Associations of TBI, PTSD, and depression with dementia risk among female military veterans: Not just men
Abstract: Over the past decade, it has become increasingly recognized that military veterans are at higher risk than the general population for neuropsychiatric conditions such as traumatic brain injury (TBI), posttraumatic stress disorder (PTSD), and depression. More recent work has shown an ≈2-fold increased long-term risk of dementia among predominantly male military veterans with TBI, PTSD, or depression compared to veterans without any neuropsychiatric conditions. However, the association of neuropsychiatric conditions with dementia among female military veterans is an important gap in the literature. More women are joining the military, and there is increasing evidence of sex differences in dementia risk in the general population.
Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate the extraction of opioid relapses, and the timing of these occurrences, from veteran patients' electronic medical record. We then demonstrated the utility of our NLP tool via analysis of pre-/post-COVID-19 opioid relapse trends among veterans with OUD. For this demonstration, we analyzed data from 107,606 veterans OUD enrolled in Veterans Health Administration, comparing a pandemic-exposed cohort (n = 53,803; January 2019-March 2021) to a matched prepandemic cohort (n = 53,803; October 2017-December 2019). The recall of our NLP tool was 75% and our precision was 94%, demonstrating moderate sensitivity and excellent specificity. Using the NLP tool, we found that the odds of opioid relapse postpandemic onset were proportionally higher compared to prepandemic trends, despite patients having fewer mental health encounters from which to derive instances of relapse postpandemic onset. In this research application of the tool, and as hypothesized, we found that opioid relapse risk was elevated postpandemic. The application of NLP Methods: to identify and monitor relapse risk holds promise for future surveillance, risk prevention, and clinical outcome research.