Scholarlink

Background <p>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.</p> Methods <p>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.</p> Results <p>Fifty-eight patients were analysed, with a total of 201 level assessments performed. None showed hyperinflammatory phenotype within 48&#xa0;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, <i>P</i> = 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%, <i>p</i> = 0.0333).</p> Conclusions <p>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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月28日

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

摘要

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 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).

Conclusions

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.