Narges Alipanah1, Carolyn S Calfee1,2. 1. Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine. 2. Department of Anesthesia, University of California San Francisco, San Francisco, California, USA.
Abstract
PURPOSE OF REVIEW: Decades of research in acute respiratory distress syndrome (ARDS) have led to few interventions that impact clinical outcomes. The pandemic of patients with ARDS due to the novel SARS-CoV-2 infection has stressed the need for more effective therapies in ARDS. Phenotyping may enable successful trials and precision therapeutics in this patient population. RECENT FINDINGS: Clinical phenotypes that group patients by shared cause, time-course or radiographic presentation are of prognostic value, but their use is limited by misclassification. Physiological phenotypes, including the P/F ratio, ventilatory ratio and dead space fraction, predict poor outcomes but can rapidly change, making them unstable over time. Biologic phenotypes have prognostic value with composite clinical and biomarker sub-phenotypes additionally impacting treatment response but are yet to be prospectively validated. SUMMARY: Although much progress has been made in ARDS phenotyping, implementation of precision medicine practices will depend on conducting phenotype-aware trials using rapid point of care assays or machine learning algorithms. Omics studies will enhance our understanding of biologic determinants of clinical outcomes in ARDS sub-phenotypes. Whether biologic ARDS sub-phenotypes are specific to this syndrome or rather more broadly identify endotypes of critical illness remains to be determined.
PURPOSE OF REVIEW: Decades of research in acute respiratory distress syndrome (ARDS) have led to few interventions that impact clinical outcomes. The pandemic of patients with ARDS due to the novel SARS-CoV-2 infection has stressed the need for more effective therapies in ARDS. Phenotyping may enable successful trials and precision therapeutics in this patient population. RECENT FINDINGS: Clinical phenotypes that group patients by shared cause, time-course or radiographic presentation are of prognostic value, but their use is limited by misclassification. Physiological phenotypes, including the P/F ratio, ventilatory ratio and dead space fraction, predict poor outcomes but can rapidly change, making them unstable over time. Biologic phenotypes have prognostic value with composite clinical and biomarker sub-phenotypes additionally impacting treatment response but are yet to be prospectively validated. SUMMARY: Although much progress has been made in ARDS phenotyping, implementation of precision medicine practices will depend on conducting phenotype-aware trials using rapid point of care assays or machine learning algorithms. Omics studies will enhance our understanding of biologic determinants of clinical outcomes in ARDS sub-phenotypes. Whether biologic ARDS sub-phenotypes are specific to this syndrome or rather more broadly identify endotypes of critical illness remains to be determined.
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