Identifying the Factors Affecting the Survival of Trauma Patients Using Logistic Regression Analysis

Project Abstract

Numerous predictors affect the clinical outcomes such as survival status, a binary outcome variable, of patients with physical trauma. Logistic regression is one of the widely used methods to analyze relationships between a set of predictors with a binary outcome variable. In this study, we built a logistic regression model for a binary outcome variable, Hospital Discharge Status (HDS). Predictors included in this analysis are arrival time, age, trauma level, injury severity score, arrival heart rate, arrival blood pressure, length of hospital stay, time from injury to arrival at the BC, patient transfer or direct admittance, mode of transfer, time from injury to the referral hospital, distance from injury to tertiary facility, and season. The goal of this retrospective observational study is to assess the association between the predictors and HDS and evaluate the odds of survival corresponding to the predictor.

Conference

Pi Mu Epsilon Contributed Session on Research by Undergraduates at the 2025 Joint Mathematics Meeting

January 8-11, 2025

https://jointmathematicsmeetings.org/meetings/national/jmm2025/2314_pme.html

Funding Type

Travel Grant

Academic College

Jesse D. Jones College of Science, Engineering and Technology

Area/Major/Minor

Mathematics/Applied Statistics

Degree

Bachelors of Science

Classification

Senior

Name

Manoj Pathak, PhD

Academic College

Jesse D. Jones College of Science, Engineering and Technology

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