Posttraumatic Epilepsy and Dementia Risk.

Importance: Although both head injury and epilepsy are associated with long-term dementia risk, posttraumatic epilepsy (PTE) has only been evaluated in association with short-term cognitive outcomes. Objective: To investigate associations of PTE with dementia risk. Design, Setting, and Participants: The Atherosclerosis Risk in Communities (ARIC) study initially enrolled participants from 1987 to 1989 and this prospective cohort study uses data through December 31, 2019, with a median follow-up of 25 years. Data were analyzed between March 14, 2023, and January 2, 2024. The study took place in 4 US communities in Minnesota, Maryland, North Carolina, and Mississippi. Of 15 792 ARIC study participants initially enrolled, 2061 were ineligible and 1173 were excluded for missing data, resulting in 12 558 included participants. Exposures: Head injury was defined by self-report and International Classification of Diseases (ICD) diagnostic codes. Seizure/epilepsy was defined using ICD codes. PTE was defined as a diagnosis of seizure/epilepsy occurring more than 7 days after head injury. Head injury, seizure/epilepsy, and PTE were analyzed as time-varying exposures. Main Outcomes and Measures: Dementia was defined using cognitive assessments, informant interviews, and ICD and death certificate codes. Adjusted Cox and Fine and Gray proportional hazards models were used to estimate dementia risk. Results: Participants had a mean (SD) age of 54.3 (5.8) years at baseline, 57.7% were female, 28.2% were of self-reported Black race, 14.4% were ultimately categorized as having head injury, 5.1% as having seizure/epilepsy, and 1.2% as having PTE. Over a median follow-up of 25 (25th to 75th percentile, 17-30) years, 19.9% developed dementia. In fully adjusted models, compared with no head injury and no seizure/epilepsy, PTE was associated with 4.56 (95% CI, 4.49-5.95) times the risk of dementia, while seizure/epilepsy was associated with 2.61 (95% CI, 2.21-3.07) times the risk and head injury with 1.63 (95% CI, 1.47-1.80) times the risk. The risk of dementia associated with PTE was significantly higher than the risk associated with head injury alone and with nontraumatic seizure/epilepsy alone. Results were slightly attenuated in models accounting for the competing risks of mortality and stroke, but patterns of association remained similar. In secondary analyses, the increased dementia risk associated with PTE occurring after first vs second head injury and after mild vs moderate/severe injury was similar. Conclusions and Relevance: In this community-based cohort, there was an increased risk of dementia associated with PTE that was significantly higher than the risk associated with head injury or seizure/epilepsy alone. These findings provide evidence that PTE is associated with long-term outcomes and supports both the prevention of head injuries via public health measures and further research into the underlying mechanisms and the risk factors for the development of PTE, so that efforts can also be focused on the prevention of PTE after a head injury.

Guidelines for Seizure Prophylaxis in Adults Hospitalized with Moderate-Severe Traumatic Brain Injury: A Clinical Practice Guideline for Health Care Professionals from the Neurocritical Care Society.

BACKGROUND: There is practice heterogeneity in the use, type, and duration of prophylactic antiseizure medications (ASMs) in patients with moderate-severe traumatic brain injury (TBI). METHODS: We conducted a systematic review and meta-analysis of articles assessing ASM prophylaxis in adults with moderate-severe TBI (acute radiographic findings and requiring hospitalization). The population, intervention, comparator, and outcome (PICO) questions were as follows: (1) Should ASM versus no ASM be used in patients with moderate-severe TBI and no history of clinical or electrographic seizures? (2) If an ASM is used, should levetiracetam (LEV) or phenytoin/fosphenytoin (PHT/fPHT) be preferentially used? (3) If an ASM is used, should a long versus short (> 7 vs. ≤ 7 days) duration of prophylaxis be used? The main outcomes were early seizure, late seizure, adverse events, mortality, and functional outcomes. We used Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology to generate recommendations. RESULTS: The initial literature search yielded 1998 articles, of which 33 formed the basis of the recommendations: PICO 1: We did not detect any significant positive or negative effect of ASM compared to no ASM on the outcomes of early seizure, late seizure, adverse events, or mortality. PICO 2: We did not detect any significant positive or negative effect of PHT/fPHT compared to LEV for early seizures or mortality, though point estimates suggest fewer late seizures and fewer adverse events with LEV. PICO 3: There were no significant differences in early or late seizures with longer versus shorter ASM use, though cognitive outcomes and adverse events appear worse with protracted use. CONCLUSIONS: Based on GRADE criteria, we suggest that ASM or no ASM may be used in patients hospitalized with moderate-severe TBI (weak recommendation, low quality of evidence). If used, we suggest LEV over PHT/fPHT (weak recommendation, very low quality of evidence) for a short duration (≤ 7 days, weak recommendation, low quality of evidence).

