Neuropsychiatric complications of coronavirus disease 2019: Mount Sinai Health System cohort study.

OBJECTIVE: To describe the frequency of neuropsychiatric complications among hospitalized patients with coronavirus disease 2019 (COVID-19) and their association with pre-existing comorbidities and clinical outcomes. METHODS: We retrospectively identified all patients hospitalized with COVID-19 within a large multicenter New York City health system between March 15, 2020 and May 17, 2021 and randomly selected a representative cohort for detailed chart review. Clinical data, including the occurrence of neuropsychiatric complications (categorized as either altered mental status [AMS] or other neuropsychiatric complications) and in-hospital mortality, were extracted using an electronic medical record database and individual chart review. Associations between neuropsychiatric complications, comorbidities, laboratory findings, and in-hospital mortality were assessed using multivariate logistic regression. RESULTS: Our study cohort consisted of 974 patients, the majority were admitted during the first wave of the pandemic. Patients were treated with anticoagulation (88.4%), glucocorticoids (24.8%), and remdesivir (10.5%); 18.6% experienced severe COVID-19 pneumonia (evidenced by ventilator requirement). Neuropsychiatric complications occurred in 58.8% of patients; 39.8% experienced AMS; and 19.0% experienced at least one other complication (seizures in 1.4%, ischemic stroke in 1.6%, hemorrhagic stroke in 1.0%) or symptom (headache in 11.4%, anxiety in 6.8%, ataxia in 6.3%). Higher odds of mortality, which occurred in 22.0%, were associated with AMS, ventilator support, increasing age, and higher serum inflammatory marker levels. Anticoagulant therapy was associated with lower odds of mortality and AMS. CONCLUSION: Neuropsychiatric complications of COVID-19, especially AMS, were common, varied, and associated with in-hospital mortality in a diverse multicenter cohort at an epicenter of the COVID-19 pandemic.

Disparities in Teleneurology Use in Medicaid Beneficiaries With Epilepsy by Practice Setting: Promoting Health Equity in Academic Centers.

BACKGROUND AND OBJECTIVES: Medicaid beneficiaries in many American academic medical centers can receive care in a separate facility than those not covered by Medicaid. We aimed to identify possible disparities in care by evaluating the association between facility type (integrated faculty practice or Medicaid-only outpatient clinic) and telehealth utilization in people with epilepsy. METHODS: We performed retrospective analyses using structured data from the Mount Sinai Health System electronic medical record data from January 2003 to August 2021. We identified people of all ages with epilepsy who were followed by an epileptologist after January 3, 2018, using a validated ICD-9-CM/10-CM coded case definition. We evaluated associations between practice setting and telehealth utilization, an outcome measure that captures the evolving delivery of neurologic care in a post-coronavirus disease 2019 era, using multivariable logistic regression. RESULTS: We identified 4,586 people with epilepsy seen by an epileptologist, including Medicaid beneficiaries in the Medicaid outpatient clinic (N = 387), Medicaid beneficiaries in the faculty practice after integration (N = 723), and non-Medicaid beneficiaries (N = 3,476). Patients not insured by Medicaid were significantly older (average age 40 years vs 29 in persons seen in Medicaid-only outpatient clinic and 28.5 in persons insured with Medicaid seen in faculty practice [p < 0.0001]). Medicaid beneficiaries were more likely to have drug-resistant epilepsy (DRE), with 51.94% of people seen in Medicaid-only outpatient clinic, 41.63% of Medicaid beneficiaries seen in faculty practice, and 37.2% of non-Medicaid beneficiaries having DRE (p < 0.0001). Medicaid outpatient clinic patients were less likely to have telehealth visits (phone or video); 81.65% of patients in the Medicaid outpatient clinic having no telehealth visits vs 71.78% of Medicaid beneficiaries in the faculty practice and 70.89% of non-Medicaid beneficiaries (p < 0.0001). In an adjusted logistic regression analysis, Medicaid beneficiaries had lower odds (0.61; 95% CI 0.46-0.81) of using teleneurology compared with all patients seen in faculty practice (p = 0.0005). DISCUSSION: Compared with the Medicaid-only outpatient clinic, we found higher telehealth utilization in the integrated faculty practice with no difference by insurance status (Medicaid vs other). Integrated care may be associated with better health care delivery in people with epilepsy; thus, future research should examine its impact on other epilepsy-related outcomes.

