Risk Factors and Temporal Patterns of Poststroke Epilepsy across Stroke Subtypes: Insights from a Nationwide Cohort Study in Korea.

INTRODUCTION: We aimed to investigate the risk factors associated with poststroke epilepsy (PSE) among patients with different subtypes of stroke, focusing on age-related risk and time-varying effects of stroke subtypes on PSE development. METHODS: A retrospective, nationwide, population-based cohort study was conducted using Korean National Health Insurance Service-National Sample Cohort data. Patients hospitalized with newly diagnosed stroke from 2005 to 2015 were included and followed up for up to 10 years. The primary outcome was the development of PSE, defined as having a diagnostic code and a prescription for anti-seizure medication. Multivariable Cox proportional hazard models were used to estimate PSE hazard ratios (HRs), and time-varying effects were also assessed. RESULTS: A total of 8,305 patients with ischemic stroke, 1,563 with intracerebral hemorrhage (ICH), and 931 with subarachnoid hemorrhage (SAH) were included. During 10 years of follow-up, 4.6% of patients developed PSE. Among patients with ischemic stroke, significant risk factors for PSE were younger age (HR = 1.47), living in rural areas (HR = 1.35), admission through the emergency room (HR = 1.33), and longer duration of hospital stay (HR = 1.45). Time-varying analysis revealed elevated HRs for ICH and SAH, particularly in the first 2 years following the stroke. The age-specific HRs also showed an increased risk for those under the age of 65, with a noticeable decrease in risk beyond that age. CONCLUSION: The risk of developing PSE varies according to stroke subtype, age, and other demographic factors. These findings underscore the importance of tailored poststroke monitoring and management strategies to mitigate the risk of PSE.

Changes in heart rate variability over time from symptom onset of transient global amnesia.

Transient global amnesia (TGA) often involves precipitating events associated with changes in autonomic nervous system (ANS), and heart rate variability (HRV) reflects the ANS state. This study aimed to investigate HRV changes after TGA. A retrospective analysis of HRV included patients diagnosed with TGA between January 2015 and May 2020. The time and frequency domains of HRV were compared among three groups: early (< 1 week after TGA, n = 19), late (1-4 weeks after TGA, n = 38), and healthy control (HC, n = 19). The Pearson's correlation between time and time-domain HRV was also examined. The standard deviation of NN intervals (SDNN) (early, 47.2; late, 35.5; HC, 41.5; p = 0.033) and root mean square of successive RR interval differences (RMSSD) (early, 38.5; late, 21.3; HC, 31.0; p = 0.006) differed significantly among the three groups. Post-hoc analysis showed statistically significant differences only in the early and late groups in both SDNN (p = 0.032) and RMSSD (p = 0.006) values. However, the frequency domain with total power, low-frequency and high-frequency powers, and low-frequency/high-frequency ratio did not differ. SDNN (Pearson correlation coefficient =- 0.396, p = 0.002) and RMSSD (Pearson correlation coefficient =- 0.406, p = 0.002) were negatively correlated with time after TGA. Changes in HRV occurred over time after the onset of TGA, with the pattern showing an increase in the first week and then a decrease within 4 weeks.

Shared comorbidity of depression, migraine, insomnia, and fibromyalgia in a population-based sample.

