Using Pattern Analysis Matching to Differentiate TBI and PTSD in a Military Sample

Distinguishing between traumatic brain injury (TBI) residuals and the effects of posttraumatic stress disorder (PTSD) during neuropsychological evaluation can be difficult because of significant overlap of symptom presentation. Using a standardized battery of tests, an artificial neural network was...

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Bibliographic Details
Published in:Applied neuropsychology. Adult 2014-01, Vol.21 (1), p.60-68
Main Authors: Meyers, John E., Miller, Ronald M., Tuita, Alexa R. R.
Format: Article
Language:English
Subjects:
Adult
Adult and adolescent clinical studies
Algorithms
Analysis of Variance
Anxiety disorders. Neuroses
artificial neural network
Biological and medical sciences
Brain Injuries - diagnosis
Brain Injuries - psychology
Female
Functional Laterality
Humans
Injuries of the nervous system and the skull. Diseases due to physical agents
Male
Medical sciences
Military Personnel
Neuropsychological Tests
Organic mental disorders. Neuropsychology
pattern analysis
Post-traumatic stress disorder
Psychiatric Status Rating Scales
Psychology. Psychoanalysis. Psychiatry
Psychopathology. Psychiatry
PTSD
Stress Disorders, Post-Traumatic - diagnosis
Stress Disorders, Post-Traumatic - psychology
TBI
Traumas. Diseases due to physical agents
Young Adult
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Summary:Distinguishing between traumatic brain injury (TBI) residuals and the effects of posttraumatic stress disorder (PTSD) during neuropsychological evaluation can be difficult because of significant overlap of symptom presentation. Using a standardized battery of tests, an artificial neural network was used to create an algorithm to perform pattern analysis matching (PAM) functions that can be used to assist with diagnosis. PAM analyzes a patient's neuropsychological data and provides a best fit classification, according to one of four groups: TBI, PTSD, malingering/invalid data, or "other" (depressed/anxious/postconcussion syndrome/normal). The original PAM was modeled on civilian data; the current study was undertaken using a database of 100 active-duty army service personnel who were referred for neuropsychological assessment in a military TBI clinic. The PAM classifications showed 90% overall accuracy when compared with clinicians' diagnoses. The PAM function is able to classify detailed neuropsychological profiles from a military population with a high degree of accuracy and is able to distinguish between TBI, PTSD, malingering/invalid data, or "other." PAM is a useful tool to help with clinical decision-making.
ISSN:2327-9095
2327-9109
DOI:10.1080/09084282.2012.737881