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Three neuromodulation therapies have been appropriately tested and approved in refractory focal epilepsies: vagus nerve stimulation (VNS), deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS), and closed-loop responsive neurostimulation of the epileptogenic zone or zones. These therapies are primarily palliative. Only a few individuals have achieved complete freedom from seizures for more than 12 months with these therapies, whereas more than half have benefited from long-term reduction in seizure frequency of more than 50%. Implantation-related adverse events primarily include infection and pain at the implant site. Intracranial haemorrhage is a frequent adverse event for ANT-DBS and responsive neurostimulation. Other stimulation-specific side-effects are observed with VNS and ANT-DBS. Biomarkers to predict response to neuromodulation therapies are not available, and high-level evidence to aid decision making about when and for whom these therapies should be preferred over other antiepileptic treatments is scant. Future studies are thus needed to address these shortfalls in knowledge, approve other forms of neuromodulation, and develop personalised closed-loop therapies with embedded machine learning. Until then, neuromodulation could be considered for individuals with intractable seizures, ideally after the possibility of curative surgical treatment has been carefully assessed and ruled out or judged less appropriate.

BACKGROUND: Since coronavirus disease 2019 (COVID-19) was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts. RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? STUDY DESIGN AND METHODS: We included adult patients (≥ 18 years) positive for laboratory-confirmed severe acute respiratory syndrome-coronavirus 2 infection from a prospective COVID-19 registry database in the Cleveland Clinic Health System in Ohio and Florida. The patients were split into training and testing sets. Using latent class analysis (LCA), we first identified phenotypic clusters of patients with COVID-19 based on demographics, comorbidities, and presenting symptoms. We then identified subphenotypes of hospitalized patients with additional blood biomarker data measured on hospital admission. The associations of phenotypes/subphenotypes and clinical outcomes were investigated. Multivariable prediction models were established to predict assignment to the LCA-defined phenotypes and subphenotypes and then evaluated on an independent testing set. RESULTS: We analyzed data for 20,572 patients. Seven phenotypes were identified on the basis of different profiles of presenting COVID-19 symptoms and existing comorbidities, including the following groups: young, no symptoms; young, symptoms; middle-aged, no symptoms; middle-aged, symptoms; middle-aged, comorbidities; old, no symptoms; and old, symptoms. The rates of inpatient hospitalization for the phenotypes were significantly different (P < .001). Five subphenotypes were identified for the subgroup of hospitalized patients, including the following subgroups: young, elevated WBC and platelet counts; middle-aged, lymphopenic with elevated C-reactive protein; middle-aged, hyperinflammatory; old, leukopenic with comorbidities; and old, hyperinflammatory with kidney dysfunction. The hospital mortality and the times from hospitalization to ICU transfer or death were significantly different (P < .001). The models for predicting the LCA-defined phenotypes and subphenotypes showed high discrimination (concordance index, 0.92 and 0.91). INTERPRETATION: Hypothesis-free LCA-defined phenotypes and subphenotypes of patients with COVID-19 can be identified. These may help clinical investigators conduct stratified analyses in clinical trials and assist basic science researchers in characterizing the pathobiology of the spectrum of COVID-19 presentations.

ObjectiveTo develop and externally validate models to predict the probability of postoperative verbal memory decline in adults after temporal lobe resection (TLR) for epilepsy using easily accessible preoperative clinical predictors.MethodsMultivariable models were developed to predict delayed verbal memory outcome on 3 commonly used measures: Rey Auditory Verbal Learning Test (RAVLT) and Logical Memory (LM) and Verbal Paired Associates (VPA) subtests from Wechsler Memory Scale–Third Edition. With the use of the Harrell step-down procedure for variable selection, models were developed in 359 adults who underwent TLR at the Cleveland Clinic and validated in 290 adults at 1 of 5 epilepsy surgery centers in the United States or Canada.ResultsTwenty-nine percent of the development cohort and 26% of the validation cohort demonstrated significant decline on at least 1 verbal memory measure. Initial models had good to excellent predictive accuracy (calibration [c] statistic range 0.77–0.80) in identifying patients with memory decline; however, models slightly underestimated decline in the validation cohort. Model coefficients were updated with data from both cohorts to improve stability. The model for RAVLT included surgery side, baseline memory score, and hippocampal resection. The models for LM and VPA included surgery side, baseline score, and education. Updated model performance was good to excellent (RAVLT c = 0.81, LM c = 0.76, VPA c = 0.78). Model calibration was very good, indicating no systematic overestimation or underestimation of risk.ConclusionsNomograms are provided in 2 easy-to-use formats to assist clinicians in estimating the probability of verbal memory decline in adults considering TLR for treatment of epilepsy.Classification of EvidenceThis study provides Class II evidence that multivariable prediction models accurately predict verbal memory decline after TLR for epilepsy in adults.

Objective Patients undergoing frontal lobectomy demonstrate lower seizure-freedom rates than patients undergoing temporal lobectomy and several other resective interventions. We attempted to utilize automated preoperative quantitative analysis of focal and global cortical volume loss to develop predictive volumetric indicators of seizure outcome after frontal lobectomy. Methods Ninety patients who underwent frontal lobectomy were stratified based on seizure freedom at a mean follow-up time of 3.5 (standard deviation [SD] 2.5) years. Automated quantitative analysis of cortical volume loss organized by distinct brain region and laterality was performed on preoperative T1-weighted magnetic resonance imaging (MRI) studies. Univariate statistical analysis was used to select potential predictors of seizure freedom. Backward variable selection and multivariate logistical regression were used to develop models to predict seizure freedom. Results Forty-eight of 90 (53.3%) patients were seizure-free at the last follow-up. Several frontal and extrafrontal brain regions demonstrated statistically significant differences in both volumetric cortical volume loss and volumetric asymmetry between the left and right sides in the seizure-free and non-seizure-free cohorts. A final multivariate logistic model utilizing only preoperative quantitative MRI data to predict seizure outcome was developed with a c-statistic of 0.846. Using both preoperative quantitative MRI data and previously validated clinical predictors of seizure outcomes, we developed a model with a c-statistic of 0.897. Significance This study demonstrates that preoperative cortical volume loss in both frontal and extrafrontal regions can be predictive of seizure outcome after frontal lobectomy, and models can be developed with excellent predictive capabilities using preoperative MRI data. Automated quantitative MRI analysis can be quickly and reliably performed in patients with frontal lobe epilepsy, and further studies may be developed for integration into preoperative risk stratification.

Objective To develop a model to predict the probability of mood decline in adults following temporal lobe resection for the treatment of pharmacoresistant epilepsy. Methods Variable selection was performed on 492 patients from the Cleveland Clinic using best subsets regression. After completing variable selection, a subset of variables was requested from four epilepsy surgery centers across North America (n = 100). All data were combined to develop a final model to predict postoperative mood decline (N = 592). Internal validation with bootstrap resampling was performed. A clinically significant increase in depressive symptoms was defined as a 15% increase in Beck Depression Inventory-Second Edition score and a postoperative raw score > 11. Results Fourteen percent of patients in the Cleveland Clinic cohort and 22% of patients in the external cohort experienced clinically significant increases in depressive symptoms following surgery. The final prediction model included six predictor variables: psychiatric history, resection side, relationship status, verbal fluency score, age at preoperative testing, and presence/absence of malformation of cortical development on magnetic resonance imaging. The model had an optimism-adjusted c-statistic of .70 and good calibration, with slight probability overestimation in higher risk patients. Significance Clinicians can utilize our nomogram via a paper tool or online calculator to estimate the risk of postoperative mood decline for individual patients prior to temporal lobe epilepsy surgery.