BACKGROUND: Depression, migraine, insomnia, and fibromyalgia are reportedly comorbidities. Nevertheless, no study has evaluated the comorbidity of all four of these disorders. This study aimed to investigate the comorbidity of these four disorders. METHODS: Cross-sectional analyses were performed using data of the Circannual Change in Headache and Sleep study, an online nationwide population-based survey. Validated questionnaires were used to diagnose the disorders and measure quality of life. The change of clinical characteristics by addition of any comorbidity was analyzed using the Jonckheere-Terpstra trend test. RESULTS: The prevalence rates of depression, migraine, insomnia, and fibromyalgia were 7.2 %, 5.6 %, 13.3 %, and 5.8 %, respectively. Among the 3030 included participants, 494 (16.3 %), 164 (5.4 %), 40 (1.3 %), and 6 (0.2 %) had one, two, three, and four of these conditions, respectively. The number of headache days per 30 days (Jonckheere-Terpstra trend test, p = 0.011) and migraine-related disability (migraine disability assessment score, p = 0.021) increased with an increase in the number of comorbidities but not with the intensity of headache (visual analog scale, p = 0.225) among participants with migraine. The severity of insomnia (Insomnia Severity Index, p < 0.001) and fibromyalgia (fibromyalgia severity score, p = 0.002) increased with additional comorbidities; however, depression (Patient Health Questionnaire-9, p = 0.384) did not show such an increase. LIMITATIONS: The diagnoses of conditions were based on self-reported questionnaires. CONCLUSIONS: The findings confirmed significant comorbidity between depression, migraine, insomnia, and fibromyalgia. Health professionals should be aware of the probable comorbidity of depression, migraine, insomnia, and fibromyalgia when caring for individuals with any of these four disorders.

Long-term outcome of treatment-naïve patients with mesial temporal lobe epilepsy with hippocampal sclerosis: A retrospective study in a single center.

PURPOSE: This study aimed to describe long-term treatment outcomes of treatment-naïve patients with mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS). METHODS: A retrospective review was conducted of treatment-naïve patients with MTLE-HS who visited the Yonsei Epilepsy Clinic from April 2000 to April 2022 and were followed up for at least 2 years. Seizure freedom (SF) was defined as no seizures or auras only for >1 year, and complete SF was defined as no seizures including auras for >1 year. RESULTS: Eighty-four treatment-naïve patients with MTLE-HS with a median follow-up of 122 months were included. Except for one patient who underwent early surgical treatment, of the remaining 83 patients, 31 (37.3 %) achieved SF and remained in remission, 38 (45.8 %) had fluctuations in seizure control, and 14 (16.9 %) never achieved SF. Additionally, 18 (21.7 %) patients achieved complete SF and remained in remission, 42 (50.6 %) showed fluctuations, and 23 (27.7 %) never achieved complete SF. Fifty-three (63.9 %) patients achieved SF and 34 (41.0 %) achieved complete SF at their last visit. Older age at epilepsy onset, male sex, low pretreatment seizure density, history of central nervous system infection before age 5, absence of aura, and fewer antiseizure medications in the final regimen were associated with favorable outcome. Of the 84 patients, 11 (13.1 %) underwent temporal lobectomy. CONCLUSIONS: Medical treatment outcomes in treatment-naïve MTLE-HS were relatively better than previously reported outcomes in MTLE-HS, although frequent fluctuations in seizure control were observed.

MRI-Based Radiomics Approach for Differentiating Juvenile Myoclonic Epilepsy from Epilepsy with Generalized Tonic-Clonic Seizures Alone.

BACKGROUND: The clinical presentation of juvenile myoclonic epilepsy (JME) and epilepsy with generalized tonic-clonic seizures alone (GTCA) is similar, and MRI scans are often perceptually normal in both conditions making them challenging to differentiate. PURPOSE: To develop and validate an MRI-based radiomics model to accurately diagnose JME and GTCA, as well as to classify prognostic groups. STUDY TYPE: Retrospective. POPULATION: 164 patients (127 with JME and 37 with GTCA) patients (age 24.0 ± 9.6; 50% male), divided into training (n = 114) and test (n = 50) sets in a 7:3 ratio with the same proportion of JME and GTCA patients kept in both sets. FIELD STRENGTH/SEQUENCE: 3T; 3D T1-weighted spoiled gradient-echo. ASSESSMENT: A total of 17 region-of-interest in the brain were identified as having clinical evidence of association with JME and GTCA, from where 1581 radiomics features were extracted for each subject. Forty-eight machine-learning combinations of oversampling, feature selection, and classification algorithms were explored to develop an optimal radiomics model. The performance of the best radiomics models for diagnosis and for classification of the favorable outcome group were evaluated in the test set. STATISTICAL TESTS: Model performance measured using area under the curve (AUC) of receiver operating characteristic (ROC) curve. Shapley additive explanations (SHAP) analysis to estimate the contribution of each radiomics feature. RESULTS: The AUC (95% confidence interval) of the best radiomics models for diagnosis and for classification of favorable outcome group were 0.767 (0.591-0.943) and 0.717 (0.563-0.871), respectively. SHAP analysis revealed that the first-order and textural features of the caudate, cerebral white matter, thalamus proper, and putamen had the highest importance in the best radiomics model. CONCLUSION: The proposed MRI-based radiomics model demonstrated the potential to diagnose JME and GTCA, as well as to classify prognostic groups. MRI regions associated with JME, such as the basal ganglia, thalamus, and cerebral white matter, appeared to be important for constructing radiomics models. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

