Document Type

Conference Proceeding

Publication Date

5-1-2022

Publication Title

Biological Psychiatry

Abstract

Background: Posttraumatic stress symptoms (PTSS) are common following trauma exposure. Identification of individuals with PTSS at the time of emergency care is important to enable preventive interventions. In this study, we used baseline survey data from two large prospective cohort studies to identify the most influential predictors of PTSS at the time of presentation for emergency care and to develop a clinical decision support tool to identify individuals who develop substantial PTSS.

Methods: Self-identifying white and black American men and women (n=1,546) presenting to one of sixteen emergency departments (EDs) within 24 hours of motor vehicle collision (MVC) trauma were enrolled. Individuals with substantial PTSS (≥33, IES-R) six months after MVC were identified via follow-up questionnaire. Sociodemographic, pain, general health, event, and psychological/cognitive characteristics collected in the ED and used in prediction modeling. Ensemble learning methods and Monte Carlo cross-validation were used for feature selection and to determine prediction accuracy. External validation was performed on a hold-out sample (30% of total sample).

Results: 25% (n=394) of individuals reported PTSS six months following MVC. Regularized linear regression was the top performing ensemble learning method. The top thirty factors together showed good reliability in predicting PTSS in the external sample (AUC=0.79+/-0.0017). Top predictors included acute pain severity, expectations of recovery, socioeconomic status, self-reported “race/ethnicity”, and psychological symptoms.

Conclusions: These analyses add to a growing literature indicating that influential predictors of PTSS can be identified and risk for future PTSS estimated from characteristics easily available/assessable at the time of ED presentation following trauma.

Volume

91

Issue

9

First Page

S341

Last Page

S342

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