The aim of this study was to conduct item reduction of the Memory Assessment Clinics Self-Rating Scale (MAC-S) to create a briefer measure that can be used to quickly evaluate subjective memory com...

OBJECTIVE: To characterize seizure and cognitive outcomes of sparing vs removing an magnetic resonance imaging (MRI)–normal hippocampus in patients with temporal lobe epilepsy. METHODS: In this retrospective cohort study, we reviewed clinical, imaging, surgical, and histopathological data on 152 individuals with temporal lobe epilepsy and non-lesional hippocampi categorized into hippocampus-spared (n = 74) or hippocampus-resected (n = 78). Extra-hippocampal lesions were allowed. Pre- and postoperative cognitive data were available on 86 patients. Predictors of seizure and cognitive outcomes were identified using Cox-proportional hazard modeling followed by treatment-specific model reduction according to Akaike information criterion, and built into an online risk calculator. RESULTS: Seizures recurred in 40% within one postoperative year, and in 63% within six postoperative years. Male gender (P = .03), longer epilepsy duration (P < .01), normal MRI (P = .04), invasive evaluation (P = .02), and acute postoperative seizures (P < .01) were associated with a higher risk of recurrence. We found no significant difference in postoperative seizure freedom rates at 5 years between those whose hippocampus was spared and those whose hippocampus was resected (P = .17). Seizure outcome models built with pre- and postoperative data had bootstrap validated concordance indices of 0.65 and 0.72. The dominant hippocampus-spared group had lower rates of decline in verbal memory (39% vs 70%; P = .03) and naming (41% vs 79%; P = .01) compared to the hippocampus-resected group. Partial hippocampus sparing had the same risk of verbal memory decline as for complete removal. SIGNIFICANCE: Sparing or removing an MRI-normal hippocampus yielded similar long-term seizure outcome. A more conservative approach, sparing the hippocampus, only partially shields patients from postoperative cognitive deficits. Risk calculators are provided to facilitate clinical counseling.

Objective Postencephalitic epilepsy is often resistant to antiseizure medications, leading to evaluation for epilepsy surgery. Characterizing its localization carries implications for optimal surgical approach. We aimed to determine whether a prior history of encephalitis is associated with specific epileptogenic networks among patients with drug resistant epilepsy undergoing stereotactic EEG (SEEG). Methods We conducted a retrospective cohort study of drug resistant epilepsy, with and without a prior history of encephalitis. We analyzed SEEG recordings to identify patterns of seizure onset and organization. Seventeen patients with a history of encephalitis (of infectious etiology in two subjects) were identified from a database of patients undergoing SEEG and were compared to seventeen drug-resistant epilepsy controls without a history of encephalitis matched for confounding variables including pre-implantation hypotheses, epilepsy duration, age, and sex. Results Independent bilateral seizures were noted in 65% of the postencephalitic epilepsy cohort. We identified four SEEG-ictal patterns in patients with a prior history of encephalitis: (1) anteromesial temporal onset (24%), (2) anteromesial temporal onset with early spread to the perisylvian region (29%), (3) perisylvian (59%) and (4) synchronized anteromesial temporal and perisylvian (29%) onsets. Patterns 3 and 4, with perisylvian involvement at onset, were unique to the encephalitis group (p = 0.0003 and 0.04 respectively) and exhibited a “patchwork” organization. None of the encephalitis patients vs 5/7 matched controls had Engel I outcome (p = 0.0048). Conclusions Postencephalitic epilepsies involve anteromesial temporal and perisylvian networks, often in a bilateral independent manner. Unique ictal patterns involving the perisylvian regions was identified in the encephalitis group, but not in the matched control group. Significance: These findings may reflect a selective vulnerability of the perisylvian regions to epilepsy resulting from encephalitis, significantly mitigating the chances of success with SEEG-guided temporal resections.

ObjectivesTo provide information on the effect of the coronavirus disease of 2019 (COVID-19) pandemic on people with epilepsy and provide consensus recommendations on how to provide the best possible care for people with epilepsy while avoiding visits to urgent care facilities and hospitalizations during the novel coronavirus pandemic.MethodsThe authors developed consensus statements in 2 sections. The first was “How should we/clinicians modify our clinical care pathway for people with epilepsy during the COVID-19 pandemic?” The second was “What general advice should we give to people with epilepsy during this crisis? The authors individually scored statements on a scale of −10 (strongly disagree) to +10 (strongly agree). Five of 11 recommendations for physicians and 3/5 recommendations for individuals/families were rated by all the authors as 7 or above (strongly agree) on the first round of rating. Subsequently, a teleconference was held where statements for which there was a lack of strong consensus were revised.ResultsAfter revision, all consensus recommendations received a score of 7 or above. The recommendations focus on administration of as much care as possible at home to keep people with epilepsy out of health care facilities, where they are likely to encounter COVID-19 (including strategies for rescue therapy), as well as minimization of risk of seizure exacerbation through adherence, and through ensuring a regular supply of medication. We also provide helpful links to additional helpful information for people with epilepsy and health providers.ConclusionThese recommendations may help health care professionals provide optimal care to people with epilepsy during the coronavirus pandemic.

BACKGROUND AND PURPOSE: NeuroQuant is an FDA-approved software that performs automated MR imaging quantitative volumetric analysis. This study aimed to compare the accuracy of NeuroQuant analysis with visual MR imaging analysis by neuroradiologists with expertise in epilepsy in identifying hippocampal sclerosis. MATERIALS AND METHODS: We reviewed 144 adult patients who underwent presurgical evaluation for temporal lobe epilepsy. The reference standard for hippocampal sclerosis was defined by having hippocampal sclerosis on pathology (n = 61) or not having hippocampal sclerosis on pathology (n = 83). Sensitivities, specificities, positive predictive values, and negative predictive values were compared between NeuroQuant analysis and visual MR imaging analysis by using a McNemar paired test of proportions and the Bayes theorem. RESULTS: NeuroQuant analysis had a similar specificity to neuroradiologist visual MR imaging analysis (90.4% versus 91.6%; P = .99) but a lower sensitivity (69.0% versus 93.0%, P