Development and validation of an artificial intelligence model for the early classification of the aetiology of meningitis and encephalitis: a retrospective observational study.

Background: Early diagnosis and appropriate treatment are essential in meningitis and encephalitis management. We aimed to implement and verify an artificial intelligence (AI) model for early aetiological determination of patients with encephalitis and meningitis, and identify important variables in the classification process. Methods: In this retrospective observational study, patients older than 18 years old with meningitis or encephalitis at two centres in South Korea were enrolled for development (n = 283) and external validation (n = 220) of AI models, respectively. Their clinical variables within 24 h after admission were used for the multi-classification of four aetiologies including autoimmunity, bacteria, virus, and tuberculosis. The aetiology was determined based on the laboratory test results of cerebrospinal fluid conducted during hospitalization. Model performance was assessed using classification metrics, including the area under the receiver operating characteristic curve (AUROC), recall, precision, accuracy, and F1 score. Comparisons were performed between the AI model and three clinicians with varying neurology experience. Several techniques (eg, Shapley values, F score, permutation feature importance, and local interpretable model-agnostic explanations weights) were used for the explainability of the AI model. Findings: Between January 1, 2006, and June 30, 2021, 283 patients were enrolled in the training/test dataset. An ensemble model with extreme gradient boosting and TabNet showed the best performance among the eight AI models with various settings in the external validation dataset (n = 220); accuracy, 0.8909; precision, 0.8987; recall, 0.8909; F1 score, 0.8948; AUROC, 0.9163. The AI model outperformed all clinicians who achieved a maximum F1 score of 0.7582, by demonstrating a performance of F1 score greater than 0.9264. Interpretation: This is the first multiclass classification study for the early determination of the aetiology of meningitis and encephalitis based on the initial 24-h data using an AI model, which showed high performance metrics. Future studies can improve upon this model by securing and inputting time-series variables and setting various features about patients, and including a survival analysis for prognosis prediction. Funding: MD-PhD/Medical Scientist Training Program through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare, Republic of Korea.

Development and Validation of MRI-Based Radiomics Models for Diagnosing Juvenile Myoclonic Epilepsy.

OBJECTIVE: Radiomic modeling using multiple regions of interest in MRI of the brain to diagnose juvenile myoclonic epilepsy (JME) has not yet been investigated. This study aimed to develop and validate radiomics prediction models to distinguish patients with JME from healthy controls (HCs), and to evaluate the feasibility of a radiomics approach using MRI for diagnosing JME. MATERIALS AND METHODS: A total of 97 JME patients (25.6 ± 8.5 years; female, 45.5%) and 32 HCs (28.9 ± 11.4 years; female, 50.0%) were randomly split (7:3 ratio) into a training (n = 90) and a test set (n = 39) group. Radiomic features were extracted from 22 regions of interest in the brain using the T1-weighted MRI based on clinical evidence. Predictive models were trained using seven modeling methods, including a light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, with radiomics features in the training set. The performance of the models was validated and compared to the test set. The model with the highest area under the receiver operating curve (AUROC) was chosen, and important features in the model were identified. RESULTS: The seven tested radiomics models, including light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, showed AUROC values of 0.817, 0.807, 0.783, 0.779, 0.767, 0.762, and 0.672, respectively. The light gradient boosting machine with the highest AUROC, albeit without statistically significant differences from the other models in pairwise comparisons, had accuracy, precision, recall, and F1 scores of 0.795, 0.818, 0.931, and 0.871, respectively. Radiomic features, including the putamen and ventral diencephalon, were ranked as the most important for suggesting JME. CONCLUSION: Radiomic models using MRI were able to differentiate JME from HCs.

