Identification of distinct clinical phenotypes of acute respiratory distress syndrome with differential responses to treatment

• Published in: Critical Care 2021, Vol.25 (1)
• Main Authors: Liu, Xiaowei, Jiang, Yusheng, Jia, Xiaonan, Ma, Xiaohui, Han, Ci, Guo, Nana, Peng, Yahui, Liu, Haitao, Ju, Yingnan, Luo, Xiangfeng, Li, Xueting, Bu, Yue, Zhang, Jin, Liu, Yansong, Gao, Yan, Zhao, Mingyan, Wang, Hongliang, Luo, Ligang, Yu, Kaijiang, Wang, Changsong
• Format: Report
• Language: English
• Subjects: Acute respiratory distress syndrome; Care and treatment; Critical care medicine; Diagnosis; Methods
• ISSN: 1364-8535
• DOI: 10.1186/s13054-021-03734-y

Background Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome, and the identification of homogeneous subgroups and phenotypes is the first step toward precision critical care. We aimed to explore whether ARDS phenotypes can be identified using clinical data, are reproducible and are associated with clinical outcomes and treatment response. Methods This study is based on a retrospective analysis of data from the telehealth intensive care unit (eICU) collaborative research database and three ARDS randomized controlled trials (RCTs) (ALVEOLI, FACTT and SAILS trials). We derived phenotypes in the eICU by cluster analysis based on clinical data and compared the clinical characteristics and outcomes of each phenotype. The reproducibility of the derived phenotypes was tested using the data from three RCTs, and treatment effects were evaluated. Results Three clinical phenotypes were identified in the training cohort of 3875 ARDS patients. Of the three phenotypes identified, phenotype I (n = 1565; 40%) was associated with fewer laboratory abnormalities, less organ dysfunction and the lowest in-hospital mortality rate (8%). Phenotype II (n = 1232; 32%) was correlated with more inflammation and shock and had a higher mortality rate (18%). Phenotype III (n = 1078; 28%) was strongly correlated with renal dysfunction and acidosis and had the highest mortality rate (22%). These results were validated using the data from the validation cohort (n = 3670) and three RCTs (n = 2289) and had reproducibility. Patients with these ARDS phenotypes had different treatment responses to randomized interventions. Specifically, in the ALVEOLI cohort, the effects of ventilation strategy (high PEEP vs low PEEP) on ventilator-free days differed by phenotype (p = 0.001); in the FACTT cohort, there was a significant interaction between phenotype and fluid-management strategy for 60-day mortality (p = 0.01). The fluid-conservative strategy was associated with improved mortality in phenotype II but had the opposite effect in phenotype III. Conclusion Three clinical phenotypes of ARDS were identified and had different clinical characteristics and outcomes. The analysis shows evidence of a phenotype-specific treatment benefit in the ALVEOLI and FACTT trials. These findings may improve the identification of distinct subsets of ARDS patients for exploration in future RCTs. Keywords: Acute respiratory distress syndrome, Phenotype, Cluster analysis, Clinical characteristics and