Germline Testing identifies Pathogenic/Likely Pathogenic Variants in Patients with Pancreatic Neuroendocrine Tumors.

10% of pancreatic neuroendocrine tumors (pNETs) are related to inherited syndromes (MEN1, MEN4, VHL, NF1, TSC). Growing evidence suggests that clinically sporadic pNETs can also harbor germline pathogenic variants. In this study, we report the prevalence of pathological/likely pathological germline variants (P/LP) in a high-risk cohort and an unselected cohort. We collected clinical data of patients with pNETs seen at MD Anderson Cancer Center (MDACC) and Johns Hopkins Hospital (JHH). High-risk cohort included (n=132) patients seen at MDACC who underwent germline testing for high-risk criteria (early onset, personal or family history of cancer and syndromic features) between 2013-2019. Unselected cohort (n=106) patients seen at JHH who underwent germline testing following their diagnosis of pNETs between 2020 to 2022. In the high-risk cohort (n=132), 33% (n=44) had P/LP variants. The majority of the patients had P/LP variants in MEN1 56% (n=25), followed by DNA repair pathways 18% (n=8), and 7 %(n=3) in MSH2 (Lynch Syndrome). Patients with P/LP were younger (45 years vs 50 years; p=0.002). In the unselected cohort (n=106), 21% (n=22) had P/LP. The majority were noted in DNA repair pathways 40% (n=9) and MEN1 36% (n=8). Multifocal tumors correlated with the presence of P/LP (p=0.0035). MEN1 germline P/LP variants correlated with younger age (40 vs 56 years) (p=0.0012). presence of multifocal tumors (p<0.0001), and WHO grade 1 histology (p=0.0078). P/LP variants are prevalent in patients with clinically sporadic pNET irrespective of high-risk features. The findings support upfront universal germline testing in all pNET patients.

Descriptive Analysis of Patients Receiving Outpatient eConsults for Neurological Disorders in the United States.

Introduction: Interprofessional consultations ("eConsults"), which facilitate asynchronous specialist consultations, remain understudied in neurological disorders. We aimed to describe the patient population receiving eConsult services for neurological disorders nationwide and to conduct a comparative analysis between rural and urban patients within this eConsult cohort. Methods: We analyzed a dataset of U.S. outpatient claims from employer-sponsored commercial and Medicare plans. Using standardized mean differences, we compared clinical and sociodemographic patient characteristics between urban and rural patients within the eConsult group. Results: We identified 1,374 patients who had an eConsult order for a neurological disorder. Overall eConsult volume increased by 548.5% between 2019 and 2021. A majority of the cohort were aged 65 years or older (23.7%), had an eConsult order in 2021 (52.4%), and live in an urban area (90.4%). The primary diagnosis for our cohort was likely to be a sleep-wake disorder (21.9%), cerebrovascular disease (14.3%), neurological sign or symptom (14.2%), or headache (13.7%). In the secondary analysis, rural eConsult patients exhibited higher rates of primary diagnoses for traumatic brain injury, neuroophthalmic disorders, or neuropathy than their urban counterparts. Discussion: In this national sample of commercially insured patients, the utilization of eConsults for neurological conditions increased nationwide since 2019, especially for patients living in rural areas.

Provider Experience With the Use of Ketamine for Refractory Status Epilepticus.

OBJECTIVE: Refractory status epilepticus (RSE) treated with anesthetic agents can be associated with complications including respiratory depression and hypotension. Ketamine is an emerging RSE treatment, but optimal dosing and timing are unknown. We studied provider attitudes and practices regarding the use of ketamine for RSE. METHODS: A literature review informed the creation of the survey, developed by professionals in epilepsy, pharmacy, and neurocritical care. The survey was distributed to members of the Critical Care EEG Monitoring and Research Consortium, Neurocritical Care Society, American Academy of Neurology Synapse community, American Epilepsy Society, and the Canadian League Against Epilepsy. Descriptive statistics were calculated. RESULTS: There were 109 respondents. First-line agents for RSE were midazolam (53%), propofol (42%), pentobarbital (2%), and ketamine (1%). Reasons for ketamine use included failure of midazolam/propofol to control seizures (81%) or hypotension on another anesthetic (35%). Perceived contraindications included hypertension (37%), elevated intracranial pressure (24%), and heart failure (18%). Perceived benefits included decreased use of vasopressors (53%) and more rapid RSE control when used adjunctively (49%). Routine ketamine users often treated more than 10 RSE cases per year, worked as intensivists or at academic institutions. Of the respondents, 59% found ketamine useful for RSE and 94% were interested in learning more about its use. CONCLUSIONS: Although most participants found ketamine helpful for RSE, it is mainly used as a second-line agent adjunctively with midazolam or propofol. Perceived ketamine benefits included decreased need for hemodynamic support and more rapid seizure control when used in conjunction with other anesthetics. Perceived contraindications centered on cardiac and intracranial pressure concerns.