Association between structural brain MRI abnormalities and epilepsy in older adults.

OBJECTIVE: To determine the association between brain MRI abnormalities and incident epilepsy in older adults. METHODS: Men and women (ages 45-64 years) from the Atherosclerosis Risk in Communities study were followed up from 1987 to 2018 with brain MRI performed between 2011 and 2013. We identified cases of incident late-onset epilepsy (LOE) with onset of seizures occurring after the acquisition of brain MRI. We evaluated the relative pattern of cortical thickness, subcortical volume, and white matter integrity among participants with incident LOE after MRI in comparison with participants without seizures. We examined the association between MRI abnormalities and incident LOE using Cox proportional hazards regression. Models were adjusted for demographics, hypertension, diabetes, smoking, stroke, and dementia status. RESULTS: Among 1251 participants with brain MRI data, 27 (2.2%) developed LOE after MRI over a median of 6.4 years (25-75 percentile 5.8-6.9) of follow-up. Participants with incident LOE after MRI had higher levels of cortical thinning and white matter microstructural abnormalities before seizure onset compared to those without seizures. In longitudinal analyses, greater number of abnormalities was associated with incident LOE after controlling for demographic factors, risk factors for cardiovascular disease, stroke, and dementia (gray matter: hazard ratio [HR]: 2.3, 95% confidence interval [CI]: 1.0-4.9; white matter diffusivity: HR: 3.0, 95% CI: 1.2-7.3). INTERPRETATION: This study demonstrates considerable gray and white matter pathology among individuals with LOE, which is present prior to the onset of seizures and provides important insights into the role of neurodegeneration, both of gray and white matter, and the risk of LOE.

Sleep apnea, hypoxia, and late-onset epilepsy: the Atherosclerosis Risk in Communities study.

STUDY OBJECTIVE: Sleep apnea is associated with unexplained epilepsy in older adults in small studies. We sought to determine the relationship between sleep apnea and additional sleep characteristics and late-onset epilepsy, adjusting for comorbidities, using data from the large, prospective Atherosclerosis Risk in Communities (ARIC) Study cohort. METHODS: We used Medicare claims to identify cases of late-onset epilepsy (LOE) in ARIC participants. We used polysomnography data from 1309 ARIC participants who also participated in the Sleep Heart Health Study in 1995-1998, and demographic and comorbidity data from ARIC. Later risk of LOE was evaluated using survival analysis with a competing risk of death. We also used survival analysis in 2672 ARIC participants to identify the association between self-reported obstructive sleep apnea (2011-2013), and the risk of subsequent LOE. RESULTS: Late-midlife oxygen desaturation to less than 80% during sleep was associated with subsequent development of LOE, adjusted subhazard ratio 3.28 (1.18-9.08), but the apnea-hypopnea index was not related. Participant report of diagnosis of sleep apnea in 2011-2013 was also associated with subsequent LOE, adjusted subhazard ratio 2.59 (1.24-5.39). CONCLUSIONS: Sleep apnea and oxygen saturation nadir during sleep are associated with LOE, independently of hypertension and other comorbidities. These potentially modifiable risk factors could have large clinical implications for LOE.

Cognitive phenotypes in late-onset epilepsy: results from the atherosclerosis risk in communities study.

