Association of Plasma Aß42/Aß40 Ratio and Late-Onset Epilepsy: Results From the Atherosclerosis Risk in Communities Study.

BACKGROUND AND OBJECTIVES: The objective of this study was to determine the relationship between plasma ß-amyloid (Aß), specifically the ratio of 2 Aß peptides (the Aß42/Aß40 ratio, which correlates with increased accumulation of Aß in the CNS), and late-onset epilepsy (LOE). METHODS: We used Medicare fee-for-service claims codes from 1991 to 2018 to identify cases of LOE among 1,424 Black and White men and women enrolled in the Atherosclerosis Risk in Communities (ARIC) study cohort. The Aß42/Aß40 ratio was calculated from plasma samples collected from ARIC participants in 1993-1995 (age 50-71 years) and 2011-2013 (age 67-90 years). We used survival analysis accounting for the competing risk of death to determine the relationship between late-life plasma Aß42/Aß40, and its change from midlife to late life, and the subsequent development of epilepsy. We adjusted for demographics, the apolipoprotein e4 genotype, and comorbidities, including stroke, dementia, and head injury. A low plasma ratio of 2 Aß peptides, the Aß42/Aß40 ratio, correlates with low CSF Aß42/Aß40 and with increased accumulation of Aß in the CNS. RESULTS: Decrease in plasma Aß42/Aß40 ratio from midlife to late life, but not an isolated measurement of Aß42/Aß40, was associated with development of epilepsy in later life. For every 50% reduction in Aß42/Aß40, there was a 2-fold increase in risk of epilepsy (adjusted subhazard ratio 2.30, 95% CI 1.27-4.17). DISCUSSION: A reduction in plasma Aß42/Aß40 is associated with an increased risk of subsequent epilepsy. Our observations provide a further validation of the link between Aß, hyperexcitable states, and LOE.

Life Stressors During Pregnancy in Women With Epilepsy: Results From the Pregnancy Risk Assessment Monitoring System.

BACKGROUND AND OBJECTIVES: To compare specific life stressors and domestic abuse that pregnant women and others with epilepsy (WWE) experience compared with pregnant women and others without epilepsy (WWoE). METHODS: The Pregnancy Risk Assessment Monitoring System (PRAMS) is an annual weighted survey of randomly sampled postpartum women administered by the Centers for Disease Control and Prevention. We used data from the PRAMS from 2012 to 2020 in 13 states to assess the life stressors reported by WWE compared with WWoE. We adjusted the data for maternal age, race, ethnicity, marital status, education, and socioeconomic status (SES; using income, Women, Infants, and Children program [WIC], and Medicaid use). We also examined reported abuse in WWE compared with WWoE. RESULTS: This study included data from 64,951 postpartum women, representing 4,072,189 women through weighted sampling. Of these, 1,140 reported having a diagnosis of epilepsy in the 3 months before their pregnancies (representing 81,021 WWE). WWE experienced a higher number of stressors compared with WWoE. WWE were more likely to have experienced 9 of the 14 stressors asked in the PRAMS questionnaire: severe illness of a close family member, separation or divorce, homelessness, loss of a partner's job, cut in work hours or pay, arguing more than usual with their partner, serving jail time, substance abuse problem in a close contact, and death of a close contact. After adjusting for demographics (age, race, and SES), epilepsy was still associated with a higher number of stressors in pregnant women. Other factors associated with stressors were younger age, Indigenous or mixed race, non-Hispanic ethnicity, lower income, and WIC or Medicaid use. Those who were married were less likely to report stressors. WWE were also more likely to report abuse before or during their pregnancies. DISCUSSION: Although managing stress is important in both epilepsy and pregnancy, WWE experience more stressors than do WWoE. After adjusting for maternal age, race, and SES, this increase in stressors persisted. Women who were younger, with lower income, on WIC or Medicaid, or not married were also more likely to experience life stressors. Alarmingly, reported abuse was also higher in WWE compared with WWoE. Attention from clinicians and support services for WWE are needed to optimize good pregnancy outcomes.

A computational framework for transmission risk assessment of aerosolized particles in classrooms.

Infectious airborne diseases like the recent COVID-19 pandemic render confined spaces high-risk areas. However, in-person activities like teaching in classroom settings and government services are often expected to continue or restart quickly. It becomes important to evaluate the risk of airborne disease transmission while accounting for the physical presence of humans, furniture, and electronic equipment, as well as ventilation. Here, we present a computational framework and study based on detailed flow physics simulations that allow straightforward evaluation of various seating and operating scenarios to identify risk factors and assess the effectiveness of various mitigation strategies. These scenarios include seating arrangement changes, presence/absence of computer screens, ventilation rate changes, and presence/absence of mask-wearing. This approach democratizes risk assessment by automating a key bottleneck in simulation-based analysis-creating an adequately refined mesh around multiple complex geometries. Not surprisingly, we find that wearing masks (with at least 74% inward protection efficiency) significantly reduced transmission risk against unmasked and infected individuals. While the use of face masks is known to reduce the risk of transmission, we perform a systematic computational study of the transmission risk due to variations in room occupancy, seating layout and air change rates. In addition, our findings on the efficacy of face masks further support use of face masks. The availability of such an analysis approach will allow education administrators, government officials (courthouses, police stations), and hospital administrators to make informed decisions on seating arrangements and operating procedures. Supplementary Information: The online version contains supplementary material available at 10.1007/s00366-022-01773-9.

Interictal EEG and ECG for SUDEP Risk Assessment: A Retrospective Multicenter Cohort Study.

