Role of Deployment History on the Association Between Epilepsy and Traumatic Brain Injury in Post-9/11 Era US Veterans.

BACKGROUND AND OBJECTIVES: Traumatic brain injury (TBI) is a well-established epilepsy risk factor and is common among service members. Deployment-related TBI, where combat/blast may be more common, may have different outcomes than nondeployment-related TBI. This work examined associations of all TBI exposures (not just combat), and epilepsy, while adjusting for comorbidities associated with epilepsy, among veterans by deployment status. METHODS: The cohort included post-9/11 veterans with ≥2 years of care in both Veterans Health Administration and Defense Health Agency systems. We identified epilepsy using ICD-9/10-CM codes, antiseizure medication, and service-connected disability for epilepsy. We conducted a logistic regression model with interaction terms for conditions by deployment history that adjusted for demographics and military characteristics. RESULTS: The cohort (n = 938,890) included post-9/11 veterans of whom 27,436 (2.92%) had epilepsy. Most veterans had a history of deployment (70.64%), referred to as "deployed." Epilepsy was more common among veterans who were never deployed ("nondeployed") (3.85% vs 2.54%). Deployed veterans were more likely to have had TBI, compared with the nondeployed veterans (33.94% vs 14.24%), but nondeployed veterans with moderate/severe TBI had higher odds of epilepsy compared with deployed veterans (adjusted odds ratio [aOR] 2.92, 95% CI 2.68-3.17 vs aOR 2.01, 95% CI 1.91-2.11). Penetrating TBI had higher odds of epilepsy among the deployed veterans (aOR 5.33, 95% CI 4.89-5.81), whereas the odds of epilepsy for mild TBI did not significantly differ by deployment status. Although most neurologic conditions were more prevalent among the nondeployed veterans, they were often associated with higher odds of epilepsy in the deployed veterans. DISCUSSION: Deployment history had a significant differential impact on epilepsy predictors. As expected, penetrating TBI had a greater epilepsy impact among deployed veterans perhaps due to combat/blast. Some epilepsy predictors (moderate/severe TBI, multiple sclerosis, and Parkinson disease) had a stronger association in the nondeployed veterans suggesting a potential healthy warrior effect in which such conditions preclude deployment. Other neurologic conditions (e.g., brain tumor, Alzheimer disease/frontotemporal dementia) had a greater epilepsy impact in the deployed veterans. This may be attributable to deployment-related exposures (combat injury, occupational exposures). A better understanding of deployment effects is critical to provide targeted epilepsy prevention in veterans and military service members.

Changes in opioid prescribing in veterans with headache during the COVID-19 pandemic: A regression discontinuity in time analysis.

OBJECTIVE: To determine changes in opioid prescribing among veterans with headaches during the coronavirus disease of 2019 (COVID-19) pandemic by comparing the stay-at-home phase (March 15 to May 30, 2020) and the reopening phase (May 31 to December 31, 2020). BACKGROUND: Opioid prescribing for chronic pain has declined substantially since 2016; however, changes in opioid prescribing during the COVID-19 pandemic among veterans with headaches remain unknown. METHODS: This retrospective cohort study utilized regression discontinuity in time and difference-in-differences design to analyze veterans aged ≥18 years with a previous diagnosis of headache disorders and an outpatient visit to the Veterans Health Administration (VHA) during the study period. We measured the weekly number of opioid prescriptions, the number of days supplied, the daily dose in morphine milligram equivalents (MMEs), and the number of prescriptions with ≥50 morphine equivalent daily doses (MEDD). RESULTS: A total of 81,376 veterans were analyzed with 589,950 opioid prescriptions. The mean (SD) age was 51.6 (13.5) years, 57,242 (70.3%) were male, and 53,464 (65.7%) were White. During the pre-pandemic period, 323.6 opioid prescriptions (interquartile range 292.1-325.8) were dispensed weekly, with an median (IQR) of 24.1 (24.0-24.4) days supplied and 31.8 (31.2-32.5) MMEs. Transition to stay-at-home was associated with a 7.7% decrease in the number of prescriptions (incidence rate ratio [IRR] 1.077, 95% confidence interval [CI] 0.866-0.984) and a 9.8% increase in days supplied (IRR 1.098, 95% CI 1.078-1.119). Similar trends were observed during the reopening period. Subgroup analysis among veterans on long-term opioid therapy also revealed 1.7% and 1.4% increases in days supplied during the stay-at-home (IRR 1.017, 95% CI 1.009-1.025) and reopening phase (IRR 1.014, 95% CI 1.007-1.021); however, changes in the total number of prescriptions, MME/day, or the number of prescriptions >50 MEDD were insignificant. CONCLUSION: Prescription opioid access was maintained for veterans within VHA during the pandemic. The de-escalation of opioid prescribing observed prior to the pandemic was not seen in our study.