Introduction: Cognitive phenotyping is a widely used approach to characterize the heterogeneity of deficits in patients with a range of neurological disorders but has only recently been applied to patients with epilepsy. In this study, we identify cognitive phenotypes in older adults with late-onset epilepsy (LOE) and examine their demographic, clinical, and vascular profiles. Further, we examine whether specific phenotypes pose an increased risk for progressive cognitive decline. Methods: Participants were part of the Atherosclerosis Risk in Communities Study (ARIC), a prospective longitudinal community-based cohort study of 15,792 individuals initially enrolled in 1987-1989. LOE was identified from linked Centers for Medicare and Medicaid Services claims data. Ninety-one participants with LOE completed comprehensive testing either prior to or after seizure onset as part of a larger cohort in the ARIC Neurocognitive Study in either 2011-2013 or 2016-2017 (follow-up mean = 4.9 years). Cognitive phenotypes in individuals with LOE were derived by calculating test-level impairments for each participant (i.e., ≤1 SD below cognitively normal participants on measures of language, memory, and executive function/processing speed); and then assigning participants to phenotypes if they were impaired on at least two tests within a domain. The total number of impaired domains was used to determine the cognitive phenotypes (i.e., Minimal/No Impairment, Single Domain, or Multidomain). Results: At our baseline (Visit 5), 36.3% met criteria for Minimal/No Impairment, 35% for Single Domain Impairment (with executive functioning/ processing speed impaired in 53.6%), and 28.7% for Multidomain Impairment. The Minimal/No Impairment group had higher education and occupational complexity. There were no differences in clinical or vascular risk factors across phenotypes. Of those participants with longitudinal data (Visit 6; n = 24), 62.5% declined (i.e., progressed to a more impaired phenotype) and 37.5% remained stable. Those who remained stable were more highly educated compared to those that declined. Discussion: Our results demonstrate the presence of identifiable cognitive phenotypes in older adults with LOE. These results also highlight the high prevalence of cognitive impairments across domains, with deficits in executive function/processing speed the most common isolated impairment. We also demonstrate that higher education was associated with a Minimal/No Impairment phenotype and lower risk for cognitive decline over time.

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.

Managing Antiseizure Medications in Pregnancy: Is Earlier and More Frequent Monitoring Better?

Background and Objective: Medication management in pregnant women with epilepsy (PWWE) poses challenges, and understanding the effects of metabolic changes on antiseizure medications (ASMs) is important in planning care for PWWE. The possible teratogenic effects and risks of poorly controlled seizures have to be weighed. There are data in the literature on clinical management of ASMs including the effects of drug levels on seizures and factors that predict seizure frequency, but timing and frequency of monitoring and dose adjustment paradigms have not been well studied. Methods: This retrospective study was approved by the Institutional Review Board at Johns Hopkins University. We retrospectively identified adult PWWE evaluated during pregnancy at the Johns Hopkins Bayview Medical Center epilepsy clinic, between January 1, 2007, and January 1, 2021. We reviewed charts for information regarding demographics, medical and epilepsy history, medications, serum drug levels, and dosing paradigms. We assessed risk factors for breakthrough seizures with a focus on frequency and timing of laboratory testing. We calculated the dose-normalized concentration (DNC) for analysis with levetiracetam and lamotrigine, assessing changes in DNC over time by half trimesters, and analyzed DNC and effects on seizures in pregnancy. We also compared preemptive vs clinically based lamotrigine dose adjustments in managing epilepsy in pregnancy. Results: A total of 45 pregnancies in 39 patients were included in this study, 8 generalized, 28 focal epilepsy, and 3 unclassified. 31 PWWE (36 pregnancies) were on lamotrigine and/or levetiracetam, and 14 of these pregnancies experienced breakthrough seizures, 77% in the first trimester. Seizures led to the diagnosis of pregnancy in 5 patients. The DNC for levetiracetam decreased significantly compared with prepregnancy levels by the second half of the first trimester and demonstrated variable but frequently significant or near significant reduction throughout pregnancy. DNC for lamotrigine decreased significantly in the first half of the first trimester and remained significant throughout pregnancy. Age of mother at conception, week of first ASM serum level and number of levels obtained during pregnancy, and epilepsy type were not associated with breakthrough/increase in seizures. The history of drug resistance (p = 0.038) was associated with a higher odds of seizures. In those on lamotrigine, preemptive dose adjustments demonstrated similar results regarding seizure control when compared with clinical-based or laboratory-based dose management (p = 0.531). Discussion: This study demonstrates that frequency and timing of ASM level monitoring may not affect overall seizure outcomes during pregnancy in those on lamotrigine or levetiracetam. Furthermore, one can consider preemptive dose adjustments or a laboratory-based/clinical-based approach in managing lamotrigine as both seem safe and feasible. However, in those with drug-resistant epilepsy before pregnancy, earlier and closer monitoring is warranted given the risk of seizures early during pregnancy. Larger prospective studies are needed to confirm these results.

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.

Development of Expert-Level Classification of Seizures and Rhythmic and Periodic Patterns During EEG Interpretation.