Pilot Study of a Mobile Phone Chatbot for Medication Adherence and Toxicity Management Among Patients With GI Cancers on Capecitabine.

PURPOSE: Capecitabine is an oral chemotherapy used to treat many gastrointestinal cancers. Its complex dosing and narrow therapeutic index make medication adherence and toxicity management crucial for quality care. METHODS: We conducted a pilot study of PENNY-GI, a mobile phone text messaging-based chatbot that leverages algorithmic surveys and natural language processing to promote medication adherence and toxicity management among patients with gastrointestinal cancers on capecitabine. Eligibility initially included all capecitabine-containing regimens but was subsequently restricted to capecitabine monotherapy because of challenges in integrating PENNY-GI with radiation and intravenous chemotherapy schedules. We used design thinking principles and real-time data on safety, accuracy, and usefulness to make iterative refinements to PENNY-GI with the goal of minimizing the proportion of text messaging exchanges with incorrect medication or symptom management recommendations. All patients were invited to participate in structured exit interviews to provide feedback on PENNY-GI. RESULTS: We enrolled 40 patients (median age 64.5 years, 52.5% male, 62.5% White, 55.0% with colorectal cancer, 50.0% on capecitabine monotherapy). We identified 284 of 3,895 (7.3%) medication-related and 13 of 527 (2.5%) symptom-related text messaging exchanges with incorrect recommendations. In exit interviews with 24 patients, participants reported finding the medication reminders reliable and user-friendly, but the symptom management tool was too simplistic to be helpful. CONCLUSION: Although PENNY-GI provided accurate recommendations in >90% of text messaging exchanges, we identified multiple limitations with respect to the intervention's generalizability, usefulness, and scalability. Lessons from this pilot study should inform future efforts to develop and implement digital health interventions in oncology.

Older adults with epilepsy and COVID-19: Outcomes in a multi-hospital health system.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is associated with high rates of mortality and morbidity in older adults, especially those with pre-existing conditions. There is little work investigating how neurological conditions affect older adults with COVID-19. We aimed to compare in-hospital outcomes, including mortality, in older adults with and without epilepsy. METHODS: This retrospective study in a large multicenter New York health system included consecutive older patients (age ≥65 years) either with or without epilepsy who were admitted with COVID-19 between 3/2020-5/2021. Epilepsy was identified using a validated International Classification of Disease (ICD) and antiseizure medicationbased case definition. Univariate comparisons were calculated using Chi-square, Fisher's exact, Mann-Whitney U, or Student's t-tests. Multivariable logistic regression models were generated to examine factors associated with mortality, discharge disposition and length of stay (LOS). RESULTS: We identified 5384 older adults admitted with COVID-19 of whom 173 (3.21 %) had epilepsy. Mean age was significantly lower in those with (75.44, standard deviation (SD): 7.23) compared to those without epilepsy (77.98, SD: 8.68, p = 0.007). Older adults with epilepsy were more likely to be ventilated (35.84 % vs. 16.18 %, p < 0.001), less likely to be discharged home (21.39 % vs. 43.12 %, p < 0.001), had longer median LOS (13 days vs. 8 days, p < 0.001), and had higher in-hospital death (35.84 % vs. 28.29 %, p = 0.030) compared to those without epilepsy. Epilepsy in older adults was associated with increased odds of in-hospital death (adjusted odds ratio (aOR), 1.55; 95 % CI 1.12-2.14, p = 0.032), non-routine discharge disposition (aOR, 3.34; 95 % CI 2.21-5.03, p < 0.001), and longer LOS (46.46 % 95 % CI 34 %-59 %, p < 0.001). CONCLUSIONS: In models that adjusted for multiple confounders including comorbidity and age, our study found that epilepsy was still associated with higher in-hospital mortality, longer LOS and worse discharge dispositions in older adults with COVID-19 higher in-hospital mortality, longer LOS and worse discharge dispositions in older adults with COVID-19. This work reinforces that epilepsy is a risk factor for worse outcomes in older adults admitted with COVID-19. Timely identification and treatment of COVID-19 in epilepsy may improve outcomes in older people with epilepsy.