ObjectiveThe aim was to compare the outcomes of subdural electrode (SDE) implantations versus stereotactic electroencephalography (SEEG), the 2 predominant methods of intracranial electroencephalography (iEEG) performed in difficult-to-localize drug-resistant focal epilepsy.MethodsThe Surgical Therapies Commission of the International League Against Epilepsy created an international registry of iEEG patients implanted between 2005 and 2019 with ≥1 year of follow-up. We used propensity score matching to control exposure selection bias and generate comparable cohorts. Study endpoints were: (1) likelihood of resection after iEEG; (2) seizure freedom at last follow-up; and (3) complications (composite of postoperative infection, symptomatic intracranial hemorrhage, or permanent neurological deficit).ResultsTen study sites from 7 countries and 3 continents contributed 2,012 patients, including 1,468 (73%) eligible for analysis (526 SDE and 942 SEEG), of whom 988 (67%) underwent subsequent resection. Propensity score matching improved covariate balance between exposure groups for all analyses. Propensity-matched patients who underwent SDE had higher odds of subsequent resective surgery (odds ratio [OR]=1.4, 95% confidence interval [CI] 1.05, 1.84) and higher odds of complications (OR=2.24, 95% CI 1.34, 3.74; unadjusted: 9.6% after SDE vs 3.3% after SEEG). Odds of seizure freedom in propensity-matched resected patients were 1.66 times higher (95% CI 1.21, 2.26) for SEEG compared with SDE (unadjusted: 55% seizure free after SEEG-guided resections vs 41% after SDE).InterpretationIn comparison to SEEG, SDE evaluations are more likely to lead to brain surgery in patients with drug-resistant epilepsy but have more surgical complications and lower probability of seizure freedom. This comparative-effectiveness study provides the highest feasible evidence level to guide decisions on iEEG. ANN NEUROL 2021;90:927-939.

ObjectiveTo determine whether a pocket card treatment algorithm improves the early treatment of status epilepticus and to assess its utilization and retention in clinical practice.MethodsMultidisciplinary care teams participated in video-recorded status epilepticus simulation sessions from 2015 to 2019. In this longitudinal cohort study, we examined the sessions recorded before and after introducing an internally developed, guideline-derived pocket card to determine differences in the adequacy or timeliness of rescue benzodiazepine. Simulation participants were queried 9 months later for submission of a differentiating identification number on each card to assess ongoing availability and utilization.ResultsForty-four teams were included (22 before and 22 after the introduction of the pocket card). The time to rescue therapy was shorter for teams with the pocket card available (84 seconds [64–132]) compared with teams before introduction (144 seconds [100–162]) (U = 94; median difference = −46.9, 95% confidence interval [CI]: −75.9 to −21.9). The adequate dosing did not differ with card availability (odds ratio 1.48, 95% CI: 0.43–5.1). At the 9-month follow-up, 32 participants (65%) completed the survey, with 26 (81%) self-reporting having the pocket card available and 11 (34%) confirming ready access with the identification number. All identification numbers submitted corresponded to the hard copy laminated pocket card, and none to the electronic version.ConclusionsA pocket card is a feasible, effective, and worthwhile educational tool to improve the implementation of updated guidelines for the treatment of status epilepticus.

Coronavirus Disease 2019 (COVID-19) is especially severe in aged patients, defined as 65 years or older, for reasons that are currently unknown. To investigate the underlying basis for this vulnerability, we performed multimodal data analyses on immunity, inflammation, and COVID-19 incidence and severity as a function of age. Our analysis leveraged age-specific COVID-19 mortality and laboratory testing from a large COVID-19 registry, along with epidemiological data of ∼3.4 million individuals, large-scale deep immune cell profiling data, and single-cell RNA-sequencing data from aged COVID-19 patients across diverse populations. To begin, we confirmed a significantly increased rate of severe outcomes in aged COVID-19 patients. Furthermore, we identified increased inflammatory markers (C-reactive protein, D-dimer, and neutrophil-lymphocyte ratio), viral entry factors in secretory cells, and TGFβ-mediated immune-epithelial cell interactions, as well as reduction in both naïve CD8 T cells and expression of interferon antiviral defense genes (i.e.,IFITM3andTRIM22), along with strong TGF-beta mediated immune-epithelial cell interactions (i.e., secretory - T regulatory cells), in aged severe COVID-19 patients. Taken together, our findings point to immuno-inflammatory factors that could be targeted therapeutically to reduce morbidity and mortality in aged COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a disproportionately severe effect on men, suggesting that the androgen pathway plays a role in the disease. Studies on the effect of castration and androgen receptor blockade have been mixed, while 5α-reductase inhibitor (5ARI) use in men with COVID-19 (2019 novel coronavirus) have shown potential benefits. We assessed the association of 5ARI use on risk of community acquired SARS-CoV-2 infection.A total of 60,474 males in a prospective registry of people tested for SARS-CoV-2 between March 8, 2020 and February 15, 2021 were included. Using a matched cohort design, men using 5ARIs were matched 1:1 to non5ARI users. Independent analysis using unconditional multivariable logistic regression on the entire unmatched data set was completed for validation. Primary outcome measures were the association of 5ARI use on rates of SARS-Cov-2 positivity and disease severity.Of the men 1,079 (1.8%) reported 5ARI use and 55,100 were available for matching. The final matched cohorts included 944 men each. Mean duration of use was 60.4 months (IQR 17-84 months). Absolute risk for infection was significantly lower in 5ARI users compared to nonusers, 42.3% (399/944) vs 47.2% (446/944), respectively (absolute risk reduction [ARR] 4.9%, OR 0.81, 95% CI 0.67-0.97, p=0.026). Unconditional multivariable logistic regression analysis of the entire study cohort of 55,100 men confirmed the protective association of 5ARI use (ARR 5.3%, OR=0.877, 95% CI 0.774-0.995, p=0.042). Use of 5ARIs was not associated with disease severity.Use of 5ARIs in men without prostate cancer was associated with a reduction in community acquired SARS-CoV-2 infection.

Objective This study aims to evaluate the role of scalp electroencephalography (EEG; ictal and interictal patterns) in predicting resective epilepsy surgery outcomes. We use the data to further develop a nomogram to predict seizure freedom. Methods We retrospectively reviewed the scalp EEG findings and clinical data of patients who underwent surgical resection at three epilepsy centers. Using both EEG and clinical variables categorized into 13 isolated candidate predictors and 6 interaction terms, we built a multivariable Cox proportional hazards model to predict seizure freedom 2 years after surgery. Harrell's step-down procedure was used to sequentially eliminate the least-informative variables from the model until the change in the concordance index (c-index) with variable removal was less than 0.01. We created a separate model using only clinical variables. Discrimination of the two models was compared to evaluate the role of scalp EEG in seizure-freedom prediction. Results Four hundred seventy patient records were analyzed. Following internal validation, the full Clinical + EEG model achieved an optimism-corrected c-index of 0.65, whereas the c-index of the model without EEG data was 0.59. The presence of focal to bilateral tonic-clonic seizures (FBTCS), high preoperative seizure frequency, absence of hippocampal sclerosis, and presence of nonlocalizable seizures predicted worse outcome. The presence of FBTCS had the largest impact for predicting outcome. The analysis of the models' interactions showed that in patients with unilateral interictal epileptiform discharges (IEDs), temporal lobe surgery cases had a better outcome. In cases with bilateral IEDs, abnormal magnetic resonance imaging (MRI) predicted worse outcomes, and in cases without IEDs, patients with extratemporal epilepsy and abnormal MRI had better outcomes. Significance This study highlights the value of scalp EEG, particularly the significance of IEDs, in predicting surgical outcome. The nomogram delivers an individualized prediction of postoperative outcome, and provides a unique assessment of the relationship between the outcome and preoperative findings.