Crystal-clear days and unclear days in migraine: A population-based study.

OBJECTIVE: To investigate crystal-clear days and unclear days in participants with migraine. BACKGROUND: Migraine affects individuals during the headache-free period. Therefore, headache-free days do not indicate migraine symptom-free days. Crystal-clear days can be characterized by days without headache and having minimal or no migraine symptoms. In contrast, days without headache, but with more than minimal migraine symptoms, can be defined as unclear days. METHODS: We used the baseline respondent data set of the Circannual Change in Headache and Sleep study, a nationwide population survey on headache and sleep. This study was a cross-sectional and case-control analysis of longitudinally collected data. The number of crystal-clear days per 30 days was assessed by asking "How many days have you had crystal-clear days without headache during the previous 30 days?". We defined headache-free, but not crystal-clear days, as unclear days. The number of unclear days per 30 days was calculated as follows: 30 - the number of headache days per 30 days - the number of crystal-clear days per 30 days. RESULTS: Of 170 participants with migraine, 165 (97.1%) had unclear days. The numbers of crystal-clear days (median [interquartile range] 20.0 [15.0-25.0] vs. 25.0 [20.0-29.0], p < 0.001) and unclears days (4.0 [0.0-8.0] vs. 1.0 [0.0-7.0], p < 0.001) per 30 days in participants with migraine were significantly lower and higher, respectively, than in those with non-migraine headache. Headache days (incident rate ratio and 95% confidence interval, 0.94 [0.90-0.97], p < 0.001) and weekly average sleep duration (0.95 [0.91-1.00], p = 0.035) were significant factors for crystal-clear days. CONCLUSIONS: The number of crystal-clear days were different from that of headache-free days. Almost all participants with migraine had unclear days. Our findings will facilitate understanding the symptoms and burden of migraine.

Development and validation of a web-based headache diagnosis questionnaire.

Information technology advances may help in conducting epidemiological studies using web-based surveys. Questionnaire-based headache diagnosis should be validated against the doctor's diagnosis. This study aimed to develop and validate a web-based diagnostic questionnaire for migraine, probable migraine (PM), and tension-type headache (TTH). We constructed a seven-item questionnaire for diagnosing migraine, PM, and TTH. A web-based survey was conducted among adults aged 20-59 years; migraine, PM, and TTH were diagnosed based on the responses. Validation interview was performed via telephone by a neurologist within 1 month after the web-based interview. Finally, 256 participants completed both web-based survey and validation interview. Of them, 121 (47.3%), 65 (25.4%), 61 (23.8%), and 9 (3.5%) were diagnosed with migraine, PM, TTH, and unclassified headache (UH), respectively in the web-based survey, whereas 119 (46.5%), 60 (23.4%), 74 (28.9%), 2 (0.8%), and 1 (0.4%) were diagnosed with migraine, PM, TTH, UH, and primary stabbing headache, respectively in the validation interview. The best agreement was found in migraine (sensitivity: 92.6%; specificity: 94.8%; kappa coefficient: 0.875), followed by TTH (sensitivity: 78.4%; specificity: 98.4%; kappa coefficient: 0.809). PM showed the least agreement (sensitivity: 85.0%; specificity: 92.9%; kappa coefficient: 0.757). In conclusion, our questionnaire is valid in identifying these headache disorders.

Prevalence and impact of visual aura in migraine and probable migraine: a population study.