BACKGROUND AND OBJECTIVES: Seizures (SZs) and other SZ-like patterns of brain activity can harm the brain and contribute to in-hospital death, particularly when prolonged. However, experts qualified to interpret EEG data are scarce. Prior attempts to automate this task have been limited by small or inadequately labeled samples and have not convincingly demonstrated generalizable expert-level performance. There exists a critical unmet need for an automated method to classify SZs and other SZ-like events with expert-level reliability. This study was conducted to develop and validate a computer algorithm that matches the reliability and accuracy of experts in identifying SZs and SZ-like events, known as "ictal-interictal-injury continuum" (IIIC) patterns on EEG, including SZs, lateralized and generalized periodic discharges (LPD, GPD), and lateralized and generalized rhythmic delta activity (LRDA, GRDA), and in differentiating these patterns from non-IIIC patterns. METHODS: We used 6,095 scalp EEGs from 2,711 patients with and without IIIC events to train a deep neural network, SPaRCNet, to perform IIIC event classification. Independent training and test data sets were generated from 50,697 EEG segments, independently annotated by 20 fellowship-trained neurophysiologists. We assessed whether SPaRCNet performs at or above the sensitivity, specificity, precision, and calibration of fellowship-trained neurophysiologists for identifying IIIC events. Statistical performance was assessed by the calibration index and by the percentage of experts whose operating points were below the model's receiver operating characteristic curves (ROCs) and precision recall curves (PRCs) for the 6 pattern classes. RESULTS: SPaRCNet matches or exceeds most experts in classifying IIIC events based on both calibration and discrimination metrics. For SZ, LPD, GPD, LRDA, GRDA, and "other" classes, SPaRCNet exceeds the following percentages of 20 experts-ROC: 45%, 20%, 50%, 75%, 55%, and 40%; PRC: 50%, 35%, 50%, 90%, 70%, and 45%; and calibration: 95%, 100%, 95%, 100%, 100%, and 80%, respectively. DISCUSSION: SPaRCNet is the first algorithm to match expert performance in detecting SZs and other SZ-like events in a representative sample of EEGs. With further development, SPaRCNet may thus be a valuable tool for an expedited review of EEGs. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that among patients with epilepsy or critical illness undergoing EEG monitoring, SPaRCNet can differentiate (IIIC) patterns from non-IIIC events and expert neurophysiologists.

EEG Correlates of Qualitative Hypermetabolic FDG-PET in Patients With Neurologic Disorders.

Background and Objectives: Case reports and case series have described fluorodeoxyglucose (FDG)-PET findings in critically ill patients with rhythmic or periodic EEG patterns, with one reporting that metabolic activity increases with increasing lateralized periodic discharge (LPD) frequency. However, larger studies examining the relationship between FDG-PET hypermetabolism and rhythmic or periodic EEG patterns are lacking. The goal of this study was to investigate the association of FDG-PET hypermetabolism with electroencephalographic features in patients with neurologic disorders. Methods: This was a single-center, retrospective study of adult patients admitted with acute neurologic symptoms who underwent FDG-PET imaging and EEG monitoring within 24 hours. Subjects were divided into 2 groups based on their FDG-PET metabolism pattern: hypermetabolic activity vs hypometabolic or normal metabolic activity. Chi-square tests and logistic regression were used to determine the relationship of FDG-PET metabolism and EEG findings. Results: Sixty patients met the inclusion criteria and underwent 63 FDG-PET studies and EEGs. Twenty-seven studies (43%) showed hypermetabolism while 36 studies (57%) showed either hypometabolism or no abnormalities on FDG-PET. Subjects with hypermetabolic FDG-PET were more likely to have electrographic seizures (44% vs 8%, p = 0.001) and LPDs with/without seizures (44% vs 14%, p = 0.007), but not other rhythmic or periodic EEG patterns (lateralized rhythmic delta activity, generalized periodic discharges, or generalized rhythmic delta activity). Subjects with hypermetabolism and LPDs were more likely to have concurrent electrographic seizures (58% vs 0%, p = 0.03), fast activity associated with the discharges (67% vs 0, p = 0.01), or spike morphology (67% vs 0, p = 0.03), compared with subjects with hypometabolic FDG-PET and LPDs. Discussion: Adults admitted with acute neurologic symptoms who had hypermetabolic FDG-PET were more likely to show electrographic seizures and LPDs, but not other rhythmic or periodic EEG patterns, compared with those with hypometabolic FDG-PET. Subjects with hypermetabolic FDG-PET and LPDs were more likely to have LPDs with concurrent electrographic seizures, LPDs with a spike morphology, and LPDs +F, compared with subjects with hypometabolic FDG-PET.