Background Prior studies in the field of epilepsy surgical disparities have examined barriers in undergoing epilepsy surgical resections in disadvantaged populations involving trust in health providers, education level, social support, and fear of treatment. Few studies have analyzed the geographical locations of specialized epilepsy centers and their role in nationwide epilepsy surgical access and disparities. Objective To better visualize the locations of epilepsy level IV centers in the United States with respect to epilepsy prevalence and socioeconomic disadvantage. Methods We created heat maps of the United States to visualize geographical locations of level IV epilepsy centers with respect to the 2015 state-wide epilepsy prevalence and 2017 county-wide Area Deprivation Index (ADI) scores, a composite measure of socioeconomic disadvantage. Univariate logistic regression was used to test for associations between the presence or absence of epilepsy centers and socioeconomic disadvantage. Results We found eight states within the United States without any level IV epilepsy centers. In states with level IV centers, centers were clustered in populated and metropolitan regions. Disadvantaged counties (with increased ADI scores) were less likely to have level IV centers compared to counties that were less disadvantaged (lower ADI scores) (p Conclusion Further work is required to remedy the decreased access to specialized epilepsy care due to geographical disparities, and to better understand its contribution to overall disparities affecting epilepsy surgery referrals.

Quantitative volumetric brain MRI measurement is important in research applications, but translating it into patient care is challenging. We explore the incorporation of clinical automated quantitative MRI measurements in statistical models predicting outcomes of surgery for temporal lobe epilepsy. Four hundred and thirty-five patients with drug-resistant epilepsy who underwent temporal lobe surgery at Cleveland Clinic, Mayo Clinic and University of Campinas were studied. We obtained volumetric measurements from the pre-operative T1-weighted MRI using NeuroQuant, a Food and Drug Administration approved software package. We created sets of statistical models to predict the probability of complete seizure-freedom or an Engel score of I at the last follow-up. The cohort was randomly split into training and testing sets, with a ratio of 7:3. Model discrimination was assessed using the concordance statistic (C-statistic). We compared four sets of models and selected the one with the highest concordance index. Volumetric differences in pre-surgical MRI located predominantly in the frontocentral and temporal regions were associated with poorer outcomes. The addition of volumetric measurements to the model with clinical variables alone increased the model’s C-statistic from 0.58 to 0.70 (right-sided surgery) and from 0.61 to 0.66 (left-sided surgery) for complete seizure freedom and from 0.62 to 0.67 (right-sided surgery) and from 0.68 to 0.73 (left-sided surgery) for an Engel I outcome score. 57% of patients with extra-temporal abnormalities were seizure-free at last follow-up, compared to 68% of those with no such abnormalities (P-value = 0.02). Adding quantitative MRI data increases the performance of a model developed to predict post-operative seizure outcomes. The distribution of the regions of interest included in the final model supports the notion that focal epilepsies are network disorders and that subtle cortical volume loss outside the surgical site influences seizure outcome., Abbreviated summary Morita-Sherman et al. demonstrate how sophisticated research imaging can cross the divide to clinical practice. They show how quantitative MRI can enhance epilepsy surgery outcome prediction. Volume changes in the structures highlighted were identified as outcome predictors, supporting the hypothesis that subtle cortical atrophy outside the resection influences seizure outcome., Graphical Abstract Graphical Abstract

Rationale Psychogenic Nonepileptic Seizures (PNES) are seizure-like episodes without EEG abnormality, and are of psychological origin. Cognitive Behavioral Therapy (CBT), a type of psychological counseling, is known to be the best intervention to treat PNES and the underlying psychiatric symptoms. Yet, many remain untreated because of limited access to specialized counseling programs. In this study, first we intended to see if the positive outcomes of the CBTip can be replicated in our patient population using within-group comparison. We also aimed to examine the outcomes of patients who received a variable dose of treatment than the established treatment protocol. Method We obtained retrospective patient reported outcomes (PRO) data from patients treated with Cognitive Behavioral Therapy-informed psychotherapy (CBT-ip) from January 2015 to January 2020 in an outpatient tertiary care epilepsy center. The CBTip program is a 12-session intervention delivered weekly by a seizure counselor. Although the program comprises 12 sessions of treatment, we included patients who attended at least 7 sessions consistent with previous research that used a similar cutoff. We had a total of 160 patient PROs included in the analysis. Outcome variables including seizure frequency, depression, anxiety, and quality of life were examined using self-report outcome scores. Demographic and other clinical and psychosocial confounding variables were controlled. Results In the first analysis in which we compared pre-treatment scores with 3-month posttreatment scores, there was no significant change in seizure frequency, depression, anxiety, and quality-of-life outcomes. In the second analysis when we compared pre- and posttreatment scores in patients who completed the treatment in longer than 3-month time, there were significant improvement in primary and secondary outcomes. For seizure frequency, 10 patients had data for “seizures per day in the last 6 months” and 5 participants (50%) improved by 50% or more in the number of seizures per day. There were also significant reductions in depression and anxiety scores but not in quality of life. Implication and conclusions Our analysis showed that patients treated with CBTip with a minimum of 7 sessions in 3 months did not have significant improvement. However, attending at least 7 sessions of CBTip in longer than 3 months was effective for seizure control, depression, and anxiety. The observational and exploratory nature of our study, however, limits the generalizability of our findings outside of the single tertiary clinical care setting.

Hemispherectomy in Adults and Adolescents: Seizure and Functional Outcomes in 47 Patients McGovern RA, NV Moosa A, Jehi L, Busch R, Ferguson L, Gupta A, et al. Epilepsia. 2019;60(12):2416-2427. http://doi.org/10.1111/epi.16378.Objective:To examine longitudinal seizure and functional outcomes after hemispherectomy in adults and adolescents.Methods:We reviewed 47 consecutive patients older than 16 years who underwent hemispherectomy between 1996 and 2016 at our center. Clinical, electroencephalographic (EEG), imaging, neuropsychological, surgical, and functional status data were analyzed.Results:Thirty-six patients were 18 years or older at surgery; 11 were aged between 16 and 18 years. Brain injury leading to hemispheric epilepsy occurred before 10 years of age in 41 (87%) patients. At a mean follow-up of 5.3 postoperative years (median = 2.9 years), 36 (77%) had Engel class I outcome. Longitudinal outcome analysis showed 84% seizure freedom (Engel IA) at 6 months, 76% at 2 years, and 76% at 5 years and beyond, with stable longitudinal outcomes up to 12 years from surgery. Multivariate analysis demonstrated that acute postoperative seizures and contralateral interictal spikes at 6-month follow-up EEG were associated with seizure recurrence. Patients who could walk unaided preoperatively and had no cerebral peduncle atrophy on brain magnetic resonance imaging were more likely to experience worsening of motor function postoperatively. Otherwise, postoperative ambulatory status and hand function were unchanged. Of the 19 patients who completed neuropsychological testing, 17 demonstrated stable or improved postoperative outcomes.Significance:Hemispherectomy in adults is a safe and effective procedure, with seizure freedom rates and functional outcome similar to those observed in children.