Visual aura (VA) presents in 98% of cases of migraine with aura. However, data on its prevalence and impact in individuals with migraine and probable migraine (PM) are limited. Data from the nation-wide, population-based Circannual Change in Headache and Sleep Study were collected. Participants with VA rating scale scores ≥ 3 were classified as having VA. Of 3,030 participants, 170 (5.6%) and 337 (11.1%) had migraine and PM, respectively; VA prevalence did not differ between these cohorts (29.4% [50/170] vs. 24.3% [82/337], p = 0.219). Participants with migraine with VA had a higher headache frequency per month (4.0 [2.0-10.0] vs. 2.0 [1.0-4.8], p = 0.014) and more severe cutaneous allodynia (12-item Allodynia Symptom Checklist score; 3.0 [1.0-8.0] vs. 2.0 [0.0-4.8], p = 0.046) than those without VA. Participants with PM with VA had a higher headache frequency per month (2.0 [2.0-8.0] vs. 2.0 [0.6-4.0], p = 0.001), greater disability (Migraine Disability Assessment score; 10.0 [5.0-26.3] vs. 5.0 [2.0-12.0], p < 0.001), and more severe cutaneous allodynia (12-item Allodynia Symptom Checklist score, 2.5 [0.0-6.0] vs. 0.0 [0.0-3.0], p < 0.001) than those without VA. VA prevalence was similar between migraine and PM. Some symptoms were more severe in the presence of VA.

Metabolic network is related to surgical outcome in temporal lobe epilepsy with hippocampal sclerosis: A brain FDG-PET study.

BACKGROUND AND PURPOSE: The aim of this study was to investigate differences in metabolic networks based on preoperative fluorodeoxyglucose (FDG)-positron emission tomography (PET) in temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS) between patients with complete seizure-free (SF) and those with noncomplete seizure-free (non-SF) after anterior temporal lobectomy. METHODS: This study was retrospectively performed at a tertiary hospital. We recruited pathologically confirmed 75 TLE patients with HS who underwent preoperative FDG-PET. All patients underwent a standard anterior temporal lobectomy. The surgical outcome was evaluated at least 12 months after surgery, and we divided the subjects into patients with SF (International League Against Epilepsy [ILAE] class I) and those with non-SF (ILAE class II-VI). We evaluated the metabolic network using graph theoretical analysis based on FDG-PET. We investigated the differences in network measures between the two groups. RESULTS: Of the 75 TLE patients with HS, 32 patients (42.6%) had SF, whereas 43 patients (57.3%) had non-SF. There were significant differences in global metabolic networks according to surgical outcomes. The patients with SF had a lower assortative coefficient than those with non-SF (-0.020 vs. -0.009, p = .044). We also found widespread regional differences in local metabolic networks according to surgical outcomes. CONCLUSION: Our study demonstrates significant differences in preoperative metabolic networks based on FDG-PET in TLE patients with HS according to surgical outcomes. This work introduces a metabolic network based on FDG-PET and can be used as a potential tool for predicting surgical outcome in TLE patients with HS.

Intrinsic Thalamic Network in Temporal Lobe Epilepsy With Hippocampal Sclerosis According to Surgical Outcomes.

Background: The aim of this study was to identify the differences of intrinsic amygdala, hippocampal, or thalamic networks according to surgical outcomes in temporal lobe epilepsy (TLE) patients with hippocampal sclerosis (HS). Methods: We enrolled 69 pathologically confirmed TLE patients with HS. All patients had pre-operative three-dimensional T1-weighted MRI using a 3.0 T scanner. We obtained the structural volumes of the amygdala nuclei, hippocampal subfields, and thalamic nuclei. Then, we investigated the intrinsic networks based on volumes of these structures using structural covariance and graph theoretical analysis. Results: Of the 69 TLE patients with HS, 21 patients (42.1%) had poor surgical outcomes, whereas 40 patients (57.9%) had good surgical outcomes. The volumes in the amygdala nuclei, hippocampal subfields, and thalamic nuclei were not different according to surgical outcome. In addition, the intrinsic amygdala and hippocampal networks were not different between the patients with poor and good surgical outcomes. However, there was a significant difference in the intrinsic thalamic network in the ipsilateral hemisphere between them. The eccentricity and small-worldness index were significantly increased, whereas the characteristic path length was decreased in the patients with poor surgical outcomes compared to those with good surgical outcomes. Conclusion: We successfully demonstrated significant differences in the intrinsic thalamic network in the ipsilateral hemisphere between TLE patients with HS with poor and good surgical outcomes. This result suggests that the pre-operative intrinsic thalamic network can be related with surgical outcomes in TLE patients with HS.

