Faculty Bibliography

Saccadic slowing as a component of supranuclear saccadic gaze palsy is an important diagnostic sign in multiple neurologic conditions, including degenerative, inflammatory, genetic, or ischemic lesions affecting brainstem structures responsible for saccadic generation. Little attention has been given to the accuracy with which clinicians correctly identify saccadic slowing. We compared clinician (n = 19) judgements of horizontal and vertical saccade speed on video recordings of saccades (from 9 patients with slow saccades, 3 healthy controls) to objective saccade peak velocity measurements from infrared oculographic recordings. Clinician groups included neurology residents, general neurologists, and fellowship-trained neuro-ophthalmologists. Saccades with normal peak velocities on infrared recordings were correctly identified as normal in 57% (91/171; 171 = 9 videos × 19 clinicians) of clinician decisions; saccades determined to be slow on infrared recordings were correctly identified as slow in 84% (224/266; 266 = 14 videos × 19 clinicians) of clinician decisions. Vertical saccades were correctly identified as slow more often than horizontal saccades (94% versus 74% of decisions). No significant differences were identified between clinician training levels. Reliable differentiation between normal and slow saccades is clinically challenging; clinical performance is most accurate for detection of vertical saccade slowing. Quantitative analysis of saccade peak velocities enhances accurate detection and is likely to be especially useful for detection of mild saccadic slowing.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Recent studies have suggested that inter-eye differences (IEDs) in peripapillary retinal nerve fiber layer (pRNFL) or ganglion cell+inner plexiform (GCIPL) thickness by spectral-domain optical coherence tomography (SD-OCT) may identify people with a history of unilateral optic neuritis (ON). However, this requires further validation. Machine learning classification may be useful for validating thresholds for OCT IEDs and for examining added utility for visual function tests, such as low-contrast letter acuity (LCLA), in the diagnosis of people with multiple sclerosis (PwMS) and for unilateral ON history. METHODS:Participants were from 11 sites within the International Multiple Sclerosis Visual System (IMSVISUAL) consortium. pRNFL and GCIPL thicknesses were measured using SD-OCT. A composite score combining OCT and visual measures was compared individual measurements to determine the best model to distinguish PwMS from controls. These methods were also used to distinguish those with history of ON among PwMS. ROC curve analysis was performed on a training dataset (2/3 of cohort), then applied to a testing dataset (1/3 of cohort). Support vector machine (SVM) analysis was used to assess whether machine learning models improved diagnostic capability of OCT. RESULTS:Among 1,568 PwMS and 552 controls, variable selection models identified GCIPL IED, average GCIPL thickness (both eyes), and binocular 2.5% LCLA as most important for classifying PwMS vs. controls. This composite score performed best, with AUC=0.89 (95% CI 0.85, 0.93), sensitivity=81% and specificity=80%. The composite score ROC curve performed better than any of the individual measures from the model (p<0.0001). GCIPL IED remained the best single discriminator of unilateral ON history among PwMS (AUC=0.77, 95% CI 0.71,0.83, sensitivity=68%, specificity=77%). SVM analysis performed comparably to standard logistic regression models. CONCLUSIONS:A composite score combining visual structure and function improved the capacity of SD-OCT to distinguish PwMS from controls. GCIPL IED best distinguished those with history of unilateral ON. SVM performed as well as standard statistical models for these classifications. CLASSIFICATION OF EVIDENCE/METHODS:The study provides Class III evidence that SD-OCT accurately distinguishes multiple sclerosis from normal controls as compared to clinical criteria.