BACKGROUND Previous reports have suggested an increasing rate of utilization of spinal fusions, but contemporary data have not been analyzed, and there has been little investigation of putative drivers of increased utilization. OBJECTIVE To investigate whether there is an ongoing trend of increased utilization of spinal fusions in recent data, and if there may be associations with an increasing proportion of elderly in the population, changing patterns of payer-types, and changing reimbursement rates. METHODS We analyze 7.1 million cases from the National Inpatient Sample between 1998 and 2014. We measure annual utilization per 100 000 persons and conduct trend analyses with subgroup analysis of the senior (65 + ) population. Spine surgery utilization is compared with nonspine surgical procedures (coronary artery bypass grafting, hernia repair, hip, and knee replacement). We assess trends in charges, payer type, Medicare reimbursement rates, and hospital type. RESULTS There was an 88% increase in the utilization rate of spinal fusion procedures from 1998 to 2014 (from 74 to 139 cases per 100 000 persons) with a significant upward trend (P

Objective The objective of this study was to compare the accuracy of clinical judgment in predicting seizure outcome after resective epilepsy surgery relative to two recently published statistical tools [the Epilepsy Surgery Nomogram (ESN) and the modified Seizure-Freedom score (m-SFS)]. Methods Details of presurgical evaluations of 20 patients who underwent epilepsy surgery were presented to 20 epilepsy experts. The final surgical treatment was also disclosed. The clinicians were asked to predict the likelihood of a good outcome (Engel 1) at 2 and 5 years in each case. The ESN and the m-SFS predictions were calculated with the data provided to the clinicians. The discriminative ability of clinical judgment, ESN, and m-SFS was assessed by calculating a concordance index (C-index). Expert opinion, the m-SFS and the ESN performances were compared using a Receiver Operating Characteristic (ROC) curve analysis. Results The mean age at surgery was 29 years (standard deviation [SD] = 14); 40% were male; 70% were right-handed, and thirteen (65%) had an Engel outcome 1 at 2 and 5 years. The mean C-index for the mean physician's prediction was 0.478 with a variance of 0.012. The ESN had an area under the curve (AUC) of 0.528 and 0.533 for the 2-year and 5-year predictions in comparison with the clinicians' predictions that was 0.476, and 0.466, respectively. For the m-SFS, the AUC at 2 years and 5 years was 0.539 and 0.539, respectively. No statistical difference was noted between the ESN and the clinicians or between m-SFS and the ESN, but there is a moderate statistical difference favoring the m-SFS to the clinicians (p 0.0960 and 0.0514, for 2 and 5 years). Significance Clinical judgment was not superior to the ESN nor to the m-SFS. Together with the interphysician's prediction variability, our findings reinforce the need for better tools to predict postoperative outcomes.

The American Epilepsy Society Meeting in New Orleans attracted more than 5900 attendees. There was a lively exchange of new science, innovation, education, clinical practice, and many other items related to epilepsy. Educational symposia were a major part of the meeting and explored varying topics of interest for all types of epilepsy professionals. This article reviews highlights of the meeting presented in major symposia. Topics ranged from how to treat varying aspects of epilepsy as a consultant in the hospital to finding the scientific underpinning of the interaction between sleep and epilepsy. Pros and cons of novel antiseizure medications, dietary, and stimulation treatments were discussed. Epilepsy may impair memory and we need to learn what is the pathophysiologic relationship. Febrile status epilepticus may have severe consequences for a later life with seizures. Epilepsy professionals should be very well aware of the ethical implications of devasting seizures and their associated disability. These are just a few select topics of the many that we need to study further to archive the final goal to improve the lives of patients with epilepsy.

OBJECTIVE: We aimed to determine the rates and predictors of resection and seizure freedom after bilateral stereo-electroencephalography (SEEG) implantation. METHODS: We reviewed 184 patients who underwent bilateral SEEG implantation (2009-2015). Noninvasive and invasive evaluation findings were collected. Outcomes of interest included subsequent resection and seizure freedom. Statistical analyses employed multivariable logistic regression and proportional hazard modeling. Preoperative and postoperative seizure frequency, severity, and quality of life scales were also compared. RESULTS: Following bilateral SEEG implantation, 106 of 184 patients (58%) underwent resection. Single seizure type (P = 0.007), a family history of epilepsy (P = 0.003), 10 or more seizures per month (P = 0.004), lower number of electrodes (P = 0.02), or sentinel electrode placement (P = 0.04) was predictive of undergoing a resection, as were lack of nonlocalized (P < 0.0001) or bilateral (P < 0.0001) ictal-onset zones on SEEG. Twenty-six of 81 patients (32% with follow-up greater than 1 year) remained seizure-free. Predictors of seizure freedom were single seizure type (P = 0.01), short epilepsy duration (P = 0.008), use of 2 or fewer antiepileptic drugs (AEDs) at the time of surgery (P = 0.0006), primary localization hypothesis involving the frontal lobe (P = 0.002), sentinel electrode placement only (P = 0.02), and lack of overlap between ictal-onset zone and eloquent cortex (P = 0.04), along with epilepsy substrate histopathology (P = 0.007). Complete resection of a suspected focal cortical dysplasia showed a trend to increased likelihood of seizure freedom (P = 0.09). The 44 of 55 patients (80%) who underwent resection and experienced seizure recurrence had >50% seizure reduction, as opposed to 26 of 45 patients (58%) who continued medical therapy alone (P = 0.003). Seventy-two percent of patients had a clinically meaningful quality of life improvement (>10% decrease in the Quality of Life in Epilepsy [QOLIE-10] score) at 1 year. SIGNIFICANCE: A strong preimplantation hypothesis of a suspected unifocal epilepsy increases the odds of resection and seizure freedom. We discuss a tailored approach, taking into account localization hypothesis and suspected epilepsy etiology in guiding implantation and subsequent surgical strategy.

Objective: To develop predictive models for in-hospital mortality and length of stay (LOS) for COVID-19 positive patients. Patients and Methods: We performed a multicenter retrospective cohort study of hospitalized COVID-19 positive patients. A total of 764 patients admitted to 14 different hospitals within the Cleveland Clinic from 03/09/2020 to 05/20/2020 who had reverse transcriptase-polymerase chain reaction proven coronavirus infection were included. We used LightGBM, a machine learning algorithm, to predict in-hospital mortality at different time points (after 7 days, 14 days, and 30 days of hospitalization) and in-hospital LOS. Results: Among 764 patients, 116 (15%) either died (n = 87) or were transitioned to hospice care (n = 29) during their hospitalization. The median LOS was 5 days (range 1 - 44 days) for patients admitted to the regular nursing floor and 10 days (range 1-38 days) for patients admitted to the intensive care unit (ICU). Patients who died during hospitalization were older, initially admitted to the ICU, more likely to be white and to have worse organ dysfunction compared to patients who survived their hospitalization. Using the 10 most important variables only, the final model's area under the Receiver Operating Characteristics curve was 0.86 for 7-day, 0.88 for 14-day, and 0.85 for 30-day mortality in the validation cohort. Conclusions: We developed a decision tool that can provide explainable and patient-specific prediction of in-hospital mortality and LOS for COVID-19 positive patients. The model can aid healthcare systems in bed allocation and distribution of vital resources.