Weekend catch-up sleep and depression: results from a nationally representative sample in Korea.

BACKGROUND: There is limited information on the association between weekend catch-up sleep (CUS), which has beneficial effects on health, and depression. This study aimed to investigate the association between CUS and depression in adults. METHODS: We used the data of the Seventh Korea National Health and Nutrition Examination Survey, 2016. Depression was defined as Patient Health Questionnaire-9 score ≥10. We categorized CUS duration as ≤0, 0 < to 1, 1 < to 2, and >2 h. RESULTS: Of 5550 eligible participants, 3286 (54.9%), 1033 (19.5%), 723 (14.7%) and 508 (10.9%) had CUS duration ≤0, 0 < to 1, 1 < to 2, and >2 h, respectively; of these, the prevalence of depression was 7.0%, 4.2%, 2.9%, and 6.0%, respectively. Multivariable regression analyses including covariates revealed that individuals with CUS duration 1 < to 2 h had a significantly decreased risk of depression compared to individuals with CUS duration ≤0 h (odds ratio [OR] = 0.517, 95% CI = 0.309-0.865). Individuals with CUS duration 0 < to 1 h (OR = 0.731, 95% CI = 0.505-1.060) and >2 h (OR = 1.164, 95% CI = 0.718-1.886) showed no significantly different risk of depression. CONCLUSIONS: The risk of depression in individuals with CUS duration 1 < to 2 h was lower than for those with CUS duration ≤0 h. This finding provides a better understanding on the association between CUS and depression; and can be a basis for better management of depression.

Impact of Insomnia Symptoms on the Clinical Presentation of Depressive Symptoms: A Cross-Sectional Population Study.

Objective: Insomnia and depression are prevalent disorders that often co-occur. This study aimed to investigate the impact of clinically significant insomnia symptoms on the prevalence and clinical presentation of clinically significant depressive symptoms and vice versa. Methods: This study used data from the Korean Headache-Sleep Study (KHSS), a nationwide cross-sectional population-based survey regarding headache and sleep. Clinically significant insomnia symptoms were defined as Insomnia Severity Index (ISI) scores ≥ 10 and clinically significant depressive symptoms were defined as Patient Health Questionnaire-9 (PHQ-9) scores ≥ 10, respectively. We referred clinically significant insomnia symptoms and clinically significant depressive symptoms as insomnia symptoms and depressive symptoms, respectively. Results: Of 2,695 participants, 290 (10.8%) and 116 (4.3%) were classified as having insomnia and depressive symptoms, respectively. The prevalence of depressive symptoms was higher among participants with insomnia symptoms than in those without insomnia symptoms (25.9 vs. 1.7%, respectively, P < 0.001). Among participants with depressive symptoms, the PHQ-9 scores were not significantly different between participants with and without insomnia symptoms (P = 0.124). The prevalence of insomnia symptoms was significantly higher among participants with depressive symptoms than in those without depressive symptoms (64.7 vs. 8.3%, respectively, P < 0.001). The ISI scores were significantly higher among participants with insomnia and depressive symptoms than in participants with insomnia symptoms alone (P < 0.001). Conclusions: Participants with depressive symptoms had a higher risk of insomnia symptoms than did those without depressive symptoms. The severity of depressive symptoms did not significantly differ based on insomnia symptoms among participants with depressive symptoms; however, the severity of insomnia symptoms was significantly higher in participants with depressive symptoms than in those without depressive symptoms.

Effect of Number of Previous Antiseizure Medications on Efficacy and Tolerability of Adjunctive Brivaracetam for Uncontrolled Focal Seizures: Post Hoc Analysis.