BACKGROUND:STRIVE was a prospective, 4-year, multicenter, observational, open-label, single-arm study of natalizumab treatment in anti-JC virus antibody-negative patients with early relapsing-remitting multiple sclerosis (RRMS). OBJECTIVE:Study objectives examined the effects of natalizumab on cognitive processing speed, confirmed disability improvement (CDI), and patient-reported outcomes (PROs). METHODS:Clinical and PRO secondary endpoints were assessed annually over 4 years in STRIVE. The Symbol Digit Modalities Test (SDMT) was used as a measure of cognitive processing speed. PROs were assessed using the Multiple Sclerosis Impact Score (MSIS-29) and the Work Productivity and Activity Impairment Questionnaire (WPAI). RESULTS:At all four annual assessments, the proportion of patients in the intent-to-treat (ITT) population (N = 222) who exhibited clinically meaningful improvement in their SDMT score from baseline (i.e., change ≥ 4 points) ranged from 41.9 to 54.0%. The cumulative probability of CDI at 4 years in patients in the ITT population with a baseline Expanded Disability Status Scale score ≥ 2 (N = 133) was 43.9%. Statistically significant reductions in the mean change from screening in the MSIS-29 physical and psychological scores, indicating improved quality of life, were observed over all 4 years (P ≤ 0.0012 for all). A statistically significant decrease from screening in the impact of MS on regular activities, signifying an improvement in this WPAI measure, was also observed over all 4 years of the study. CONCLUSION/CONCLUSIONS:These results further extend our knowledge of the effectiveness, specifically regarding improvements in cognitive processing speed, disability and PROs, of long-term natalizumab treatment in early RRMS patients. CLINICALTRIALS/RESULTS:GOV: NCT01485003 (5 December 2011).

BACKGROUND/OBJECTIVES/OBJECTIVE:Little is known about trajectories of recovery 12-months after hospitalization for severe COVID. METHODS:We conducted a prospective, longitudinal cohort study of patients with and without neurological complications during index hospitalization for COVID-19 from March 10, 2020-May 20, 2020. Phone follow-up batteries were performed at 6- and 12-months post-COVID symptom onset. The primary 12-month outcome was the modified Rankin Scale (mRS) comparing patients with or without neurological complications using multivariable ordinal analysis. Secondary outcomes included: activities of daily living (Barthel Index), telephone Montreal Cognitive Assessment (t-MoCA) and Neuro-QoL batteries for anxiety, depression, fatigue and sleep. Changes in outcome scores from 6 to 12-months were compared using non-parametric paired-samples sign test. RESULTS:Twelve-month follow-up was completed in N=242 patients (median age 65, 64% male, 34% intubated during hospitalization) and N=174 completed both 6- and 12-month follow-up. At 12-months 197/227 (87%) had ≥1 abnormal metric: mRS>0 (75%), Barthel<100 (64%), t-MoCA≤18 (50%), high anxiety (7%), depression (4%), fatigue (9%) and poor sleep (10%). 12-month mRS scores did not differ significantly among those with (N=113) or without (N=129) neurological complications during hospitalization after adjusting for age, sex, race, pre-COVID mRS and intubation status (adjusted OR 1.4, 95% CI0.8-2.5), though those with neurological complications had higher fatigue scores (T-score 47 vs 44, P=0.037). Significant improvements in outcome trajectories from 6- to 12-months were observed in t-MoCA scores (56% improved, median difference 1 point, P=0.002), and Neuro-QoL anxiety scores (45% improved, P=0.003). Non-significant improvements occurred in fatigue, sleep and depression scores in 48%, 48% and 38% of patients, respectively. Barthel and mRS scores remained unchanged between 6 and 12-months in >50% of patients. DISCUSSION/CONCLUSIONS:At 12-months post-hospitalization for severe COVID, 87% of patients had ongoing abnormalities in functional, cognitive or Neuro-QoL metrics and abnormal cognition persisted in 50% of patients without a prior history of dementia/cognitive abnormality. Only fatigue severity differed significantly between patients with or without neurological complications during index hospitalization. However, significant improvements in cognitive (t-MoCA) and anxiety (Neuro-QoL) scores occurred in 56% and 45% of patients, respectively, between 6- to 12-months. These results may not be generalizable to those with mild/moderate COVID.

