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Scoring for Hemorrhage Severity in Traumatic Injury

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Biomarkers in Trauma, Injury and Critical Care

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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).

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Abbreviations

AI:

Artificial Intelligence

HISS:

Hemorrhage Intensive Severity and Survivability Score

ML:

Machine Learning

MODS:

Multiple Organ Dysfunction Syndrome

MOF:

Multiple Organ Failure

SOFA:

Sequential Organ Failure Assessment

START:

Simple Triage and Rapid Treatment

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Acknowledgments

Support provided by the Center for Bioelectronics, Biosensors, and Biochips (C3B®) and from ABTECH Scientific, Inc. Professor Guiseppi-Elie acknowledges support via a TEES Research Professorship. Professor Rashidi was supported by National Science Foundation CAREER award 1750192 and 1R01EB029699 from the National Institute of Biomedical Imaging and Bioengineering (NIH/NIBIB).

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Conflicts of Interest

A. G.-E. is founder and scientific director of ABTECH Scientific, Inc., manufacturer of microfabricated biochip devices.

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Authors and Affiliations

  1. J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA

    Benjamin Shickel

  2. Department of Surgery, University of Florida Health, Gainesville, FL, USA

    Jeremy Balch & Tyler J. Loftus

  3. Test Development, Roche Diagnostics, Indianapolis, IN, USA

    John R. Aggas

  4. Walter Reed National Military Medical Center, Bethesda, MD, USA

    Christian N. Kotanen

  5. J. Crayton Pruitt Family Department of Biomedical Engineering, Gainesville, FL, USA

    Parisa Rashidi

  6. Center for Bioelectronics, Biosensors and Biochips (C3B), Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, USA

    Anthony Guiseppi-Elie

Authors
  1. Benjamin Shickel
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  2. Jeremy Balch
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  3. John R. Aggas
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  4. Tyler J. Loftus
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  5. Christian N. Kotanen
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  6. Parisa Rashidi
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  7. Anthony Guiseppi-Elie
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Corresponding author

Correspondence to Anthony Guiseppi-Elie .

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Editors and Affiliations

  1. College of Medicine, King Saud bin Abdulaziz University of Health Sciences, Riyadh, Saudi Arabia

    Rajkumar Rajendram

  2. School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, UK

    Victor R. Preedy

  3. School of Life Sciences, University of Westminster, London, UK

    Vinood B. Patel

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Shickel, B. et al. (2023). Scoring for Hemorrhage Severity in Traumatic Injury. In: Rajendram, R., Preedy, V.R., Patel, V.B. (eds) Biomarkers in Trauma, Injury and Critical Care. Biomarkers in Disease: Methods, Discoveries and Applications. Springer, Cham. https://doi.org/10.1007/978-3-031-07395-3_58

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