INTRODUCTION: The aim was to evaluate the efficacy and tolerability of adjunctive brivaracetam (BRV) in adults with severely drug-resistant focal seizures versus adults with less drug-resistant disease. METHODS: Data were pooled from patients with focal seizures on 1-2 concomitant antiseizure medications (ASMs) randomized to BRV 50, 100, 200 mg/day, or placebo in 3 phase 3 trials (N01252 [NCT00490035], N01253 [NCT00464269], and N01358 [NCT01261325]) with a 12-week treatment period. Outcomes were assessed in patients with ≥ 5 and 0-4 previous ASMs (stopped before trial drug initiation). RESULTS: In ≥ 5 previous ASMs subgroup (BRV 50, 100, 200 mg/day: n = 26, n = 137, n = 120; placebo: n = 151), percentage reduction over placebo in 28-day adjusted focal seizure frequency was 13.0% for 50 mg/day (p = 0.38), 18.1% for 100 mg/day (p = 0.006), 19.8% for 200 mg/day (p = 0.004), and 17.0% for all BRV-treated patients (p = 0.001). The 50% responder rate was 26.9%, 29.9%, 30.0%, and 29.7% for BRV 50, 100, 200, and 50-200 mg/day, respectively (placebo: 13.2%); odds ratios versus placebo were statistically significant (p < 0.05) for BRV 100, 200, and 50-200 mg/day. In 0-4 previous ASMs subgroup (BRV 50, 100, 200 mg/day: n = 135, n = 195, n = 129; placebo: n = 267), all BRV dosages showed statistically significant (1) percentage reduction over placebo in 28-day adjusted focal seizure frequency (21.4-28.7%); (2) differences from placebo in median percentage reduction in 28-day adjusted focal seizure frequency from baseline (35.5-45.9%; placebo: 21.3%); and (3) odds ratios versus placebo (favoring BRV) for 50% responder rates. In BRV-treated patients, treatment-emergent adverse event (TEAE) incidence (73.8% [217/294] vs. 64.6% [329/509]) and discontinuation due to TEAEs (10.5% vs. 4.5%) were higher in the ≥ 5 versus 0-4 previous ASMs subgroup; serious TEAEs were rare in both subgroups (≥ 5 previous ASMs: 3.1%; 0-4 previous ASMs: 2.9%). CONCLUSION: Adjunctive BRV showed efficacy and was generally well tolerated in adults with focal seizures independent of the number of previous ASMs.

Nasopharyngeal electrodes in temporal lobe epilepsy: A reappraisal of their diagnostic utility.

OBJECTIVE: To compare electroencephalography (EEG) recordings with nasopharyngeal electrodes (NPEs) plus anterior temporal electrodes (ATEs) (NPE recordings) and those with only ATEs (non-NPE recordings) for the detection of interictal epileptiform discharges (IEDs) in patients with suspected temporal lobe epilepsy (TLE). METHODS: We retrospectively analyzed the initial EEGs of 229 patients that were recorded simultaneously with ATEs and NPEs in addition to the electrodes of the 10-20 system of electrode placement. Two data sets of NPE and non-NPE recordings were reviewed independently by three interpreters with differing degrees of experience. Discordant findings in the interpretation among the three interpreters were resolved by a consensus to yield final results. RESULTS: IEDs were detected in 76.4% of patients with NPE recordings compared to 55.5% with non-NPE recordings (p < 0.01). Bilateral independent IEDs were found in 26.2% and 11.4% of EEGs with NPE and non-NPE recordings (p < 0.01). The degree of agreement for the detection of IEDs among the three interpreters was higher with the NPE than with non-NPE recordings (κappa score, 0.70 vs. 0.54). The increased diagnostic yield of NPE recordings for the detection of IEDs was particularly prominent in patients with mesial and non-lesional TLEs. CONCLUSIONS: EEG recordings using NPEs are useful to improve the sensitivity and level of agreement among interpreters for the detection of IEDs in patients with TLE. SIGNIFICANCE: NPE recordings may be recommended in routine EEGs for the evaluation of patients with suspected TLE.

