Faculty Bibliography

BACKGROUND:In many parts of the world including India, the prevalence of autoimmune inflammatory diseases such as neuromyelitis optica spectrum disorders (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and multiple sclerosis (MS) is rising. A diagnosis is often delayed due to insufficient diagnostic tools. Machine learning (ML) models have accurately differentiated eyes of patients with MS from those of healthy controls (HCs) using optical coherence tomography (OCT)-based retinal images. Examining OCT characteristics may allow for early differentiation of these conditions. The objective of this study was to determine feasibility of ML analyses to distinguish between patients with different autoimmune inflammatory diseases, other ocular diseases, and HCs based on OCT measurements of the peripapillary retinal nerve fiber layer (pRNFL), ganglion cell-inner plexiform layer (GCIPL), and inner nuclear layers (INLs). METHODS:Eyes of people with MS (n = 99 patients), NMOSD (n = 40), MOGAD (n = 74), other ocular diseases (OTHER, n = 16), and HCs (n = 54) from the Mangalore Demyelinating Disease Registry were included. Support vector machine (SVM) classification models incorporating age, pRNFL, GCIPL, and INL were performed. Data were split into training (70%) and testing (30%) data and accounted for within-patient correlations. Cross-validation was used in training to choose the best parameters for the SVM model. Accuracy and area under receiver operating characteristic curves (AUROCs) were used to assess model performance. RESULTS:The SVM models distinguished between eyes of patients with each condition (i.e., MOGAD vs NMOSD, NMOSD vs HC, MS vs OTHER, etc) with strong discriminatory power demonstrated from the AUROCs for these comparisons ranging from 0.81 to 1.00. These models also performed with moderate to high accuracy, ranging from 0.66 to 0.81, with the exception of the MS vs NMOSD comparison, which had an accuracy of 0.53. CONCLUSIONS:ML models are useful for distinguishing between autoimmune inflammatory diseases and for distinguishing these from HCs and other ocular diseases based on OCT measures. This study lays the groundwork for future deep learning studies that use analyses of raw OCT images for identifying eyes of patients with such disorders and other etiologies of optic neuropathy.

The 2024 revised McDonald criteria for multiple sclerosis recognize the optic nerve as a topography for dissemination in space. Optical coherence tomography-derived inter-eye differences in peri-papillary retinal nerve fiber layer or ganglion cell-inner plexiform layer thicknesses (≥6μm or ≥4μm, respectively) are proposed for identifying unilateral optic nerve involvement. However, the value of combining inter-eye difference measures and optimal temporal-quadrant peri-papillary retinal nerve fiber layer inter-eye differences remains unclear. We investigated the diagnostic performance of combined inter-eye differences, optimal temporal-quadrant peri-papillary retinal nerve fiber layer inter-eye differences, and examined the effects of time, prior optic neuritis frequency, sex, and race on inter-eye differences. Retinal optical coherence tomography images from all study participants underwent rigorous quality control. Receiver operating characteristic analyses and area under the receiver operating characteristic curves (AUC) were used to determine optimal inter-eye differences of individual and combined measures to distinguish eyes with, from without, prior optic neuritis in people with multiple sclerosis. Mixed-effects models were used to assess impact of time, prior optic neuritis events, sex, and race on inter-eye differences. An independent multiple sclerosis cohort from a second center was examined for external validation. Among 1854 people with multiple sclerosis, optimal inter-eye difference thresholds for identifying unilateral optic nerve involvement were 6μm for peri-papillary retinal nerve fiber layer (AUC=0.80), 4μm for ganglion cell-inner plexiform layer (AUC=0.83), and 8μm for temporal-quadrant peri-papillary retinal nerve fiber layer (AUC=0.71) thicknesses. Peri-papillary retinal nerve fiber layer inter-eye differences ≥6μm or ganglion cell-inner plexiform layer inter-eye differences ≥4μm yielded 87.6% sensitivity, 70.0% specificity, and 64.0% positive predictive value. Concurrent inter-eye differences at lower thresholds (≥5μm peri-papillary retinal nerve fiber layer, ≥3μm ganglion cell-inner plexiform layer) reduced sensitivity to 72.5%, but improved specificity (86.6%) and positive predictive value (76.7%), while maintaining accuracy and negative predictive value. Temporal-quadrant peri-papillary retinal nerve fiber layer inter-eye differences did not improve diagnostic performance. Over a median of 5.1 years, ganglion cell-inner plexiform layer and peri-papillary retinal nerve fiber layer inter-eye differences remained stable. Prior optic neuritis counts and sex did not affect inter-eye differences. Although Black Americans had higher inter-eye differences than White Americans, optimal thresholds were comparable across races. The validation cohort comprising 254 people with multiple sclerosis confirmed these findings. In conclusion, concurrent peri-papillary retinal nerve fiber layer (≥5μm) and ganglion cell-inner plexiform layer inter-eye differences (≥3μm) improve unilateral optic nerve involvement detection versus either alone (≥6μm or ≥4μm, respectively), while temporal-quadrant peri-papillary retinal nerve fiber layer inter-eye differences offer limited benefit. Inter-eye differences remain stable longitudinally and unaffected by prior optic neuritis frequency.

