Faculty Bibliography

IMPORTANCE/UNASSIGNED:Neurological manifestations during acute SARS-CoV-2-related multisystem inflammatory syndrome in children (MIS-C) are common in hospitalized patients younger than 18 years and may increase risk of new neurocognitive or functional morbidity. OBJECTIVE/UNASSIGNED:To assess the association of severe neurological manifestations during a SARS-CoV-2-related hospital admission with new neurocognitive or functional morbidities at discharge. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This prospective cohort study from 46 centers in 10 countries included patients younger than 18 years who were hospitalized for acute SARS-CoV-2 or MIS-C between January 2, 2020, and July 31, 2021. EXPOSURE/UNASSIGNED:Severe neurological manifestations, which included acute encephalopathy, seizures or status epilepticus, meningitis or encephalitis, sympathetic storming or dysautonomia, cardiac arrest, coma, delirium, and stroke. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcome was new neurocognitive (based on the Pediatric Cerebral Performance Category scale) and/or functional (based on the Functional Status Scale) morbidity at hospital discharge. Multivariable logistic regression analyses were performed to examine the association of severe neurological manifestations with new morbidity in each SARS-CoV-2-related condition. RESULTS/UNASSIGNED:Overall, 3568 patients younger than 18 years (median age, 8 years [IQR, 1-14 years]; 54.3% male) were included in this study. Most (2980 [83.5%]) had acute SARS-CoV-2; the remainder (588 [16.5%]) had MIS-C. Among the patients with acute SARS-CoV-2, 536 (18.0%) had a severe neurological manifestation during hospitalization, as did 146 patients with MIS-C (24.8%). Among survivors with acute SARS-CoV-2, those with severe neurological manifestations were more likely to have new neurocognitive or functional morbidity at hospital discharge compared with those without severe neurological manifestations (27.7% [n = 142] vs 14.6% [n = 356]; P < .001). For survivors with MIS-C, 28.0% (n = 39) with severe neurological manifestations had new neurocognitive and/or functional morbidity at hospital discharge compared with 15.5% (n = 68) of those without severe neurological manifestations (P = .002). When adjusting for risk factors in those with severe neurological manifestations, both patients with acute SARS-CoV-2 (odds ratio, 1.85 [95% CI, 1.27-2.70]; P = .001) and those with MIS-C (odds ratio, 2.18 [95% CI, 1.22-3.89]; P = .009) had higher odds of having new neurocognitive and/or functional morbidity at hospital discharge. CONCLUSIONS AND RELEVANCE/UNASSIGNED:The results of this study suggest that children and adolescents with acute SARS-CoV-2 or MIS-C and severe neurological manifestations may be at high risk for long-term impairment and may benefit from screening and early intervention to assist recovery.

AIM AND RATIONALE/UNASSIGNED:Problems with manual dexterity and cognition impact the everyday performance of people with multiple sclerosis (PwMS). Accumulated findings point to the relationship between deficits in manual dexterity and auditory domains of cognition with a lack of evidence on visuospatial and verbal aspects of cognitive functioning. Therefore, this study explores the relationship between manual dexterity and cognition in a cohort of PwMS. METHOD/METHODS:This cross-sectional study collected data from 63 PwMS aged 22 to 55 through a convenient sampling method. Participants were diagnosed with relapsing-remitting multiple sclerosis (RRMS). Cognition was measured using a multi-domain computerized cognitive testing, NeuroTrax, and manual dexterity was measured using a 9-hole peg assessment. Spearman correlation was used to identify the correlation among cognition subtests as well as with manual dexterity. Linear regression analysis was also conducted to identify whether manual dexterity predicts cognitive functioning. RESULTS:= 0.165, p = 0.001. CONCLUSION/CONCLUSIONS:Manual dexterity was found to not only predict cognitive dysfunction but was also associated with multiple cognitive domains. Understanding the relationship between manual dexterity and cognition and the inferred progression of deficits can assist clinicians to provide interventions at earlier stages of disease progression to potentially increase daily functioning and quality of life (QoL).

INTRODUCTION/BACKGROUND:Switching disease-modifying therapy (DMT) may be considered for relapsing-remitting multiple sclerosis (RRMS) if a patient's current therapy is no longer optimal. This was particularly important during the recent COVID-19 pandemic because of considerations around immune deficiency and impaired vaccine response associated with B cell-depleting DMTs. This real-world, single-center study aimed to evaluate change or decline in functional ability and overall disease stability in people with RRMS who were switched from B cell-depleting ocrelizumab (OCRE) to diroximel fumarate (DRF) because of safety concern related to the COVID-19 pandemic. METHODS:Adults with RRMS were included if they had been clinically stable for ≥ 1 year on OCRE. Data collected at baseline and 1 year post switch included relapse rate, magnetic resonance imaging (MRI), blood work for assessment of peripheral immune parameters, the Cognitive Assessment Battery (CAB), optical coherence tomography (OCT), and patient-reported outcomes (PROs). RESULTS:cells 1 year after switching (p < 0.05). Similarly, there were no significant changes in CAB, OCT, and PROs. CONCLUSION/CONCLUSIONS:These preliminary findings suggest that transition to DRF from OCRE may be an effective treatment option for people with RRMS who are clinically stable but may need to switch for reasons unrelated to effectiveness. Longer follow-up times on larger samples are needed to confirm these observations.

