Latent Neuropsychological Profiles to Discriminate Mild Traumatic Brain Injury and Posttraumatic Stress Disorder in Active-Duty Service Members.

Abstract

To determine whether cognitive and psychological symptom profiles differentiate clinical diagnostic classifications (eg, history of mild traumatic brain injury [mTBI] and posttraumatic stress disorder [PTSD]) in military personnel. US Active-Duty Service Members ( N = 209, 89% male) with a history of mTBI ( n = 56), current PTSD ( n = 23), combined mTBI + PTSD ( n = 70), or orthopedic injury controls ( n = 60) completed a neuropsychological battery assessing cognitive and psychological functioning. Latent profile analysis was performed to determine how neuropsychological outcomes of individuals clustered together. Diagnostic classifications (ie, mTBI, PTSD, mTBI + PTSD, and orthopedic injury controls) within each symptom profile were examined. A 5-profile model had the best fit. The profiles differentiated subgroups with high (34.0%) or normal (21.5%) cognitive and psychological functioning, cognitive symptoms (19.1%), psychological symptoms (15.3%), and combined cognitive and psychological symptoms (10.0%). The symptom profiles differentiated participants as would generally be expected. Participants with PTSD were mainly represented in the psychological symptom subgroup, while orthopedic injury controls were mainly represented in the high-functioning subgroup. Further, approximately 79% of participants with comorbid mTBI and PTSD were represented in a symptomatic group (∼24% = cognitive symptoms, ∼29% = psychological symptoms, and 26% = combined cognitive/psychological symptoms). Our results also showed that approximately 70% of military personnel with a history of mTBI were represented in the high- and normal-functioning groups. These results demonstrate both overlapping and heterogeneous symptom and performance profiles in military personnel with a history of mTBI, PTSD, and/or mTBI + PTSD. The overlapping profiles may underscore why these diagnoses are often difficult to diagnose and treat, but suggest that advanced statistical models may aid in identifying profiles representing symptom and cognitive performance impairments within patient groups and enable identification of more effective treatment targets.