Biomarkers trajectories in critically ill patients with COVID-19 acute respiratory distress syndrome: insights from latent class growth analysis
Abstract
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common condition requiring intensive care, with limited effective treatments due to its clinical and biological heterogeneity. Efforts in critical care medicine have identified ARDS sub-phenotypes, hyperinflammatory and hypoinflammatory, which suggest underlying heterogeneity in patient responses. Studies have detected a low prevalence of the hyperinflammatory phenotype in ARDS patients related to Coronavirus Disease 2019 (COVID-19). To identify targeted therapeutic interventions, this study applied growth mixture models to longitudinal biomarker data to determine specific latent trajectory groups. METHODS: This is a secondary analysis of a cohort study on patients with COVID-19 pneumonia admitted to an Italian intensive care unit (ICU) with at least two assessments of inflammatory marker levels within 28 days of admission. Plasma levels of interleukin 6 (IL-6), interleukin-8 (IL-8), soluble tumour necrosis factor receptor 1 (sTNFR-1), intercellular adhesion molecule 1 (ICAM-1), soluble receptor for advanced glycation end products (sRAGE) and angiopoietin-2 (Ang2) were assessed. RESULTS: Fifty-eight patients were analysed, with a total of 201 level assessments performed. None showed hyperinflammatory phenotype within 48 h of ICU admission. Latent class growth analysis identified distinct trajectories for sTNFR-1, ICAM-1, and sRAGE, with sTNFR-1 class 1 including 39.7% of patients showing elevated levels escalating…
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Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence.
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