The late-onset GM2 gangliosidoses, comprising late-onset Tay-Sachs and Sandhoff diseases, are rare, slowly progressive, neurogenetic disorders primarily characterized by neurogenic weakness, ataxia, and dysarthria. The aim of this longitudinal study was to characterize the natural history of late-onset GM2 gangliosidoses using a number of clinical outcome assessments to measure different aspects of disease burden and progression over time, including neurological, functional, and quality of life, to inform the design of future clinical interventional trials. Patients attending the United States National Tay-Sachs & Allied Diseases Family Conference between 2015 and 2019 underwent annual clinical outcome assessments. Currently, there are no clinical outcome assessments validated to assess late-onset GM2 gangliosidoses; therefore, instruments used or designed for diseases with similar features, or to address various aspects of the clinical presentations, were used. Clinical outcome assessments included the Friedreich's Ataxia Rating Scale, the 9-Hole Peg Test, and the Assessment of Intelligibility of Dysarthric Speech. Twenty-three patients participated in at least one meeting visit (late-onset Tay-Sachs, n = 19; late-onset Sandhoff, n = 4). Patients had high disease burden at baseline, and scores for the different clinical outcome assessments were generally lower than would be expected for the general population. Longitudinal analyses showed slow, but statistically significant, neurological progression as evidenced by worsening scores on the 9-Hole Peg Test (2.68%/year, 95% CI: 0.13-5.29; p = 0.04) and the Friedreich's Ataxia Rating Scale neurological examination (1.31 points/year, 95% CI: 0.26-2.35; p = 0.02). Time since diagnosis to study entry correlated with worsening scores on the 9-Hole Peg Test (r = 0.728; p < 0.001), Friedreich's Ataxia Rating Scale neurological examination (r = 0.727; p < 0.001), and Assessment of Intelligibility of Dysarthric Speech intelligibility (r = -0.654; p = 0.001). In summary, patients with late-onset GM2 gangliosidoses had high disease burden and slow disease progression. Several clinical outcome assessments suitable for clinical trials showed only small changes and standardized effect sizes (change/standard deviation of change) over 4 years. These longitudinal natural history study results illustrate the challenge of identifying responsive endpoints for clinical trials in rare, slowly progressive, neurogenerative disorders where arguably the treatment goal is to halt or decrease the rate of decline rather than improve clinical status. Furthermore, powering such a study would require a large sample size and/or a long study duration, neither of which is an attractive option for an ultra-rare disease with no available treatment. These findings support the development of potentially more sensitive late-onset GM2 gangliosidoses-specific rating instruments and/or surrogate endpoints for use in future clinical trials.

Febrile infection-related epilepsy syndrome (FIRES) is a subset of new onset refractory status epilepticus (NORSE) that involves a febrile infection prior to the onset of the refractory status epilepticus. It is unclear whether FIRES and non-FIRES NORSE are distinct conditions. Here, we compare 34 patients with FIRES to 30 patients with non-FIRES NORSE for demographics, clinical features, neuroimaging, and outcomes. Because patients with FIRES were younger than patients with non-FIRES NORSE (median = 28 vs. 48 years old, p = .048) and more likely cryptogenic (odds ratio = 6.89), we next ran a regression analysis using age or etiology as a covariate. Respiratory and gastrointestinal prodromes occurred more frequently in FIRES patients, but no difference was found for non-infection-related prodromes. Status epilepticus subtype, cerebrospinal fluid (CSF) and magnetic resonance imaging findings, and outcomes were similar. However, FIRES cases were more frequently cryptogenic; had higher CSF interleukin 6, CSF macrophage inflammatory protein-1 alpha (MIP-1a), and serum chemokine ligand 2 (CCL2) levels; and received more antiseizure medications and immunotherapy. After controlling for age or etiology, no differences were observed in presenting symptoms and signs or inflammatory biomarkers, suggesting that FIRES and non-FIRES NORSE are very similar conditions.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Generalized convulsive seizures (GCSs) are the main risk factor of sudden unexpected death in epilepsy (SUDEP), which is likely due to peri-ictal cardiorespiratory dysfunction. The incidence of GCS-induced cardiac arrhythmias, their relationship to seizure severity markers, and their role in SUDEP physiopathology are unknown. The aim of this study was to analyze the incidence of seizure-induced cardiac arrhythmias, their association with electroclinical features and seizure severity biomarkers, as well as their specific occurrences in SUDEP cases. METHODS:-score test for 2 population proportions was used to test whether the proportion of seizures and patients with postconvulsive ESAWB or bradycardia differed between SUDEP cases and survivors. RESULTS:> 0.05). DISCUSSION/CONCLUSIONS:Markers of seizure severity are not related to seizure-induced arrhythmias of interest, suggesting that other factors such as occult cardiac abnormalities may be relevant for their occurrence. Seizure-induced ESAWB and bradycardia were more frequent in SUDEP cases, although this observation was based on a very limited number of SUDEP patients. Further case-control studies are needed to evaluate the yield of arrhythmias of interest along with respiratory changes as potential SUDEP biomarkers.

