Objectives
To estimate the prevalence of post-traumatic stress disorder (PTSD) in a large civilian population with traumatic brain injury (TBI), and to assess whether brain injury severity is correlated with PTSD symptoms.
DesignObservational, cross-sectional study.
Setting and participantsOutpatient clinic in a major UK trauma centre and secondary care hospital. Estimates of PTSD prevalence are based on 171 sampled individuals attending TBI clinic within an 18-month period. Analysis of the relationship between TBI severity and PTSD was performed on the subset of 127 patients for whom injury severity data were also available.
MethodsCivilian TBI clinic attendees completed validated self-report questionnaires assessing PTSD (PTSD Checklist Civilian Version (PCL-C)) and other psychiatric symptoms. From this, the prevalence of PTSD was estimated in our cohort. Postresuscitation Glasgow Coma Score and Marshall grade on CT brain scan were recorded as indicators of brain injury severity. A hierarchical regression explored whether TBI severity may predict PTSD scores.
ResultsA high prevalence of PTSD was estimated (21% with PCL-C score >50). Higher Marshall grading displayed a slight negative correlation with PTSD symptoms. This statistically significant relationship persisted after confounding factors such as depression and postconcussion symptoms were controlled for.
ConclusionsPTSD and TBI frequently coexist, share antecedents and overlap in their resultant symptoms. This complexity has given rise to conflicting hypotheses about relationships between the two. This research reveals that PTSD is common in civilians with TBI (adding to evidence drawn from military populations). The analysis indicated that more severe brain injury may exert a slight protective influence against the development of PTSD—potentially by disrupting implicit access to traumatic memories, or via overlapping neuropsychiatric symptoms that impede diagnosis. The association suggests that further research is warranted to explore the reuse of routine clinical and neuroimaging data—investigating its potential to predict risk of psychiatric morbidity.
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