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Using NTDB Data to Examine Variables Predictive of Survival in Severely Injured Trauma Patients

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Abstract

In the United States, traumatic injuries are the leading cause of death among adults under the age of 45, and account for at least 69 billion dollars of lost income and 327 billion in medical care and expenses annually. This project examines whether trauma survival among severely injured trauma patients has improved between 2017-2022 and identifies variables most strongly associated with survival among trauma patients. Data were obtained from the National Trauma Data Bank (NTDB) data set, a national registry of demographic, injury, and outcome data on trauma patients cared for in U.S. trauma centers. Analyses included Random Forest, a variety of machine ensemble learning, as well as logistic regression.

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Description
Date
2025-12
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Research Projects
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Keywords
trauma, injury, random forest, machine learning, public health, biostatistics
Citation
Rothenberg, Rocky. "Using NTDB Data to Examine Variables Predictive of Survival in Severely Injured Trauma Patients." Master's thesis, Georgia State University, 2025. https://doi.org/10.57709/78q4-7z19
Embargo Lift Date
2027-12-01
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