The G2019S mutation in the leucine-rich repeat kinase 2 (LRRK2) gene is a major risk factor for the development of Parkinson's disease (PD). LRRK2, although ubiquitously expressed, is highly abundant in cells of the innate immune system. Given the importance of central and peripheral immune cells in the development of PD, we sought to investigate the consequences of the G2019S mutation on microglial and monocyte transcriptome and function. We have generated large-scale transcriptomic profiles of isogenic human induced microglial cells (iMGLs) and patient derived monocytes carrying the G2019S mutation under baseline culture conditions and following exposure to the proinflammatory factors IFNγ and LPS. We demonstrate that the G2019S mutation exerts a profound impact on the transcriptomic profile of these myeloid cells, and describe corresponding functional differences in iMGLs. The G2019S mutation led to an upregulation in lipid metabolism and phagolysosomal pathway genes in untreated and LPS/IFNγ stimulated iMGLs, which was accompanied by an increased phagocytic capacity of myelin debris. We also identified dysregulation of cell cycle genes, with a downregulation of the E2F4 regulon. Transcriptomic characterization of human-derived monocytes carrying the G2019S mutation confirmed alteration in lipid metabolism associated genes. Altogether, these findings reveal the influence of G2019S on the dysregulation of the myeloid cell transcriptome under proinflammatory conditions.

OBJECTIVES/OBJECTIVE:Carotid interventions are indicated for both patients with symptomatic and a subset of patients with severe asymptomatic carotid artery stenosis (CAS). Symptomatic CAS accounts for up to 12%-25% of overall carotid interventions, but predictors of symptomatic presentation remain poorly defined. The aim of this study was to identify factors associated with symptomatic CAS in our patient population. METHODS:Between January 2015 and February 2022, an institutional retrospective cohort study of prospectively collected data on patients undergoing interventions for CAS was performed. Procedures included carotid endarterectomy (CEA), transcarotid artery revascularization (TCAR), and transfemoral carotid artery stenting (TF-CAS). Demographic data, comorbidities, procedural details, and anatomic features from various imaging modalities were collected. Comparisons were made between symptomatic (symptoms within the prior 6 months) and asymptomatic patients. RESULTS:< .001), and symptomatic patients with ulcerated plaques more frequently had less than 50% compared to moderate/severe CAS. Nine patients who presented with symptoms had mild CAS and underwent intervention. CONCLUSIONS:Symptomatic CAS was associated with a history of remote prior symptoms and lack of anti-platelet therapy at time of presentation. Furthermore, symptomatic patients not on anti-platelet agents were more likely to have a greater area of parenchymal involvement when presenting with stroke and symptomatic patients with ulcerated plaques were more likely to have mild CAS, suggesting the role of plaque instability in symptomatic presentation. These findings underscore the importance of appropriate medical management and adherence in all patients with CAS and perhaps a role for more frequent surveillance in those with potentially unstable plaque morphology.

INTRODUCTION/BACKGROUND:Hematoma expansion (HE) in patients with intracerebral hemorrhage (ICH) is a key predictor of poor prognosis and potentially amenable to treatment. This study aimed to build a classification model to predict HE in patients with ICH using deep learning algorithms without using advanced radiological features. METHODS:Data from the ATACH-2 trial (Antihypertensive Treatment of Acute Cerebral Hemorrhage) was utilized. Variables included in the models were chosen as per literature consensus on salient variables associated with HE. HE was defined as increase in either >33% or 6 mL in hematoma volume in the first 24 h. Multiple machine learning algorithms were employed using iterative feature selection and outcome balancing methods. 70% of patients were used for training and 30% for internal validation. We compared the ML models to a logistic regression model and calculated AUC, accuracy, sensitivity and specificity for the internal validation models respective models. RESULTS:[5.03-18.17] and 25.2% had HE. The best performing model across all feature selection groups and sampling cohorts was using an artificial neural network (ANN) for HE in the testing cohort with AUC 0.702 [95% CI, 0.631-0.774] with 8 hidden layer nodes The traditional logistic regression yielded AUC 0.658 [95% CI, 0.641-0.675]. All other models performed with less accuracy and lower AUC. Initial hematoma volume, time to initial CT head, and initial SBP emerged as most relevant variables across all best performing models. CONCLUSION/CONCLUSIONS:We developed multiple ML algorithms to predict HE with the ANN classifying the best without advanced radiographic features, although the AUC was only modestly better than other models. A larger, more heterogenous dataset is needed to further build and better generalize the models.