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.

Optogenetic stimulation reveals a latent tipping point in cortical networks during ictogenesis.

Brain-state transitions are readily apparent from changes in brain rhythms,1 but are difficult to predict, suggestive that the underlying cause is latent to passive recording methods. Among the most important transitions, clinically, are the starts of seizures. We here show that an 'active probing' approach may have several important benefits for epileptic management, including by helping predict these transitions. We used mice expressing the optogenetic actuator, channelrhodopsin, in pyramidal cells, allowing this population to be stimulated in isolation. Intermittent stimulation at frequencies as low as 0.033 Hz (period = 30 s) delayed the onset of seizure-like events in an acute brain slice model of ictogenesis, but the effect was lost if stimulation was delivered at even lower frequencies (1/min). Notably, active probing additionally provides advance indication of when seizure-like activity is imminent, revealed by monitoring the postsynaptic response to stimulation. The postsynaptic response, recorded extracellularly, showed an all-or-nothing change in both amplitude and duration, a few hundred seconds before seizure-like activity began-a sufficient length of time to provide a helpful warning of an impending seizure. The change in the postsynaptic response then persisted for the remainder of the recording, indicative of a state change from a pre-epileptic to a pro-epileptic network. This occurred in parallel with a large increase in the stimulation-triggered Ca2+ entry into pyramidal dendrites, and a step increase in the number of evoked postsynaptic action potentials, both consistent with a reduction in the threshold for dendritic action potentials. In 0 Mg2+ bathing media, the reduced threshold was not associated with changes in glutamatergic synaptic function, nor of GABAergic release from either parvalbumin or somatostatin interneurons, but simulations indicate that the step change in the optogenetic response can instead arise from incremental increases in intracellular [Cl-]. The change in the response to stimulation was replicated by artificially raising intracellular [Cl-], using the optogenetic chloride pump, halorhodopsin. By contrast, increases in extracellular [K+] cannot account for the firing patterns in the response to stimulation, although this, and other cellular changes, may contribute to ictal initiation in other circumstances. We describe how these various cellular changes form a synergistic network of positive feedback mechanisms, which may explain the precipitous nature of seizure onset. This model of seizure initiation draws together several major lines of epilepsy research as well as providing an important proof-of-principle regarding the utility of open-loop brain stimulation for clinical management of the condition.

Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs.

BACKGROUND AND OBJECTIVES: The validity of brain monitoring using electroencephalography (EEG), particularly to guide care in patients with acute or critical illness, requires that experts can reliably identify seizures and other potentially harmful rhythmic and periodic brain activity, collectively referred to as "ictal-interictal-injury continuum" (IIIC). Previous interrater reliability (IRR) studies are limited by small samples and selection bias. This study was conducted to assess the reliability of experts in identifying IIIC. METHODS: This prospective analysis included 30 experts with subspecialty clinical neurophysiology training from 18 institutions. Experts independently scored varying numbers of ten-second EEG segments as "seizure (SZ)," "lateralized periodic discharges (LPDs)," "generalized periodic discharges (GPDs)," "lateralized rhythmic delta activity (LRDA)," "generalized rhythmic delta activity (GRDA)," or "other." EEGs were performed for clinical indications at Massachusetts General Hospital between 2006 and 2020. Primary outcome measures were pairwise IRR (average percent agreement [PA] between pairs of experts) and majority IRR (average PA with group consensus) for each class and beyond chance agreement (κ). Secondary outcomes were calibration of expert scoring to group consensus, and latent trait analysis to investigate contributions of bias and noise to scoring variability. RESULTS: Among 2,711 EEGs, 49% were from women, and the median (IQR) age was 55 (41) years. In total, experts scored 50,697 EEG segments; the median [range] number scored by each expert was 6,287.5 [1,002, 45,267]. Overall pairwise IRR was moderate (PA 52%, κ 42%), and majority IRR was substantial (PA 65%, κ 61%). Noise-bias analysis demonstrated that a single underlying receiver operating curve can account for most variation in experts' false-positive vs true-positive characteristics (median [range] of variance explained ([Formula: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Formula: see text]: 75 [59, 89]%). Thus, variation between experts is mostly attributable not to differences in expertise but rather to variation in decision thresholds. DISCUSSION: Our results provide precise estimates of expert reliability from a large and diverse sample and a parsimonious theory to explain the origin of disagreements between experts. The results also establish a standard for how well an automated IIIC classifier must perform to match experts. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that an independent expert review reliably identifies ictal-interictal injury continuum patterns on EEG compared with expert consensus.

