Abstract
Severity scores have long been used for the classification or stratification of patients for clinical care and in the evaluation of outcomes. Such scores find highest utility as a standardization instrument in the study of large cohorts of patients. The advent of pervasive tools and capabilities of Artificial Intelligence (AI) and Machine Learning (ML) increases the value of applying such scores to personalized bedside decisions regarding single patients, in which case the score has the data richness of a biomarker of disease. While not molecular biomarkers, such scores are often informed by molecular indicators of pathophysiology and find utility similar to that of traditional biomarkers. This chapter explores the use of severity scores such as the Injury Severity Score (ISS) and New Injury Severity Score (NISS), an internationally recognized scoring system which correlates with mortality, morbidity, and other measures of severity. We also highlight recently introduced scores that capture the rich pathophysiological data of the Emergency Department (ED) and the Intensive Care Unit (ICU).
Published Version
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