Summary Background T cells control viral infection, promote vaccine durability, and in coronavirus disease 2019 (COVID-19) associate with mild disease. We investigated whether prior measles-mumps-rubella (MMR) or tetanus-diphtheria-pertussis (Tdap) vaccination elicits cross-reactive T cells that mitigate COVID-19. Methods Antigen-presenting cells (APC) loaded ex vivo with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), MMR, or Tdap antigens and autologous T cells from COVID-19-convalescent participants, uninfected individuals, and COVID-19 mRNA-vaccinated donors were co-cultured. T cell activation and phenotype were detected by interferon-γ (IFN-γ) enzyme-linked immunospot (ELISpot) assays and flow cytometry. ELISAs (enzyme-linked immunosorbant assays) and validation studies identified the APC-derived cytokine(s) driving T cell activation. TCR clonotyping and single-cell RNA sequencing (scRNA-seq) identified cross-reactive T cells and their transcriptional profile. A propensity-weighted analysis of COVID-19 patients estimated the effects of MMR and Tdap vaccination on COVID-19 outcomes. Findings High correlation was observed between T cell responses to SARS-CoV-2 (spike-S1 and nucleocapsid) and MMR and Tdap proteins in COVID-19-convalescent and -vaccinated individuals. The overlapping T cell population contained an effector memory T cell subset (effector memory re-expressing CD45RA on T cells [TEMRA]) implicated in protective, anti-viral immunity, and their detection required APC-derived IL-15, known to sensitize T cells to activation. Cross-reactive TCR repertoires detected in antigen-experienced T cells recognizing SARS-CoV-2, MMR, and Tdap epitopes had TEMRA features. Indices of disease severity were reduced in MMR- or Tdap-vaccinated individuals by 32%–38% and 20%–23%, respectively, among COVID-19 patients. Conclusions Tdap and MMR memory T cells reactivated by SARS-CoV-2 may provide protection against severe COVID-19. Funding This study was supported by a National Institutes of Health (R01HL065095, R01AI152522, R01NS097719) donation from Barbara and Amos Hostetter and the Chleck Foundation.

This cohort study examines health care utilization patterns for patients with COVID-19 who were enrolled vs not enrolled in a home monitoring program.

Background Dementia-like cognitive impairment is an increasingly reported complication of SARS-CoV-2 infection. However, the underlying mechanisms responsible for this complication remain unclear. A better understanding of causative processes by which COVID-19 may lead to cognitive impairment is essential for developing preventive and therapeutic interventions. Methods In this study, we conducted a network-based, multimodal omics comparison of COVID-19 and neurologic complications. We constructed the SARS-CoV-2 virus-host interactome from protein-protein interaction assay and CRISPR-Cas9-based genetic assay results and compared network-based relationships therein with those of known neurological manifestations using network proximity measures. We also investigated the transcriptomic profiles (including single-cell/nuclei RNA-sequencing) of Alzheimer’s disease (AD) marker genes from patients infected with COVID-19, as well as the prevalence of SARS-CoV-2 entry factors in the brains of AD patients not infected with SARS-CoV-2. Results We found significant network-based relationships between COVID-19 and neuroinflammation and brain microvascular injury pathways and processes which are implicated in AD. We also detected aberrant expression of AD biomarkers in the cerebrospinal fluid and blood of patients with COVID-19. While transcriptomic analyses showed relatively low expression of SARS-CoV-2 entry factors in human brain, neuroinflammatory changes were pronounced. In addition, single-nucleus transcriptomic analyses showed that expression of SARS-CoV-2 host factors (BSG and FURIN) and antiviral defense genes (LY6E, IFITM2, IFITM3, and IFNAR1) was elevated in brain endothelial cells of AD patients and healthy controls relative to neurons and other cell types, suggesting a possible role for brain microvascular injury in COVID-19-mediated cognitive impairment. Overall, individuals with the AD risk allele APOE E4/E4 displayed reduced expression of antiviral defense genes compared to APOE E3/E3 individuals. Conclusion Our results suggest significant mechanistic overlap between AD and COVID-19, centered on neuroinflammation and microvascular injury. These results help improve our understanding of COVID-19-associated neurological manifestations and provide guidance for future development of preventive or treatment interventions, although causal relationship and mechanistic pathways between COVID-19 and AD need future investigations.

Multiple factors influence the outcomes of epilepsy surgery. Prognostic indicators varying from clinical characteristics, imaging findings, ictal, and interictal electrophysiological activity have been linked to surgical outcomes. In this review, we focus on the relatively under‐studied role of the underlying epilepsy histopathology in driving post‐surgical outcomes, specifically focusing on the broad categories of seizure outcomes and cognitive outcomes. For each of these two outcomes of interest, we answer two questions: 1)‐ does etiology matter? and 2)‐ how could it matter? The goal is to review the existing literature on the relationship between etiology and surgical outcomes to provide the best possible judgment as to whether a causal relationship exists between histopathology and the ultimate surgical outcome as an initial step. Then, we delve into the possible mechanisms via which such relationships can be explained. We conclude with a call to action to the epilepsy surgery and histopathology research community to push the mechanistic understanding of the pathology‐outcome interaction and identify actionable knowledge and biomarkers that could inform patient care in a timely fashion., In this review, we focus on the relatively under‐studied role of the underlying epilepsy histopathology in driving post‐surgical outcomes, specifically focusing on the broad categories of seizure outcomes and cognitive outcomes. For each of these two outcomes of interest, we answer two questions: (1) does etiology matter? and (2) how could it matter? We then delve into the mechanisms of these answers.

Background There is concern that the Patient Health Questionnaire-9 (PHQ-9) depression scale may be impacted by the presence of somatic symptoms (differential item functioning (DIF)) in patients with neurological conditions. We evaluated the PHQ-9 for the presence and impact of DIF in large clinical samples of neurological patients. Methods We conducted a cross-sectional study of patients seen at the Cleveland Clinic Cerebrovascular, Headache, Movement Disorder, and Neuromuscular clinics who completed the PHQ-9 and patient-reported disease severity measures as part of standard care between 7/29/2008-2/21/2013. We evaluated PHQ-9 items for DIF with respect to disease-specific severity for each condition. Salient DIF impact was characterized as a difference between DIF-adjusted and unadjusted PHQ-9 scores. Results Included in the study were 2,112 patients with stroke, 8,221 with migraine, 440 with amyotrophic lateral sclerosis (ALS), and 5,022 with Parkinson's disease (PD). Several PHQ-9 items demonstrated DIF with respect to disease-specific severity, although salient DIF was present in very few patients (stroke (n=0); migraine (n=1); ALS (n=13); PD (n=1)). Conclusions PHQ-9 items function consistently across disease severity, with salient levels of DIF impact found only for a very small proportion of people. These results suggest that the PHQ-9 provides a consistent measure of depression severity among people with neurological conditions associated with somatic symptoms that overlap with depression.