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts (RHI). In CTE, hyperphosphorylated tau (p-tau) aggregates are found in neurons at the depth of cortical sulci close to the gray matter/white matter (GM/WM) boundary. To date, CTE can only be diagnosed postmortem by neuropathological examination. Traumatic encephalopathy syndrome (TES) is the clinical syndrome purported to be associated with CTE pathology. The aim of this study is to investigate microstructural properties at the GM/WM boundary in individuals with a history of exposure to RHI and clinical features of CTE (i.e., TES). Diffusion magnetic resonance imaging (dMRI), TES diagnoses, and cerebrospinal fluid (CSF) biomarkers were acquired from 165 male former American football players (age: 57.29 ± 8.23 years) from the DIAGNOSE CTE Research Project, a multicenter, observational cohort study. Fractional anisotropy (FA) was measured at the GM/WM boundary of the whole brain. In addition, a widely used method (tract-based spatial statistics [TBSS]) was applied to measure FA of central WM. We used analyses of covariance to test associations between FA and TES. Furthermore, we used linear regressions to test associations between FA and nine CSF biomarkers (i.e., p-tau-181, -217, -231, total tau, amyloid β [Aβ]_1-40, Aβ_1-42, glial fibrillary acidic protein [GFAP], neurofilament light [NfL], and soluble triggering receptor expressed on myeloid cells-2 [sTREM2]). We report an association between higher FA at the GM/WM boundary and higher levels of certainty for CTE pathology (F(1, 147) = 5.781, 95% confidence interval (CI) = 0.0003-0.003, p = 0.035) as well as neurobehavioral dysregulation (F(1, 148) = 7.559, 95% CI = 0.001-0.009, p = 0.020), and functional dependence/dementia (F(1, 148) = 5.046, 95% CI = 0.0004-0.006, p = 0.039). In addition, we report an association between higher FA at the GM/WM boundary and higher CSF p-tau-181 (β = 0.272, 95% CI = 0.078-0.466, p = 0.029) and p-tau-217 (β = 0.295, 95% CI = 0.102-0.488, p = 0.027). FA of the central WM was not associated with TES diagnoses. Taken together, these findings suggest that dMRI at the GM/WM boundary could be used to investigate microstructural alterations suggestive of tau pathology-associated neurodegeneration in individuals with TES, the clinical presentation of CTE. Future studies are needed to validate this approach and to identify clinically useful cutoff values for dMRI metrics.

