Biomarkers trajectories in critically ill patients with COVID-19 acute respiratory distress syndrome: insights from latent class growth analysis

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. 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. 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 during ICU stay. Compared to sTNFR-1 class 2, class 1 patients were older (63.8 ± 14.7 versus 58.4 ± 12.7, P = 0.0486), had higher baseline inflammatory marker levels (IL-6, IL-8, sRAGE, and sTNFR-1), higher proportions of prone positioning and continuous renal replacement therapy utilization, and a higher mortality rate (56.5% versus 28.6%, p = 0.0333). In our cohort of critically ill patients with severe COVID-19, we identified distinct latent trajectories based on longitudinal data of inflammatory markers. sTNFR-1 levels identified a subgroup with a hypoinflammatory phenotype, demonstrating a mortality rate comparable to that typically observed in ARDS hyperinflammatory phenotype. These findings point out the criticality of delineating distinct patient subgroups within the context of ARDS and COVID-19, enhancing clinical management and optimizing patient prognosis.

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Publication Details

Journal
BMC Pulmonary Medicine
Published
2025-10-28
DOI
https://doi.org/10.1186/s12890-025-03961-x
Citations
1
Primary Topic
COVID-19 Clinical Research Studies
Type
article
Field-Weighted Citation Impact
1.40

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article

Biomarkers trajectories in critically ill patients with COVID-19 acute respiratory distress syndrome: insights from latent class growth analysis

Vittorio Scaravilli, Chiara Ferraris Fusarini, Mauro Panigada, Elena Trombetta et al.
1 citations
BMC Pulmonary Medicine
COVID-19 Clinical Research Studies
1.40
article

Biomarkers trajectories in critically ill patients with COVID-19 acute respiratory distress syndrome: insights from latent class growth analysis

Vittorio Scaravilli, Chiara Ferraris Fusarini, Mauro Panigada, Elena Trombetta, Amedeo Guzzardella, Alberto Zanella, Fabiana Madotto, Kevin Delucchi, Eleonora Carlesso, Gaetano Florio, Carolyn S. Calfee, Fiorenza Ferrari, Giacomo Grasselli, Marta Tornese
article en
1 citations

Abstract

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. 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. 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 during ICU stay. Compared to sTNFR-1 class 2, class 1 patients were older (63.8 ± 14.7 versus 58.4 ± 12.7, P = 0.0486), had higher baseline inflammatory marker levels (IL-6, IL-8, sRAGE, and sTNFR-1), higher proportions of prone positioning and continuous renal replacement therapy utilization, and a higher mortality rate (56.5% versus 28.6%, p = 0.0333). In our cohort of critically ill patients with severe COVID-19, we identified distinct latent trajectories based on longitudinal data of inflammatory markers. sTNFR-1 levels identified a subgroup with a hypoinflammatory phenotype, demonstrating a mortality rate comparable to that typically observed in ARDS hyperinflammatory phenotype. These findings point out the criticality of delineating distinct patient subgroups within the context of ARDS and COVID-19, enhancing clinical management and optimizing patient prognosis.

BMC Pulmonary MedicineVol. 25(1)
University of California, San Francisco (US), University of Milan (IT), Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT)
Ministero della Salute
Openalex Percentile: Top 15%
COVID-19 Clinical Research Studies
1.40
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