Immunotherapy of MSI Cancer: Facts and Hopes.

Microsatellite instability (MSI) is a tumor molecular phenotype that evolves from loss of function in the mismatch repair (MMR) proteins through deleterious germline mutations, epigenetic inactivation, or somatic biallelic mutations. This phenotype is characterized by genomic hyper-mutability, increased neoantigen expression, and a favorable, immune-rich tumor microenvironment. These features confer a greater likelihood of response to treatment with the class of agents known as immune checkpoint inhibitors (ICI) and, potentially, other immune-based therapeutics. MSI as a predictive biomarker for response to treatment with ICIs ultimately led to the first tissue-agnostic approval of pembrolizumab for advanced, previously treated MSI or deficient MMR (dMMR) tumors. Nevertheless, response to ICIs in dMMR/MSI tumors is not universal. Identifying predictors of response and elucidating mechanisms of immune escape will be crucial to continued successful treatment of this subset. In this review, we aim to describe the pathogenesis and key immunologic features of dMMR/MSI tumors, provide a brief overview of the currently approved treatments, and discuss promising novel immune-based therapeutics currently under investigation.

Healthcare utilization impacts of an eConsult program for headache at an academic medical center.

INTRODUCTION: Interprofessional consultations ("eConsults") can reduce healthcare utilization. However, the impact of eConsults on healthcare utilization remains poorly characterized among patients with headache. METHODS: We performed a retrospective, 1:1 matched cohort study comparing patients evaluated for headache via eConsult request or in-person referral at the Mount Sinai Health System in New York. Groups were matched on clinical and demographic characteristics. Our primary outcome was one or more outpatient headache-related encounters in 6 months following referral date. Secondary outcomes included one or more all-cause outpatient neurology and headache-related emergency department (ED) encounters during the same period. We used univariable and multivariable logistic regression to model associations between independent variables and outcomes. RESULTS: We identified 74 patients with headache eConsults who were matched to 74 patients with in-person referrals. Patients in the eConsult group were less likely to achieve the primary outcome (29.7% vs 62.2%, P < 0.0001) or have an all-cause outpatient neurology encounter (33.8% vs 79.7%, P < 0.0001) than patients in the comparison group. Both groups did not significantly differ by headache-related ED encounters. In multivariable analyses, patients in the eConsult group had significantly lower odds of having one or more headache-related or all-cause neurology encounters than patients in the comparison group (odds ratio (OR) 0.3, 95% confidence interval (CI) 0.1-0.6; OR 0.1, 95% CI 0.1-0.3, respectively). DISCUSSION: In comparison to in-person referrals, eConsult requests for headache were associated with reduced likelihood of outpatient neurology encounters in the short-term but not with differential use of headache-related ED encounters. Larger-scale, prospective studies should validate our findings and assess patient outcomes.

Health equity integrated epilepsy care and research: A narrative review.

BACKGROUND: With the unanimous approval of the Intersectoral Global Action Plan on epilepsy and other neurological disorders by the World Health Organization in May 2022, there are strong imperatives to work towards equitable neurological care. AIMS: Using epilepsy as an entry point to other neurologic conditions, we discuss disparities faced by marginalized groups including racial/ethnic minorities, Americans living in rural communities, and Americans with low socioeconomic status. MATERIALS AND METHODS: The National Institute on Minority Health Disparities Research Framework (NIMHD) was used to conduct a narrative review through a health equity lens to create an adapted framework for epilepsy and propose approaches to working towards equitable epilepsy and neurological care. RESULTS: In this narrative review, we identified priority populations (racial and ethnic minority, rural-residing, and low socioeconomic status persons with epilepsy) and outcomes (likelihood to see a neurologist, be prescribed antiseizure medications, undergo epilepsy surgery, and be hospitalized) to explore disparities in epilepsy and guide our focused literature search using PubMed. In an adapted NIMHD framework, we examined individual, interpersonal, community, and societal level contributors to health disparities across five domains: (1) behavioral, (2) physical/built environment, (3) sociocultural, (4) environment, and (5) healthcare system. We take a health equity approach to propose initiatives that target modifiable factors that impact disparities and advocate for sustainable change for priority populations. DISCUSSION: To improve equity, healthcare providers and relevant societal stakeholders can advocate for improved care coordination, referrals for epilepsy surgery, access to care, health informatics interventions, and education (i.e., to providers, patients, and communities). More broadly, stakeholders can advocate for reforms in medical education, and in the American health insurance landscape. CONCLUSIONS: Equitable healthcare should be a priority in neurological care.