PURPOSE/OBJECTIVE:Many studies estimate that more than 50% of non-hospitalized patients with long-COVID develop moderate to severe autonomic dysfunction. However, the specific impact of autonomic dysfunction as it relates to quality of life in long-COVID is not fully understood. The aim of the current study is to assess autonomic symptoms and quality-of-life in patients with Post-Acute Sequelae of COVID-19 (PASC) recruited from a neurology department outpatient setting. METHODOLOGY/METHODS:In a two-year follow-up study of a baseline cohort of 93 non-hospitalized SARS-CoV-2 laboratory-positive patients evaluated for PASC between November 2020-August 2021, 44 participants completed follow-up telephone questionnaires examining quality-of-life as well as neurologic and autonomic symptoms. RESULTS:Among 93 participants, 44 (47 %) completed the two-year follow-up evaluation and 27 (61 %) were female with a median age of 55 years (IQR = 24-88). Most participants (95 %, 42/44) were vaccinated against COVID-19 and 43 % (19/44) had a pre-existing neurological disorder. Median time from index COVID-19 infection to follow-up was 26 months (IQR = 23-17), with a median of 15 months (IQR = 15-16) between visits. Fatigue, word finding difficulty, and changes in memory were the most commonly reported PASC symptoms. Sixty-six percent (29/44) of individuals met criteria for autonomic dysfunction as defined by the Composite Autonomic Symptom Score-31 (COMPASS-31) scale. Secretomotor and gastrointestinal subdomains demonstrated significant associations with Neuro-QoL metrics for Anxiety, Depression, and Fatigue. For every 1 additional PASC symptom reported at a follow-up study visit, there was an average increase of 1.5 points on the COMPASS-31 composite score. In addition, visual disturbances and sleep impairment were both associated with increased autonomic dysfunction. CONCLUSION/CONCLUSIONS:The strong association between autonomic dysfunction and reduced QoL in PASC and the relation to insomnia, visual dysfunction, and functional impairment are valuable findings, reinforcing the clinical impact of these symptoms longitudinally after index COVID-19 infection.

BACKGROUND:There is paucity of data on long-term functional and cognitive outcomes after COVID-19 compared to COVID-negative controls. METHODS:We conducted an observational cohort study of patients ≥ 1 year after COVID-19 compared to contemporaneous COVID-19 negative controls (SARS-CoV-2 nucleocapsid IgG negative with no history of COVID-19). Functional (modified Rankin Scale [mRS], Barthel Index), cognitive (telephone MoCA [t-MoCA]), and patient-reported neuropsychiatric symptoms were compared between groups using multivariable logistic regression analysis. In a subgroup of COVID-19 patients who were followed longitudinally, trajectories of recovery were assessed using the paired samples Sign test. RESULTS:Of 145 participants, N = 115 COVID-19 patients (median age 62, 51 % female, 33 % hospitalized for COVID-19, median 2.9 years from index infection), and N = 30 non-COVID-19 controls (median age 75, 70 % female) were enrolled. Neuropsychiatric symptoms were reported in 76 % of COVID-19 patients versus 7 % of controls (aOR 15.0, 95 %CI 3.09-72.47, P < 0.001). Abnormal mRS> 0 occurred in 42 % of COVID-19 patients compared to 11 % of controls (P = 0.002). However, this difference was not significant after adjusting for age, sex, COVID-19 hospitalization and history of mood disorder (aOR 2.10, 95 %CI 0.52-8.51). Rates of abnormal t-MoCA≤ 18 (40 % of COVID-19 versus 41 % of controls, P = 1.00) and Barthel scores< 100 (19 % of COVID-19 versus 14 % in controls, P = 0.785) were similar. Among N = 26 COVID-19 patients with repeated measures, mRS significantly improved between 6-months to 3-years post-COVID (+1.3 points, p = 0.004), while no changes were observed in t-MoCA or Barthel. CONCLUSIONS:Three years after COVID-19, neuropsychiatric symptoms were significantly more frequent compared to controls, however no differences in functional or cognitive status were detected.