Multiple factors affect how health care stakeholders measure success, but at a minimum, clinicians must become more accountable for patient outcomes. While challenges in development and utilization...

BACKGROUND T cells control viral infection and promote vaccine durability and in COVID-19 associate with mild disease. We investigated whether prior Measles-Mumps-Rubella (MMR) or Tetanus-Diptheria-Pertussis (Tdap) vaccination elicit cross-reactive T cells that mitigate COVID-19. METHODS Antigen presenting cells (APC) loaded ex vivo with SARS-CoV-2, MMR or Tdap antigens and autologous T cells from COVID-19 convalescent and uninfected individuals, and COVID-19 mRNA vaccinated donors were co-cultured and T cell activation and phenotype were detected by IFN-γ ELISpot assays and flow cytometry. ELISA assays and validation studies identified the APC-derived cytokine(s) driving T cell activation. TCR clonotyping and scRNA-seq identified cross-reactive T cells and their transcriptional profile. A propensity-weighted analysis of COVID-19 patients estimated the effects of MMR and Tdap vaccination on COVID-19 outcomes. FINDINGS High correlation was observed between T cell responses to SARS-CoV-2 (Spike-S1 and Nucleocapsid) and MMR and Tdap proteins in COVID-19 convalescent and vaccinated individuals. The overlapping T cell population contained an effector memory T cell subset (TEMRA) implicated in protective, anti-viral immunity and their detection required APC-derived IL-15, known to sensitize T cells to activation. Cross-reactive TCR repertoires detected in antigen-experienced T cells recognizing SARS-CoV-2, MMR and Tdap epitopes had TEMRA features. Indices of disease severity were reduced in MMR or Tdap vaccinated individuals by 32-38% and 20-23% respectively, among COVID-19 patients. CONCLUSIONS Tdap and MMR memory T cells reactivated by SARS-CoV-2 may provide protection against severe COVID-19 disease. FUNDING National Institutes of Health (R01HL065095, R01AI152522, R01NS097719), donation from Barbara and Amos Hostetter and the Chleck Foundation., Graphical Abstract, T cells critically control infection and effective vaccination. In COVID-19 convalescent or COVID-19 vaccinated individuals, memory T cells previously generated by MMR or Tdap vaccines are reactivated by SARS-CoV-2 antigens and have features of TEMRA, implicated in anti-viral immunity. Prior MMR or Tdap vaccination may protect against severe COVID-19 disease.

Summary Both mild and severe epilepsies are influenced by variants in the same genes, yet an explanation for the resulting phenotypic variation is unknown. As part of the ongoing Epi25 Collaboration, we performed a whole-exome sequencing analysis of 13,487 epilepsy-affected individuals and 15,678 control individuals. While prior Epi25 studies focused on gene-based collapsing analyses, we asked how the pattern of variation within genes differs by epilepsy type. Specifically, we compared the genetic architectures of severe developmental and epileptic encephalopathies (DEEs) and two generally less severe epilepsies, genetic generalized epilepsy and non-acquired focal epilepsy (NAFE). Our gene-based rare variant collapsing analysis used geographic ancestry-based clustering that included broader ancestries than previously possible and revealed novel associations. Using the missense intolerance ratio (MTR), we found that variants in DEE-affected individuals are in significantly more intolerant genic sub-regions than those in NAFE-affected individuals. Only previously reported pathogenic variants absent in available genomic datasets showed a significant burden in epilepsy-affected individuals compared with control individuals, and the ultra-rare pathogenic variants associated with DEE were located in more intolerant genic sub-regions than variants associated with non-DEE epilepsies. MTR filtering improved the yield of ultra-rare pathogenic variants in affected individuals compared with control individuals. Finally, analysis of variants in genes without a disease association revealed a significant burden of loss-of-function variants in the genes most intolerant to such variation, indicating additional epilepsy-risk genes yet to be discovered. Taken together, our study suggests that genic and sub-genic intolerance are critical characteristics for interpreting the effects of variation in genes that influence epilepsy.

Sex differences in the susceptibility of SARS-CoV-2 infection and severity have been controversial, and the underlying mechanisms of COVID-19 in a sex-specific manner remain understudied. Here we inspected sex differences in SARS-CoV-2 infection, hospitalization, admission to the intensive care unit (ICU), sera inflammatory biomarker profiling, and single-cell RNA-sequencing (scRNA-seq) profiles across nasal, bronchoalveolar lavage fluid (BALF), and peripheral blood mononuclear cells (PBMCs) from COVID-19 patients with varying degrees of disease severities. Our propensity score-matching observations revealed that male individuals have a 29% elevated likelihood of SARS-CoV-2 positivity, with a hazard ratio (HR) 1.32 (95% confidence interval [CI] 1.18–1.48) for hospitalization and HR 1.51 (95% CI 1.24–1.84) for admission to ICU. Sera from male patients at hospital admission had elevated neutrophil–lymphocyte ratio and elevated expression of inflammatory markers (C-reactive protein and procalcitonin). We found that SARS-CoV-2 entry factors, including ACE2, TMPRSS2, FURIN, and NRP1, have elevated expression in nasal squamous cells from male individuals with moderate and severe COVID-19. We observed male-biased transcriptional activation in SARS-CoV-2-infected macrophages from BALF and sputum samples, which offers potential molecular mechanism for sex-biased susceptibility to viral infection. Cell–cell interaction network analysis reveals potential epithelium–immune cell interactions and immune vulnerability underlying male-elevated disease severity and mortality in COVID-19. Mechanistically, monocyte-elevated expression of Toll-like receptor 7 (TLR7) and Bruton tyrosine kinase (BTK) is associated with severe outcomes in males with COVID-19. In summary, these findings provide basis to decipher immune responses underlying sex differences and designing sex-specific targeted interventions and patient care for COVID-19.

Sex differences in the risk of SARS-CoV-2 infection have been controversial and the underlying mechanisms of COVID-19 sexual dimorphism remain understudied. Here we inspected sex differences in SARS-CoV-2 positivity, hospitalization, admission to the intensive care unit (ICU), sera immune profiling, and two single-cell RNA-sequencing (snRNA-seq) profiles from nasal tissues and peripheral blood mononuclear cells (PBMCs) of COVID-19 patients with varying degrees of disease severity. Our propensity score-matching observations revealed that male individuals have a 29% increased likelihood of SARS-CoV-2 positivity, with a hazard ration (HR) 1.32 (95% confidence interval [CI] 1.18-1.48) for hospitalization and HR 1.51 (95% CI 1.24-1.84) for admission to ICU. Sera from male patients at hospital admission had decreased lymphocyte count and elevated inflammatory markers (C-reactive protein, procalcitonin, and neutrophils). We found that SARS-CoV-2 entry factors, including ACE2, TMPRSS2, FURIN and NRP1, have elevated expression in nasal squamous cells from males with moderate and severe COVID-19. Cell-cell network proximity analysis suggests possible epithelium-immune cell interactions and immune vulnerability underlying a higher mortality in males with COVID-19. Monocyte-elevated expression of Toll like receptor 7 (TLR7) and Bruton tyrosine kinase (BTK) is associated with severe outcomes in males with COVID-19. These findings provide basis for understanding immune responses underlying sex differences, and designing sex-specific targeted treatments and patient care for COVID-19.