ABSTRACT:A 62-year-old man presented with headache, fever, and malaise. He was diagnosed with Anaplasma phagocytophilum, confirmed by serum polymerase chain reaction, and started on oral doxycycline. After 5 days of treatment, the patient began to experience gait imbalance with frequent falls, as well as myoclonus, and confusion. Examination was notable for opsoclonus-myoclonus-ataxia (OMA) and hypometric saccades. Cerebrospinal fluid (CSF) autoimmune encephalitis panel demonstrated a markedly elevated neuronal intermediate filament (NIF) immunoglobulin G antibody titer of 1:16, with positive neurofilament light- and heavy-chain antibodies. These antibodies were suspected to have been triggered by the Anaplasma infection. Repeat CSF examination 8 days later still showed a positive immunofluorescence assay for NIF antibodies, but the CSF titer was now less than 1:2. Body computed tomography imaging was unrevealing for an underlying cancer. Our patient illustrates a postinfectious mechanism for OMA and saccadic hypometria after Anaplasma infection.

Purpose/UNASSIGNED:Herpes zoster (HZ) has been identified as a potential association with the BNT162b2 COVID-19 vaccination. This study evaluated this possible association in a cohort of patients receiving the vaccination. Methods/UNASSIGNED:Epic electronic health records of adult patients who received at least one COVID-19 vaccination between January 12, 2020 and 9/30/2021 within the NYU Langone Health were reviewed to analyze a new diagnosis of herpes zoster within 3 months before compared to 3 months after vaccination. Results/UNASSIGNED:Of the 596,111 patients who received at least one COVID-19 vaccination, 716 patients were diagnosed with HZ within three months prior to vaccination, compared to 781 patients diagnosed within 3 months afterwards. Using the chi-square test for independence of proportions, there was not a statistically significant difference in frequency of HZ before (proportion: 0.0012, 95% CI: [0.0011, 0.0013]) vs. after vaccination (proportion: 0.0013, 95% CI: [0.0012, 0.0014]); (p = 0.093). Conclusions and importance/UNASSIGNED:This study did not find evidence of an association between COVID-19 vaccination and a new diagnosis of HZ. We encourage health care professionals to strongly recommend COVID-19 vaccinations per Centers for Disease Control (CDC) recommendations and vaccination against HZ according to Food and Drug Administration (FDA) approval for the recombinant zoster vaccine.

INTRODUCTION/BACKGROUND:Neurological complications among hospitalized COVID-19 patients may be associated with elevated neurodegenerative biomarkers. METHODS:Among hospitalized COVID-19 patients without a history of dementia (N = 251), we compared serum total tau (t-tau), phosphorylated tau-181 (p-tau181), glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), ubiquitin carboxy-terminal hydrolase L1 (UCHL1), and amyloid beta (Aβ40,42) between patients with or without encephalopathy, in-hospital death versus survival, and discharge home versus other dispositions. COVID-19 patient biomarker levels were also compared to non-COVID cognitively normal, mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia controls (N = 161). RESULTS:Admission t-tau, p-tau181, GFAP, and NfL were significantly elevated in patients with encephalopathy and in those who died in-hospital, while t-tau, GFAP, and NfL were significantly lower in those discharged home. These markers correlated with severity of COVID illness. NfL, GFAP, and UCHL1 were higher in COVID patients than in non-COVID controls with MCI or AD. DISCUSSION/CONCLUSIONS:Neurodegenerative biomarkers were elevated to levels observed in AD dementia and associated with encephalopathy and worse outcomes among hospitalized COVID-19 patients.

We describe an educational intervention for neurology residents aimed at developing feedback skills. An objective structured clinical examination case was designed to simulate the provision of feedback to a medical student. After the simulated case session, residents received structured, individualized feedback on their performance and then participated in a group discussion about feedback methods. Survey data were collected from the standardized medical student regarding residents' performance and from residents for assessments of their performance and of the OSCE case. This manuscript aims to describe this educational intervention and to demonstrate the feasibility of this approach for feedback skills development.