BACKGROUND AND OBJECTIVES/OBJECTIVE:While reductions in optical coherence tomography (OCT) pRNFL and ganglion cell-inner plexiform layer thicknesses have been shown to be associated with brain atrophy in adult-onset MS (AOMS) cohorts, the relationship between OCT and brain MRI measures is less established in pediatric-onset MS (POMS). Our aim was to examine the associations of OCT measures with volumetric MRI in a cohort of patients with POMS to determine whether OCT measures reflect CNS neurodegeneration in this patient population, as is seen in AOMS cohorts. METHODS:This was a cross-sectional study with retrospective ascertainment of patients with POMS evaluated at a single center with expertise in POMS and neuro-ophthalmology. As part of routine clinical care, patients with POMS are evaluated by a POMS expert and undergo volumetric brain MRI, including whole-brain (WB), subregional, and gray matter (GM) volume analyses. Patients with POMS are routinely referred to neuro-ophthalmology for evaluation that includes high-contrast visual acuity, color vision testing, and OCT. Generalized estimating equation (GEE) models, accounting for within-patient, intereye correlations (both eyes of each patient were included), MS disease duration, and disease-modifying therapy efficacy, were used to determine the relationship between visual pathway structure and function and volumetric MRI measures. RESULTS:= 0.015, respectively). DISCUSSION/CONCLUSIONS:Our results demonstrate that changes in visual pathway structures are associated with reductions in overall brain volume and GM volumes, as well as greater lesion and black hole burden. Collectively, our results emphasize the importance of visual assessment in POMS and suggest that OCT reflects overall CNS neurodegeneration in this cohort.

The 2024 revisions of the McDonald diagnostic criteria include the optic nerve as a fifth anatomical location within the CNS for the diagnosis of multiple sclerosis, in addition to periventricular, juxtacortical or cortical, infratentorial, and spinal cord lesions. Demonstration of dissemination in space can now be achieved with the detection of typical lesions in at least two of these five locations. We review the evidence supporting the use of optical coherence tomography (OCT) and visual evoked potentials (VEPs) to show optic nerve involvement in the diagnosis of multiple sclerosis. We also report consensus recommendations for their use. Provided there is no better explanation for optic nerve involvement and that rigorous quality control is applied, OCT-derived peripapillary retinal nerve fibre layer inter-eye differences of 6 μm or greater or composite macular ganglion cell and inner plexiform layer inter-eye differences of 4 μm or greater support optic nerve injury. Delayed VEP latency, which depends on technical and methodological factors, and is centre and device dependent, supports demyelinating optic nerve injury when done with appropriate technical knowledge and interpretation.

BACKGROUND AND OBJECTIVES/UNASSIGNED:Burnout is a pervasive occupational hazard for neurologists-undermining their well-being, jeopardizing patient safety and satisfaction, limiting access to care, and inflating health care costs. Well-designed appreciation and recognition practices may help mitigate some of its key drivers. This pilot study evaluates faculty perspectives on appreciation strategies in an academic neurology department. We used the Moffitt Provider Appreciation Assessment (MPAA), which assesses the types of appreciation methods respondents value, regardless of whether those practices are currently implemented in their workplace. METHODS/UNASSIGNED:A cross-sectional survey was conducted among full-time clinical faculty in the Department of Neurology at NYU Grossman School of Medicine. The survey included demographics, the MPAA, the single-item Mini-Z burnout inventory to assess self-reported burnout levels, and an intent-to-leave question. MPAA responses were analyzed for frequencies, and the association between burnout and intent to leave was examined. RESULTS/UNASSIGNED:< 0.00001). Because the scores for self-reported burnout and intent to leave reflect current work conditions while MPAA scores capture enduring personal values, MPAA rankings cannot be compared directly with burnout or turnover metrics. DISCUSSION/UNASSIGNED:Neurology clinical faculty prioritized appreciation methods that directly address clinical work, underscoring the value of implementing tailored recognition practices that may reduce burnout. The methodology used in this pilot study can be adapted for broader application in other settings. After identifying faculty preferences, health care organizations can implement meaningful, transparent, and inclusive appreciation strategies that have the potential to strengthen physician relationships, promote well-being, and support a sustainable workforce.

