David Maslove, MD, MS
Assistant Professor
Department of Medicine and Critical Care
Queens University

ABSTRACT:
The diseases treated in the Intensive Care Units (ICU) are syndromic in nature, largely defined by a number of vague or arbitrary criteria. As a result, there exists significant case mixing within ICU syndromes, whereby different syndrome subtypes – or endotypes – are all treated the same way. This limits the effectiveness of evidence-based practices evaluated in large clinical trials, and makes critical care particularly suitable to a precision approach. Further enabling this approach is the incredible abundance of data generated in the ICU, upon which distinctions between patients can be made. Making the most of these data requires that they be systematically collected, vetted, merged, and analyzed, ideally in a near real-time environment that respects the fast-paced nature of ICU practice. We will explore some key challenges to this approach, with a focus on specific examples involving physiologic, clinical, and genomic data generated from critically ill and injured patients.