Classifying ARDS by dynamic or static oxygenation impairment or are other approaches needed for greater value

In this issue, Bai et al present a novel approach to classifying acute respiratory distress syndrome (ARDS), analysing how oxygenation trajectories over the first days of ventilation relate to outcomes, rather than relying on a single static measurement.1 Using data from multiple databases, they applied group-based trajectory modelling to identify three distinct subgroups of patients based on the evolution of oxygenation. These subgroups were termed ‘persistently low’, ‘gradually increasing’ and ‘rapid improving’. They demonstrate that dynamic subgroups are more strongly associated with patient outcomes and reveal clearer treatment differences with respect to positive end-expiratory pressure (PEEP) strategies than conventional static categories.2 The work highlights the potential of trajectory-based approaches in improving prognostication in patients with ARDS. The findings also raise important considerations for future clinical trials, suggesting that dynamic patient subphenotyping could improve the identification of those most likely to benefit from specific interventions. Overall, this work contributes to the growing recognition that time-dependent physiological changes may offer meaningful insights into disease severity and treatment responses.