Nasal pain as an aura: Amygdala origin?

PURPOSE: Nasal pain, as an epileptic aura, has been poorly recognized. This study aims to demonstrate clinical features of patients with epilepsy who have nasal pain as an aura. METHODS: We retrospectively investigated consecutive patients who visited the epilepsy clinic of tertiary hospital from April 2000 to September 2019. All included patients underwent epilepsy-dedicated, high-resolution magnetic resonance imaging (MRI) examinations. All MRI studies were analyzed by visual inspection. RESULTS: Seven patients who presented nasal pain as an aura, were identified. Four patients reported nasal pain as the first aura. Four patients had right amygdala enlargement (isolated amygdala enlargement in three patients; amygdala enlargement in addition to hippocampal sclerosis in one patient), and one patient with compression of an internal carotid-posterior communicating artery aneurysm to right amygdala on brain MRI. Interictal epileptiform or ictal discharges on EEG were found in the right temporal region in five patients. In all four patients with amygdala enlargement, amygdala enlargement was ipsilateral to EEG anomalies. In all patients, nasal pain was accompanied by ictal semiological features, such as autonomic, olfactory, abdominal, or psychic auras, and focal impaired awareness seizures, which are typically associated with mesial temporal lobe epilepsy. CONCLUSIONS: Our findings suggest that nasal pain can occur as an epileptic aura in patients with temporal lobe epilepsy with probable involvement of the amygdala.

Functional Neural Changes after Low-Frequency Bilateral Globus Pallidus Internus Deep Brain Stimulation for Post-Hypoxic Cortical Myoclonus: Voxel-Based Subtraction Analysis of Serial Positron Emission.

Post-hypoxic myoclonus (PHM) and Lance-Adams syndrome (LAS) are rare conditions following cardiopulmonary resuscitation. The aim of this study was to identify functional activity in the cerebral cortex after a hypoxic event and to investigate alterations that could be modulated by deep brain stimulation (DBS). A voxel-based subtraction analysis of serial positron emission tomography (PET) scans was performed in a 34-year-old woman with chronic medically refractory PHM that improved with bilateral globus pallidus internus (Gpi) DBS implanted three years after the hypoxic event. The patient required low-frequency stimulation to show myoclonus improvement. Using voxel-based statistical parametric mapping, we identified a decrease in glucose metabolism in the prefrontal lobe including the dorsolateral, orbito-, and inferior prefrontal cortex, which was suspected to be the origin of the myoclonus from postoperative PET/magnetic resonance imaging (MRI) after DBS. Based on the present study results, voxel-based subtraction of PET appears to be a useful approach for monitoring patients with PHM treated with DBS. Further investigation and continuous follow-up on the use of PET analysis and DBS treatment for patients with PHM are necessary to help understanding the pathophysiology of PHM, or LAS.

Sex differences in the association between chronotype and risk of depression.

Information on sex differences in the association between chronotype and depression is scarce. We aimed to investigate these differences using data from the Korea National Health and Nutrition Examination Survey in 2016. Chronotypes were categorised based on mid-sleep time on free days corrected by sleep debt accumulated on workdays (MSFsc): early type, < mean MSFsc - 1 standard deviation (SD); intermediate type, between mean MSFsc - 1 SD and MSFsc + 1 SD; and late type, > mean MSFsc + 1 SD. A Patient Health Questionnaire-9 score of ≥ 10 indicated depression. Among 5550 non-shift working adults aged 19-80 years, the prevalence rates of depression in the early, intermediate, and late chronotype groups were 7.4%, 4.5%, and 9.3%, respectively. Women with late chronotype (odds ratio [OR] = 2.9, 95% confidence interval [CI] = 1.8-4.7) showed a higher risk of depression than women with intermediate chronotype after adjusting for covariates. Women with early chronotype did not show a significant difference in depression risk (OR = 1.3, 95% CI = 0.9-2.0). In conclusion, late chronotype is associated with an increased risk of depression in women but not in men. Early chronotype is not associated with depression in women or men.