BACKGROUND:Visual tests in Alzheimer disease (AD) have been examined over the last several decades to identify a sensitive and noninvasive marker of the disease. Rapid automatized naming (RAN) tasks have shown promise for detecting prodromal AD or mild cognitive impairment (MCI). The purpose of this investigation was to determine the capacity for new rapid image and number naming tests and other measures of visual pathway structure and function to distinguish individuals with MCI due to AD from those with normal aging and cognition. The relation of these tests to vision-specific quality of life scores was also examined in this pilot study. METHODS:Participants with MCI due to AD and controls from well-characterized NYU research and clinical cohorts performed high and low-contrast letter acuity (LCLA) testing, as well as RAN using the Mobile Universal Lexicon Evaluation System (MULES) and Staggered Uneven Number test, and vision-specific quality of life scales, including the 25-Item National Eye Institute Visual Function Questionnaire (NEI-VFQ-25) and 10-Item Neuro-Ophthalmic Supplement. Individuals also underwent optical coherence tomography scans to assess peripapillary retinal nerve fiber layer and ganglion cell/inner plexiform layer thicknesses. Hippocampal atrophy on brain MRI was also determined from the participants' Alzheimer disease research center or clinical data. RESULTS:Participants with MCI (n = 14) had worse binocular LCLA at 1.25% contrast compared with controls (P = 0.009) and longer (worse) MULES test times (P = 0.006) with more errors in naming images (P = 0.009) compared with controls (n = 16). These were the only significantly different visual tests between groups. MULES test times (area under the receiver operating characteristic curve [AUC] = 0.79), MULES errors (AUC = 0.78), and binocular 1.25% LCLA (AUC = 0.78) showed good diagnostic accuracy for distinguishing MCI from controls. A combination of the MULES score and 1.25% LCLA demonstrated the greatest capacity to distinguish (AUC = 0.87). These visual measures were better predictors of MCI vs control status than the presence of hippocampal atrophy on brain MRI in this cohort. A greater number of MULES test errors (rs = -0.50, P = 0.005) and worse 1.25% LCLA scores (rs = 0.39, P = 0.03) were associated with lower (worse) NEI-VFQ-25 scores. CONCLUSIONS:Rapid image naming (MULES) and LCLA are able to distinguish MCI due to AD from normal aging and reflect vision-specific quality of life. Larger studies will determine how these easily administered tests may identify patients at risk for AD and serve as measures in disease-modifying therapy clinical trials.

OBJECTIVE:Rapid automatized naming (RAN) tasks have been utilized for decades to evaluate neurological conditions. Time scores for the Mobile Universal Lexicon Evaluation System (MULES, rapid picture naming) and Staggered Uneven Number (SUN, rapid number naming) are prolonged (worse) with concussion, mild cognitive impairment, multiple sclerosis and Parkinson's disease. The purpose of this investigation was to compare paper/pencil versions of MULES and SUN with a new digitized format, the MICK app. METHODS:Participants (healthy office-based volunteers, professional women's hockey players), completed two trials of the MULES and SUN tests on both platforms (tablet, paper/pencil). The order of presentation of the testing platforms was randomized. Between-platform variability was calculated using the two-way random-effects intraclass correlation coefficient (ICC). RESULTS:Among 59 participants (median age 32, range 22-83), no significant differences were observed for comparisons of mean best scores for the paper/pencil versus MICK app platforms, counterbalanced for order of administration (P = 0.45 for MULES, P = 0.50 for SUN, linear regression). ICCs for agreement between the MICK and paper/pencil tests were 0.92 (95% CI 0.86, 0.95) for MULES and 0.94 (95% CI 0.89, 0.96) for SUN, representing excellent levels of agreement. Inter-platform differences did not vary systematically across the range of average best time score for either test. CONCLUSION/CONCLUSIONS:The MICK app for digital administration of MULES and SUN demonstrates excellent agreement of time scores with paper/pencil testing. The computerized app allows for greater accessibility and scalability in neurological diseases, inclusive of remote monitoring. Sideline testing for sports-related concussion may also benefit from this technology.