In-hospital outcomes in patients with and without epilepsy diagnosed with COVID-19-A cohort study.

OBJECTIVES: Coronavirus disease 2019 (COVID-19) is associated with mortality in persons with comorbidities. The aim of this study was to evaluate in-hospital outcomes in patients with COVID-19 with and without epilepsy. METHODS: We conducted a retrospective study of patients with COVID-19 admitted to a multicenter health system between March 15, 2020, and May 17, 2021. Patients with epilepsy were identified using a validated International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)/ICD-10-CM case definition. Logistic regression models and Kaplan-Meier analyses were conducted for mortality and non-routine discharges (i.e., not discharged home). An ordinary least-squares regression model was fitted for length of stay (LOS). RESULTS: We identified 9833 people with COVID-19 including 334 with epilepsy. On univariate analysis, people with epilepsy had significantly higher ventilator use (37.70% vs 14.30%, p < .001), intensive care unit (ICU) admissions (39.20% vs 17.70%, p < .001) mortality rate (29.60% vs 19.90%, p < .001), and longer LOS (12 days vs 7 days, p < .001). and fewer were discharged home (29.64% vs 57.37%, p < .001). On multivariate analysis, only non-routine discharge (adjusted odds ratio [aOR] 2.70, 95% confidence interval [CI] 2.00-3.70; p < .001) and LOS (32.50% longer, 95% CI 22.20%-43.60%; p < .001) were significantly different. Factors associated with higher odds of mortality in epilepsy were older age (aOR 1.05, 95% CI 1.03-1.08; p < .001), ventilator support (aOR 7.18, 95% CI 3.12-16.48; p < .001), and higher Charlson comorbidity index (CCI) (aOR 1.18, 95% CI 1.04-1.34; p = .010). In epilepsy, admissions between August and December 2020 or January and May 2021 were associated with a lower odds of non-routine discharge and decreased LOS compared to admissions between March and July 2020, but this difference was not statistically significant. SIGNIFICANCE: People with COVID-19 who had epilepsy had a higher odds of non-routine discharge and longer LOS but not higher mortality. Older age (≥65), ventilator use, and higher CCI were associated with COVID-19 mortality in epilepsy. This suggests that older adults with epilepsy and multimorbidity are more vulnerable than those without and should be monitored closely in the setting of COVID-19.

Association of first anti-seizure medication choice with injuries in older adults with newly diagnosed epilepsy.

BACKGROUND: Epilepsy incidence increases exponentially in older adults, who are also at higher risk of adverse drug effects. Anti-seizure medications (ASM) may be associated with sedation and injuries, but discontinuation can result in seizures. We sought to determine whether there was an association between prescribing non-guideline concordant ASM and subsequent injury as this could inform care models. METHODS: Retrospective cohort study of adults 50 years or older with newly-diagnosed epilepsy in 2015-16, sampled from the MarketScan Databases. The outcome of interest was injury within 1-year of ASM prescription (e.g., burns, falls) and the exposure of interest was ASM category (recommended vs. not recommended by clinical guidelines). Descriptive statistics characterized covariates and a multivariable Cox-regression model was built to examine the association between ASM category and subsequent injury. RESULTS: 5,931 people with newly diagnosed epilepsy were prescribed an ASM within 1-year. The three most common ASMs were: levetiracetam (62.86%), gabapentin (11.73%), and phenytoin (4.45%). Multivariable Cox-regression found that medication category was not associated with injury; however, older age (adjusted hazard ratio (AHR) 1.01/year), history of prior injury (AHR 1.77), traumatic brain injury (AHR 1.55) and ASM polypharmacy (AHR 1.32) were associated with increased hazard of injury. CONCLUSIONS: Most older adults appear to be getting appropriate first prescriptions for epilepsy. However, a substantial proportion still receives medication that guidelines suggest avoiding. In addition, we show that ASM polypharmacy is associated with an increased hazard of injury within 1- year. Efforts to improve prescribing in older adults with epilepsy should consider how to reduce. both polypharmacy and exposure to medications that guidelines recommend avoiding.

