Event sponsored by:
AI Health
Biomedical Engineering (BME)
Biostatistics and Bioinformatics
Computer Science
CTSI CREDO
Division of Pulmonary, Allergy, and Critical Care Medicine
Duke Clinical and Translational Science Award (CTSA)
Duke Clinical Research Institute (DCRI)
Duke Regeneration Center
Electrical and Computer Engineering (ECE)
Statistical Science
Contact:
Duke AI HealthSpeaker:
Chris Lindsell, PhD, Christina Barkauskas, MD and Anru Zhang, PhD
ARDS, pneumonia, and sepsis are common critical illnesses with high mortality.
The conditions are overlapping, and diagnosis, prognosis and prediction are all challenging. Decades of research has been done to try and unravel the heterogeneity and find treatments to improve outcomes for these patients, yet to little effect. Progress is
hampered in part by the high acuity and time-sensitive clinical context, the plethora of interventions required for organ support, limited understanding of the pathophysiology, incomplete assessment of molecular data, and incomplete documentation of clinical
course - among other things. To fill the knowledge gap and provide the foundation for successful interventions in these high mortality conditions, the APS consortium is generating the most comprehensive dataset ever to be available. This talk will discuss
the challenges and solutions in designing and implementing this ambitious prospective observational cohort study that will deeply phenotype 4000 patients with serial assessments throughout their clinical course. We will also discuss the principles being applied
to maximize the validity of analyses, and we will highlight opportunities for ancillary studies.