Highlights • We present a report on continuous EEG (cEEG) findings in COVID-19 patients. • cEEG revealed findings consistent with encephalopathy independent of IV anesthetics. • Acute symptomatic seizures were noted in two patients., Objective As concerns regarding neurological manifestations in COVID-19 (coronavirus disease 2019) patients increase, limited data exists on continuous electroencephalography (cEEG) findings in these patients. We present a retrospective cohort study of cEEG monitoring in COVID-19 patients to better explore this knowledge gap. Methods Among 22 COVID-19 patients, 19 underwent cEEGs, and 3 underwent routine EEGs (

Focal epilepsy (FE) is clinically highly heterogeneous. It has been shown recently that not only rare but also a subset of common genetic variants confer risk for FE. The relatively modest power of genetic studies in FE suggests a high genetic heterogeneity of FE when grouped as one disorder. We hypothesize that the clinical heterogeneity of FE is correlated with genetic heterogeneity on a common risk variant level. To test the hypothesis, we used an FE polygenic risk score "FE-PRS" that combines small effect sizes of thousands of common variants from the largest FE-GWAS (genome-wide association study) into a single measure. We grouped 414 individuals with FE according to common clinical features into subgroups, either by one feature at a time or by all features combined in a cluster analysis. We examined their association with FE-PRS compared to 20 435 matched population controls and observed heterogeneous FE-PRS burden among the subgroups. The highest phenotypic variance explained by FE-PRS was identified in a cluster analysis-defined FE subgroup where all individuals had unknown etiologies and psychiatric comorbidities, and the majority had early onset seizures. Our results indicate that genetic factors associated with FE have differential burden among FE subtypes. Future studies using better-powered FE-PRS might have clinical utility.

Background Coronavirus disease 2019 (COVID-19) is sweeping the globe. Despite multiple case-series, actionable knowledge to tailor decision-making proactively is missing. Research Question Can a statistical model accurately predict infection with COVID-19? Study Design and Methods We developed a prospective registry of all patients tested for COVID-19 in Cleveland Clinic to create individualized risk prediction models. We focus here on the likelihood of a positive nasal or oropharyngeal COVID-19 test. A least absolute shrinkage and selection operator logistic regression algorithm was constructed that removed variables that were not contributing to the model’s cross-validated concordance index. After external validation in a temporally and geographically distinct cohort, the statistical prediction model was illustrated as a nomogram and deployed in an online risk calculator. Results In the development cohort, 11,672 patients fulfilled study criteria, including 818 patients (7.0%) who tested positive for COVID-19; in the validation cohort, 2295 patients fulfilled criteria, including 290 patients who tested positive for COVID-19. Male, African American, older patients, and those with known COVID-19 exposure were at higher risk of being positive for COVID-19. Risk was reduced in those who had pneumococcal polysaccharide or influenza vaccine or who were on melatonin, paroxetine, or carvedilol. Our model had favorable discrimination (c-statistic = 0.863 in the development cohort and 0.840 in the validation cohort) and calibration. We present sensitivity, specificity, negative predictive value, and positive predictive value at different prediction cutoff points. The calculator is freely available at https://riskcalc.org/COVID19 . Interpretation Prediction of a COVID-19 positive test is possible and could help direct health-care resources. We demonstrate relevance of age, race, sex, and socioeconomic characteristics in COVID-19 susceptibility and suggest a potential modifying role of certain common vaccinations and drugs that have been identified in drug-repurposing studies.

Background: Understanding the impact of the COVID-19 pandemic on healthcare workers (HCW) is crucial.Objective: Utilizing a health system COVID-19 research registry, we assessed HCW risk for COVID-19 infection, hospitalization and intensive care unit (ICU) admission.Design: Retrospective cohort study with overlap propensity score weighting.Participants: Individuals tested for SARS-CoV-2 infection in a large academic healthcare system (N=72,909) from March 8-June 9 2020 stratified by HCW and patient-facing status. Main Measures: SARS-CoV-2 test result, hospitalization, and ICU admission for COVID-19 infection. Key Results: Of 72,909 individuals tested, 9.0% (551) of 6,145 HCW tested positive for SARS-CoV-2 compared to 6.5% (4353) of 66,764 non-HCW. The HCW were younger than non-HCW (median age 39.7 vs. 57.5, pConclusions: In a large healthcare system, HCW had similar odds for testing SARS-CoV-2 positive, but lower odds of hospitalization compared to non-HCW. Patient-facing HCW had higher odds of a positive test. These results are key to understanding HCW risk mitigation during the COVID-19 pandemic.

Significant technological advances have improved our ability to localize epilepsy and investigate the electrophysiology in patients undergoing preparation for epilepsy surgery. Conversely, our process of decision-making and outcome prediction has remained essentially restricted to subjective clinical judgment. This may have hindered our ability to improve outcomes. In this review, we highlight the cognitive biases that interfere with medical decision-making and present data on the use of algorithms and statistical models in general health care, before pivoting to discuss applications in the context of epilepsy.

Background Stereoelectroencephalography (SEEG) is used to identify the epileptogenic zone (EZ) in patients with epilepsy for potential surgical intervention. Occasionally, the EZ is difficult to localize even after an SEEG implantation. Objective To demonstrate a safe technique for placing additional electrodes in ongoing SEEG evaluations. Describe efficacy, complications, and surgical outcomes. Methods An operative technique which involves maintaining previously placed electrodes and sterilely placing new electrodes was developed and implemented. All patients who underwent placement of additional SEEG electrodes during the same admission were retrospectively reviewed. Results A total of 14 patients met criteria and had undergone SEEG evaluation with 198 electrodes implanted. A total 93% of patients (13/14) had nonlesional epilepsy. After unsuccessful localization of the EZ after a mean of 9.6 d of monitoring, each patient underwent additional placement of electrodes (5.5 average electrodes per patient) to augment the original implantation. At no point did any patients develop new hemorrhage, infection, wound breakdown, or require any kind of additional antimicrobial treatment. A total 64% (9/14) of patients were able to undergo surgery aimed at removing the EZ guided by the additional SEEG electrodes. A total 44% (4/9) of surgical patients had Engel class I outcomes at an average follow-up time of 11 mo. Conclusion Placing additional SEEG electrodes, while maintaining the previously placed electrodes, appears to be safe, effective, and had no infectious complications. When confronted with difficult-to-localize epilepsy even after invasive monitoring, it appears to be safe and potentially clinically effective to place additional electrodes during the same admission.