Effective mild cognitive impairment (MCI) screening requires accessible testing. This study compared two tests for distinguishing MCI patients from controls: Rapid Automatized Naming (RAN) for naming speed and Low Contrast Letter Acuity (LCLA) for sensitivity to low contrast letters. Two RAN tasks were used: the Mobile Universal Lexicon Evaluation System (MULES, picture naming) and Staggered Uneven Number test (SUN, number naming). Both RAN tasks were administered on a tablet and in a paper/pencil format. The tablet format was administered using the Mobile Integrated Cognitive Kit (MICK) application. LCLA was tested at 2.5% and 1.25% contrast. Sixty-four participants (31 MCI, 34 controls; mean age 73.2 ± 6.8 years) were included. MCI patients were slower than controls for paper/pencil (75.0 vs. 53.6 sec, p < 0.001), and tablet MULES (69.0 sec vs. 50.2 sec, p = 0.01). The paper/pencil SUN showed no significant difference (MCI: 59.5 sec vs. controls: 59.9 sec, p = 0.07), nor did tablet SUN (MCI: 59.3 sec vs. controls: 55.7 sec, p = 0.36). MCI patients had worse performance on LCLA testing at 2.5% contrast (33 letters vs. 36, p = 0.04*) and 1.25% (0 letters vs. 14. letters, p < 0.001). Receiver operating characteristic (ROC) analysis showed similar performance of paper/pencil and tablet MULES in distinguishing MCI from controls (AUC = 0.77), outperforming both SUN (AUC = 0.63 paper, 0.59 tablet) and LCLA (2.5% contrast: AUC = 0.65, 1.25% contrast: AUC = 0.72). The MULES, in both formats, may be a valuable screening tool for MCI.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Disturbances in brain catecholamine activity may be associated with symptoms after exposure to repetitive head impacts (RHIs) or related chronic traumatic encephalopathy (CTE). In this article, we studied CSF catecholamines in former professional and college American football players and examined the relationship with football proxies of RHI exposure, CTE probability, cognitive performance, neuropsychiatric symptoms, and parkinsonism. METHODS:In this observational cross-sectional study, we examined male former American football players, professional ("PRO") or college ("COL") level, and asymptomatic unexposed male ("UE") individuals from the DIAGNOSE CTE Research Project. Catecholamines-norepinephrine (NE) and its metabolite, 3,4-dihydroxyphenylglycol (DHPG), and dopamine (DA) and its precursor, 3,4-dihydroxyphenylalanine (l-DOPA), and metabolite, 3,4-dihydroxyphenylacetic acid (DOPAC)-were measured in CSF with high-performance liquid chromatography and compared across groups with analysis of covariance. Multivariable linear regression models tested the relationship between CSF catecholamines and proxies of RHI exposure (e.g., total years of playing American football), factor scores for cognition, and neurobehavioral dysregulation (explosivity, emotional dyscontrol, impulsivity, affective lability), as well as depressive/anxiety symptoms, measured with the Beck Depression/Anxiety Inventories. CTE probability and parkinsonism were assessed using the National Institute of Neurological Disorders and Stroke consensus diagnostic criteria for traumatic encephalopathy syndrome (TES), and biomarkers were compared among different diagnostic groups. RESULTS:The cohort consisted of 120 former American football players (85 PRO players, 35 COL players) and 35 UE participants (age 45-75). Former players had significantly lower levels of NE (mean difference = -0.114, 95% CI -0.190 to -0.038), l-DOPA (-0.121, 95% CI -0.109 to -0.027), and DOPAC (-0.116, 95% CI -0.177 to -0.054) than UE participants. For NE and DOPAC, these overall group differences were primarily due to differences between the PRO and UE cohorts. No significant differences were found across TES-CTE probability subgroups or TES-parkinsonism diagnostic groups. Within the COL cohort, tested as post hoc analyses, higher CSF NE and l-DOPA were associated with higher neurobehavioral dysregulation factor scores, BAI total score, and worse executive functioning and processing speed. CSF DHPG and DOPAC were associated with impulsivity only in this subgroup. DISCUSSION/CONCLUSIONS:We observed reduced CSF catecholamine concentrations in former elite American football players, although the relationship with degree of RHI exposure and the clinical impact needs further study.