Objective: Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality. Although lots of effort has been made in identifying clinical risk factors for SUDEP in the literature, there are few validated methods to predict individual SUDEP risk. Prolonged postictal EEG suppression (PGES) is a potential SUDEP biomarker, but its occurrence is infrequent and requires epilepsy monitoring unit admission. We use machine learning methods to examine SUDEP risk using interictal EEG and ECG recordings from SUDEP cases and matched living epilepsy controls. Methods: This multicenter, retrospective, cohort study examined interictal EEG and ECG recordings from 30 SUDEP cases and 58 age-matched living epilepsy patient controls. We trained machine learning models with interictal EEG and ECG features to predict the retrospective SUDEP risk for each patient. We assessed cross-validated classification accuracy and the area under the receiver operating characteristic (AUC) curve. Results: The logistic regression (LR) classifier produced the overall best performance, outperforming the support vector machine (SVM), random forest (RF), and convolutional neural network (CNN). Among the 30 patients with SUDEP [14 females; mean age (SD), 31 (8.47) years] and 58 living epilepsy controls [26 females (43%); mean age (SD) 31 (8.5) years], the LR model achieved the median AUC of 0.77 [interquartile range (IQR), 0.73-0.80] in five-fold cross-validation using interictal alpha and low gamma power ratio of the EEG and heart rate variability (HRV) features extracted from the ECG. The LR model achieved the mean AUC of 0.79 in leave-one-center-out prediction. Conclusions: Our results support that machine learning-driven models may quantify SUDEP risk for epilepsy patients, future refinements in our model may help predict individualized SUDEP risk and help clinicians correlate predictive scores with the clinical data. Low-cost and noninvasive interictal biomarkers of SUDEP risk may help clinicians to identify high-risk patients and initiate preventive strategies.

Association of Head Injury With Late-Onset Epilepsy: Results From the Atherosclerosis Risk in Communities Cohort.

BACKGROUND AND OBJECTIVES: Late-onset epilepsy (LOE; i.e., epilepsy starting in later adulthood) affects a significant number of individuals. Head injury is also a risk factor for acquired epilepsy, but the degree to which prior head injury may contribute to LOE is less well understood. Our objective was to determine the association between head injury and subsequent development of LOE. METHODS: Included were 8,872 participants enrolled in the Atherosclerosis Risk in Communities (ARIC) study with continuous Centers for Medicare Services fee-for-service (FFS) coverage (55.1% women, 21.6% Black). We identified head injuries through 2018 from linked Medicare fee for service claims for inpatient/emergency department care, active surveillance of hospitalizations, and participant self-report. LOE cases through 2018 were identified from linked Medicare FFS claims. We used Cox proportional hazards models to evaluate associations of head injury with LOE, adjusting for demographic, cardiovascular, and lifestyle factors. RESULTS: The adjusted hazard ratio (HR) for developing LOE after a history of head injury was 1.88 (95% confidence interval [CI] 1.44-2.43). There was evidence for dose-response associations with greater risk for LOE with increasing number of prior head injuries (HR 1.37, 95% CI 1.01-1.88 for 1 prior head injury and HR 3.55, 95% CI 2.51-5.02 for 2+ prior head injuries, compared to no head injuries) and with more severe head injury (HR 2.53, 95% CI 1.83-3.49 for mild injury and HR 4.90, 95% CI 3.15-7.64 for moderate/severe injury, compared to no head injuries). Associations with LOE were significant for head injuries sustained at older age (age ≥67 years: HR 4.01, 95% CI 2.91-5.54), but not for head injuries sustained at younger age (age < 67 years: HR 0.98, 95% CI 0.68-1.41). DISCUSSION: Head injury was associated with increased risk of developing LOE, particularly when head injuries were sustained at an older age, and there was evidence for higher risk for LOE after a greater number of prior head injuries and after more severe head injuries. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that an increased risk of late-onset epilepsy is associated with head injury and that this risk increases further with multiple and more severe head injuries.

Dementia in late-onset epilepsy: The Atherosclerosis Risk in Communities study.

OBJECTIVE: To determine the risk of dementia after the development of late-onset epilepsy. METHODS: We used data from the Atherosclerosis Risk in Communities (ARIC) cohort study, which started in 1987 to 1989 with 15,792 mostly Black and White men and women from 4 US communities. We identified late-onset epilepsy (LOE; seizures starting at age 67 or later) from linked Medicare claims data. We used a Cox proportional hazards regression model to evaluate associations between LOE and dementia through 2017 as ascertained from neuropsychological testing, interviews, and hospital discharge surveillance, and we used multinomial logistic regression to assess the risk of dementia and mild cognitive impairment in the subset with full neuropsychological assessments available. We adjusted for demographics and vascular and Alzheimer disease risk factors. RESULTS: Of 9,033 ARIC participants with sufficient Medicare coverage data (4,980 [55.1%] female, 1993 [22.1%] Black), 671 met the definition of LOE. Two hundred seventy-nine (41.6%) participants with and 1,408 (16.8%) without LOE developed dementia (p < 0.001). After a diagnosis of LOE, the adjusted hazard ratio for developing subsequent dementia was 3.05 (95% confidence interval 2.65-3.51). The median time to dementia ascertainment after the onset of LOE was 3.66 years (quartile 1-3, 1.28-8.28 years). INTERPRETATION: The risk of incident dementia is substantially elevated in individuals with LOE. Further work is needed to explore causes for the increased risk of dementia in this growing population.