Prevalence of and characteristics associated with in-hospital mortality in a Ugandan neurology ward.

BACKGROUND: While the burden of neurologic illness in developing countries is increasing, less is known about mortality among patients admitted to sub-Saharan African hospitals with neurologic disease. We sought to characterize the rate and patient-level predictors of in-hospital mortality in a Ugandan Neurology ward.cc. METHODS: Data was prospectively collected on 335 patients admitted to the Neurology ward of Mulago Hospital, Kampala, Uganda. Kaplan-Meier survival curves and multivariate COX proportional hazard modeling were used to assess survival. RESULTS: Within our sample (n = 307), 35.8% received no diagnosis at time of hospital admission. Stroke (27.3%), head trauma (19.6%), and malaria (16.0%) were the most common diagnoses. Among the 56 (18.5%) patients who died during the index hospitalization, the most common diagnosis at admission and at death was stroke. Adjusted regression analysis showed that patients without a diagnosis at time of death (HR = 7.01 [2.42-20.35], p < .001) and those with diagnoses of infections (HR = 5.21 [2.16-12.58], p = <.001), stroke (HR = 2.69 [1.20-6.04], p = .017), or head trauma (HR = 3.39, [1.27-9.07], p = 0.15) had worse survival. CONCLUSIONS: In-hospital mortality affected nearly 20% of the cohort, with worse survival among those without a diagnosis and with infections, stroke, head trauma. Future work should identify reasons for increased mortality among these high-risk groups and implement targeted interventions.

Measuring coordination of epilepsy care: A mixed methods evaluation of social network analysis versus relational coordination.

OBJECTIVES: Coordination of multidisciplinary care is critical to address the complex needs of people with neurological disorders; however, quality improvement and research tools to measure coordination of neurological care are not well-developed. This study explored and compared the value of social network analysis (SNA) and relational coordination (RC) in measuring coordination of care in a neurology setting. The Department of Veterans Affairs Healthcare System (VA) established an Epilepsy Centers of Excellence (ECOE) hub and spoke model of care, which provides a setting to measure coordination of care across networks of providers. METHODS: In a parallel mixed methods approach, we compared coordination of care of VA providers who formally engage the ECOE system to VA providers outside the ECOE system using SNA and RC. Coordination of care scores were compiled from provider teams across 66 VA facilities, and key informant interviews of 80 epilepsy care team members were conducted concurrently to describe the quality of epilepsy care coordinating in the VA healthcare system. RESULTS: On average, members of healthcare teams affiliated with the ECOE program rated quality of communication and respect higher than non-ECOE physicians. Connectivity between neurologist and primary care providers as well as between neurologists and mental health providers were higher within ECOE hub facilities compared to spoke referring facilities. Key informant interviews reported the important role of formal and informal programming, social support and social capital, and social influence on epilepsy care networks. CONCLUSION: For quality improvement and research purposes, SNA and RC can be used to measure coordination of neurological care; RC provides a detailed assessment of the quality of communication within and across healthcare teams but is difficult to administer and analyze; SNA provides large scale coordination of care maps and metrics to compare across large healthcare systems. The two measures provide complimentary coordination of care data at a local as well as population level. Interviews describe the mechanisms of developing and sustaining health professional networks that are not captured in either SNA or RC measures.

Antiepileptic drugs and suicide-related behavior: Is it the drug or comorbidity?

BACKGROUND: We sought to compare trends of suicide-related behavior (SRB) before and after initiation of antiepileptic drug (AED) therapy among AED users (with and without epilepsy) to that of individuals without AED use controlling for sociodemographic characteristics and mental health comorbidity. METHODS: We used national Veterans Health Administration (VHA) data for post-9/11 veterans who received VHA care (2013-2014) without prior AED use. We conducted generalized estimation equation (GEE) analyses, stratified by epilepsy status and type of AED received, to assess the trend of SRB prevalence the year prior to and after the index date (date of first AED prescription/date of first health care encounter for non-AED users) controlling for sociodemographic factors and mental health comorbidity. RESULTS: The GEE analysis showed significant curvilinear trends of SRB prevalence over the 24-month study period among the AED users, indicating that the probability of SRB diagnoses increased over time with a peak before the index month and decreased thereafter. Similar patterns were observed among non-AED users, but significantly lower odds for SRB. Among AED users, there were no significant differences by epilepsy status; however, higher SRB prevalence and differential SRB trajectory measures were observed among those who received AEDs with mood-stabilizing action. CONCLUSIONS: The peak of SRB prior to and rapid reduction in SRB after initiation of AED, and the finding that individuals eventually prescribed a mood-stabilizing AED (vs other AED or levetiracetam) had higher odds of SRB, suggests a strong possibility that the relationship of AED and SRB is one of residual confounding.