Palliative care referral across the disease trajectory in high-grade glioma.

PURPOSE: Adults with high-grade glioma (HGG), WHO grade III or IV, have substantial palliative care needs. Our aim was to determine occurrence, timing, and factors associated with palliative care consultation (PCC) in HGG at one large academic institution. METHODS: HGG patients receiving care between 08/1/2011 and 01/23/2020 were identified retrospectively from a multi-center healthcare system cancer registry. Patients were stratified by any PCC (yes/no), and timing of initial PCC by disease phase: diagnosis (before radiation), during initial treatment (first-line chemotherapy/radiation), second-line treatment(s), or end-of-life (after last chemotherapy). RESULTS: Of 621 HGG patients, 134 (21.58%) received PCC with the vast majority occurring during hospital admission [111 (82.84%)]. Of the 134, 14 (10.45%) were referred during the diagnostic phase; 35 (26.12%) during initial treatment; 20 (14.93%) during second-line treatment; and 65 (48.51%) during end of life. In multivariable logistic regression, only higher Charlson Comorbidity Index was associated with greater odds of PCC [OR 1.3 (95% CI 1.2-1.4), p < 0.01]; but not age or histopathology. Patients who received PCC prior to end of life had longer survival from diagnosis than those referred during end of life [16.5 (8, 24) months vs. 11 (4, 17); p < 0.01]. CONCLUSION: A minority of HGG patients ever received PCC, which primarily occurred in the inpatient setting, and nearly half during the end-of-life phase. Thus, only about one in ten patients in the entire cohort potentially received the benefits of earlier PCC despite earlier referral having an association with longer survival. Further studies should elucidate barriers and facilitators to early PCC in HGG.

Cancer beliefs and screening behaviors: The impact of neighborhood and other social determinants of health.

Background: Beliefs about cancer influence breast and colorectal cancer (CRC) screening behavior. Screening rates for these cancers differ in the contiguous neighborhoods of East Harlem (EH), Central Harlem (CH), and the Upper East Side (UES), which have distinct socio-demographic compositions. We assessed the belief-screening behavior relationship in these neighborhoods. Methods: The 2019 Community Cancer Needs Survey included adults eligible for breast and/or colorectal cancer screening. Raking was used to generate neighborhood-specific distribution estimates. Categorical variables were compared using Chi-square tests. Stepwise logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between cancer beliefs and screening. Results: Our weighted sample included 147,726 respondents. Screening was 75% in CH, 81% in EH, and 90% in the UES for breast cancer, and 71%, 76%, and 92% for CRC, respectively. The fatalistic belief "There's not much you can do to lower your chances of getting cancer" differed by neighborhood with screening more likely in CH respondents (breast OR =1.45 and colorectal OR =1.11), but less likely in EH (OR= 0.77 and 0.37, respectively). UES ORs were not generated due to too few unscreened respondents. Conclusions: Cancer beliefs were inconsistently associated with breast and CRC screening across three NYC neighborhoods. This suggests that a given belief may either motivate or deter screening, depending upon context or interpretation. Once access is addressed, efforts seeking to enhance screening rates should consider implications of communities' varying beliefs.

Deep Neural Network for EEG Signal-Based Subject-Independent Imaginary Mental Task Classification.

BACKGROUND: Mental task identification using electroencephalography (EEG) signals is required for patients with limited or no motor movements. A subject-independent mental task classification framework can be applied to identify the mental task of a subject with no available training statistics. Deep learning frameworks are popular among researchers for analyzing both spatial and time series data, making them well-suited for classifying EEG signals. METHOD: In this paper, a deep neural network model is proposed for mental task classification for an imagined task from EEG signal data. Pre-computed features of EEG signals were obtained after raw EEG signals acquired from the subjects were spatially filtered by applying the Laplacian surface. To handle high-dimensional data, principal component analysis (PCA) was performed which helps in the extraction of most discriminating features from input vectors. RESULT: The proposed model is non-invasive and aims to extract mental task-specific features from EEG data acquired from a particular subject. The training was performed on the average combined Power Spectrum Density (PSD) values of all but one subject. The performance of the proposed model based on a deep neural network (DNN) was evaluated using a benchmark dataset. We achieved 77.62% accuracy. CONCLUSION: The performance and comparison analysis with the related existing works validated that the proposed cross-subject classification framework outperforms the state-of-the-art algorithm in terms of performing an accurate mental task from EEG signals.

