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Latent Neuropsychological Profiles to Discriminate Mild Traumatic Brain Injury and Posttraumatic Stress Disorder in
Carrie Esopenko1, Nicola L de Souza, Yuane Jia
1Departments of Rehabilitation and Movement Sciences (Dr Esopenko) and Interdisciplinary Studies (Drs Jia and Parrott), School of Health Professions, Rutgers Biomedical and Health Sciences; School of Graduate Studies, Biomedical Sciences, Rutgers Biomedical and Health Sciences, Newark, New Jersey (Ms de Souza); Department of Psychology & Neuroscience Center, Brigham Young University, Provo, Utah (Dr Merkley); Department of Neurology, TBI and Concussion Center, University of Utah School of Medicine, Salt Lake City (Drs Merkley, Dennis, Wilde, and Tate and Ms Velez); George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah (Drs Dennis, Wilde, and Tate); Department of Psychology, Pennsylvania State University, University Park, and Social Life and Engineering Sciences Imaging Center, University Park, Pennsylvania (Dr Hillary); San Antonio VA Polytrauma Rehabilitation Center, San Antonio, and Departments of Rehabilitation Medicine and Psychiatry, UT Health San Antonio, San Antonio, Texas (Dr Cooper); General Dynamics Information Technology (GDIT) contractor for the Traumatic Brain Injury Center of Excellence (TBICoE), Neurology Service, Department of Medicine, Brooke Army Medical Center, Joint Base San Antonio, Fort Sam Houston, Texas (Dr Kennedy); Wright Patterson Air Force Base/Wright State University, Psychiatry Residency Program, Dayton, Ohio (Dr Lewis); Alaska Radiology Associates, Anchorage (Dr York); Michael E. DeBakey VA Medical Center, Houston, and The Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas (Dr Menefee); Department of Neurology, H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, and Department of Pediatrics, Baylor College of Medicine, Houston, Texas (Dr McCauley); and Brain Injury Rehabilitation Service, Department of Rehabilitation Medicine, Brooke Army Medical Center, Joint Base San Antonio, Fort Sam Houston, Texas (Dr Bowles).
Objective:
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.
Methods:
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.
Results:
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.
Conclusions:
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.
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