Presurgical depression and anxiety are not associated with worse epilepsy surgery outcome five years postoperatively.

PURPOSE: Anxiety and depression have been associated with poor seizure control after epilepsy surgery. This study explored the effect of presurgical anxiety or depression on two- and five-year seizure control outcomes. METHODS: Adult subjects were enrolled between 1996 and 2001 in a multicenter prospective study to evaluate outcomes of resective epilepsy surgery. A Poisson regression was used to analyze the association of depression and anxiety with surgical outcome, while adjusting for gender, age, ethnicity, number of years with seizures, and presence of mesial temporal sclerosis. RESULTS: The relative risk (RR) of presurgical depression on two-year seizure-free outcome in this cohort is 1.12 (95% confidence interval (CI), 0.84-1.49) and 1.06 (CI, 0.73-1.55) on five-year seizure free outcome. The RR of presurgical anxiety on two-year seizure outcome is 0.73 (CI, 0.50-1.07) and 0.70 (CI, 0.43-1.17) on five-year seizure outcome. When including Engel classes I and II, the RRs of presurgical depression, anxiety, or both two years after surgery were 0.96 (p=0.59), 0.73 (p<0.05), and 0.97 (p=0.70), respectively, and they were 0.97 (p=0.82), 0.84 (p=0.32), and 0.89 (p=0.15), respectively, five years after surgery. Only presurgical anxiety was associated with worse epilepsy surgery outcome two year after surgery but not at five years postsurgery. Depression was not a risk factor for poor epilepsy surgical outcome in the long term. CONCLUSION: These findings from a prospective study that utilized a standardized protocol for psychiatric and seizure outcome assessment suggest that presurgical mood disorders have no substantial impact on postsurgical seizure outcome for up to five years after surgery.

Psychiatric and behavioral comorbidities in epilepsy: A critical reappraisal.

Psychiatric and behavioral disorders are important aspects of epilepsy and have received increasing attention in the last several years. The literature upon which most of the field relies contains some biases that must be carefully examined and resolved in future studies. First, in the pediatric epilepsy literature, many reports find that children with epilepsy have high levels of behavioral and psychiatric disorders when compared to appropriate controls. Most of these studies rely on parent-proxy completed instruments to assess these behavioral endpoints. Parents' reports are not objective but reflect parents' reactions and emotions. Increasing evidence suggests inherent biases in proxy reports and highlights the need to assess children directly. Second, periictal phenomena may be mischaracterized as underlying mood disorders. Third, many studies report elevated levels of psychiatric morbidity before and after the diagnosis of epilepsy, suggesting an inherent relation between the two types of disorders. Psychogenic nonepileptic seizures, while widely recognized as posing a diagnostic dilemma in the clinic, may account for some of these research findings. Diagnostic errors between epilepsy and psychogenic nonepileptic seizures need careful consideration when evaluating studies demonstrating associations between psychiatric disorders and epilepsy or poorer seizure control in association with psychiatric disorders in people who have epilepsy. Mental health concerns are important for everyone. An accurate, undistorted understanding of the relation between mental health disorders and epilepsy is essential to ensure appropriate therapy and to avoid unnecessary and potentially harmful treatments and common misconceptions.

Communicating diagnostic certainty of psychogenic nonepileptic seizures - a national study of provider documentation.

Management of psychogenic nonepileptic seizures (PNES) requires collaboration among and between health care professionals. Although criteria are established for diagnosis of PNES, miscommunication between neurologists, primary care providers, and mental health professionals may occur if the clinical impression is not clearly articulated. We extracted progress notes from the Department of Veterans Affairs (VA) electronic health record (EHR) nationally to study veterans who were evaluated for PNES. Of the 750 patients being worked up for PNES, the majority of patients did not meet criteria for PNES (64.6%). Of those who were thought to suffer from PNES, 147 (19.6%) met International League Against Epilepsy (ILAE) criteria for documented PNES, 14 (1.9%) for clinically established PNES, and 104 (13.9%) for probable or possible PNES. Neurologists tended to use ambiguous language, such as "thought to be" or "suggestive of" to describe their impressions of patients overall, even those with definitive PNES. Ambiguous language may lead to miscommunication across providers and inappropriate health care.