Priming locomotor training with transspinal stimulation in people with spinal cord injury: study protocol of a randomized clinical trial.

BACKGROUND: The seemingly simple tasks of standing and walking require continuous integration of complex spinal reflex circuits between descending motor commands and ascending sensory inputs. Spinal cord injury greatly impairs standing and walking ability, but both improve with locomotor training. However, even after multiple locomotor training sessions, abnormal muscle activity and coordination persist. Thus, locomotor training alone cannot fully optimize the neuronal plasticity required to strengthen the synapses connecting the brain, spinal cord, and local circuits and potentiate neuronal activity based on need. Transcutaneous spinal cord (transspinal) stimulation alters motoneuron excitability over multiple segments by bringing motoneurons closer to threshold, a prerequisite for effectively promoting spinal locomotor network neuromodulation and strengthening neural connectivity of the injured human spinal cord. Importantly, whether concurrent treatment with transspinal stimulation and locomotor training maximizes motor recovery after spinal cord injury is unknown. METHODS: Forty-five individuals with chronic spinal cord injury are receiving 40 sessions of robotic gait training primed with 30 Hz transspinal stimulation at the Thoracic 10 vertebral level. Participants are randomized to receive 30 min of active or sham transspinal stimulation during standing or active transspinal stimulation while supine followed by 30 min of robotic gait training. Over the course of locomotor training, the body weight support, treadmill speed, and leg guidance force are adjusted as needed for each participant based on absence of knee buckling during the stance phase and toe dragging during the swing phase. At baseline and after completion of all therapeutic sessions, neurophysiological recordings registering corticospinal and spinal neural excitability changes along with clinical assessment measures of standing and walking, and autonomic function via questionnaires regarding bowel, bladder, and sexual function are taken. DISCUSSION: The results of this mechanistic randomized clinical trial will demonstrate that tonic transspinal stimulation strengthens corticomotoneuronal connectivity and dynamic neuromodulation through posture-dependent corticospinal and spinal neuroplasticity. We anticipate that this mechanistic clinical trial will greatly impact clinical practice because, in real-world clinical settings, noninvasive transspinal stimulation can be more easily and widely implemented than invasive epidural stimulation. Additionally, by applying multiple interventions to accelerate motor recovery, we are employing a treatment regimen that reflects a true clinical approach. TRIAL REGISTRATION: ClinicalTrials.gov NCT04807764 . Registered on March 19, 2021.

Latent class analysis of eHealth behaviors among adults with epilepsy.

OBJECTIVE: The objective of this study was to determine the proportions of uptake and factors associated with electronic health (eHealth) behaviors among adults with epilepsy. METHODS: The 2013, 2015, and 2017 National Health Interview Surveys were analyzed. We assessed the proportions of use of five domains of eHealth in those with epilepsy: looked up health information on the internet, filled a prescription on the internet, scheduled a medical appointment on the internet, communicated with a health care provider via email, and used chat groups to learn about health topics. Multivariate logistic regressions were conducted to identify factors associated with any eHealth behaviors among those with active epilepsy. Latent class analysis was performed to identify underlying patterns of eHealth activity. Survey participants were classified into three discrete classes: (1) frequent, (2) infrequent, and (3) nonusers of eHealth. Multinomial logistic regression was performed to identify factors associated with frequency of eHealth use. RESULTS: There were 1770 adults with epilepsy, of whom 65.87% had at least one eHealth behavior in the prior year. By domain, 62.61% looked up health information on the internet, 15.81% filled a prescription on the internet, 14.95% scheduled a medical appointment on the internet, 17.20% communicated with a health care provider via email, and 8.27% used chat groups to learn about health topics. Among those with active epilepsy, female sex, more frequent computer usage, and internet usage were associated with any eHealth behavior. Female sex and frequent computer use were associated with frequent eHealth use as compared to nonusers. SIGNIFICANCE: A majority of persons with epilepsy were found to use at least one form of eHealth. Various technological and demographic factors were associated with eHealth behaviors. Individuals with lower eHealth behaviors should be provided with targeted interventions that address barriers to the adoption of these technologies.