Effects of membrane and flexural stiffnesses on aortic valve dynamics: identifying the mechanics of leaflet flutter in thinner biological tissues.

Valvular pathologies that induce deterioration in the aortic valve are a common cause of heart disease among aging populations. Although there are numerous available technologies to treat valvular conditions and replicate normal aortic function by replacing the diseased valve with a bioprosthetic implant, many of these devices face challenges in terms of long-term durability. One such phenomenon that may exacerbate valve deterioration and induce undesirable hemodynamic effects in the aorta is leaflet flutter, which is characterized by oscillatory motion in the biological tissues. While this behavior has been observed for thinner bioprosthetic valves, the specific underlying mechanics that lead to leaflet flutter have not previously been identified. This work proposes a computational approach to isolate the fundamental mechanics that induce leaflet flutter in thinner biological tissues during the cardiac cycle. The simulations in this work identify reduced flexural stiffness as the primary factor that contributes to increased leaflet flutter in thinner biological tissues, while decreased membrane stiffness and mass of the thinner tissues do not directly induce flutter in these valves. The results of this study provide an improved understanding of the mechanical tissue properties that contribute to flutter and offer significant insights into possible developments in the design of bioprosthetic tissues to account for and reduce the incidence of flutter.

A pilot investigation of the tricuspid valve annulus in newborns with hypoplastic left heart syndrome.

Objective: Hypoplastic left heart syndrome (HLHS) is a congenital disease characterized by an underdevelopment of the anatomical components inside the left heart. Approximately 30% of HLHS newborns will develop tricuspid regurgitation (TR), and it is currently unknown how the valve annulus mechanics and geometry are associated with regurgitation. Thus, we present an engineering mechanics-based analysis approach to quantify the mechanics and geometry of the HLHS-afflicted tricuspid valve (TV), using 4-dimensional echocardiograms. Methods: Infants born with hypoplastic left heart syndrome (n=8) and healthy newborns (n=4) had their tricuspid valves imaged, and the data was imported to the 3D Slicer. The annular curves were defined at five points in the cardiac cycle. The geometry and deformation (strain) of the TV annulus were calculated to elucidate the mechanics of this critical structure, and compare them between HLHS and normal neonates. Results: For the annular geometry, HLHS-afflicted newborns had significantly larger annular circumferences (20-30%) and anterior-posterior diameters (35-45%) than the healthy patients. From a biomechanics perspective, the HLHS patients had significantly smaller strains in the anterior segments (-0.1±2.6%) during end diastolic and end isovolumetric relaxation (1.7±3.0%) compared to the healthy counterparts (-13.3±2.9% and 6.8±0.9%, respectively). Conclusions: The image-based analysis in this study may provide novel insights into the geometric and mechanistic differences in the TV annulus between healthy and HLHS newborns. Future longitudinal studies of the biomechanics of TV annulus and other subvalvular structures may inform our understanding of the initiation and development of TR and the design of optimal repairs in this challenging population.

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.

An in-silico benchmark for the tricuspid heart valve - Geometry, finite element mesh, Abaqus simulation, and result data set.

This article provides Abaqus input files and user subroutines for performing finite element simulations of the tricuspid heart valve with an idealized geometry. Additional post-processing steps to obtain a ParaView visualization file (*.vtk) of the deformed geometry are also provided to allow the readers to use the included ParaView state file (*.pvsm) for customizable visualization and evaluation of the simulation results. We expect this first-of-its-kind in-silico benchmark dataset will facilitate user-friendly simulations considering material nonlinearity, leaflet-to-leaflet contact, and large deformations. Additionally, the information included herein can be used to rapidly evaluate other novel in-silico approaches developed for simulating cardiac valve function. The benchmark can be expanded to consider more complex features of the tricuspid valve function, such as the dynamic annulus motion or the time-varying transvalvular pressure. Interested readers are referred to the companion article (Johnson et al., 2021) for an example application of this in-silico tool for isogeometric analysis of tricuspid valves.