Faculty Bibliography

BACKGROUND:Limited data exists evaluating predictors of long-term outcomes after hospitalization for COVID-19. METHODS:We conducted a prospective, longitudinal cohort study of patients hospitalized for COVID-19. The following outcomes were collected at 6 and 12-months post-diagnosis: disability using the modified Rankin Scale (mRS), activities of daily living assessed with the Barthel Index, cognition assessed with the telephone Montreal Cognitive Assessment (t-MoCA), Neuro-QoL batteries for anxiety, depression, fatigue and sleep, and post-acute symptoms of COVID-19. Predictors of these outcomes, including demographics, pre-COVID-19 comorbidities, index COVID-19 hospitalization metrics, and life stressors, were evaluated using multivariable logistic regression. RESULTS:Of 790 COVID-19 patients who survived hospitalization, 451(57%) completed 6-month (N = 383) and/or 12-month (N = 242) follow-up, and 77/451 (17%) died between discharge and 12-month follow-up. Significant life stressors were reported in 121/239 (51%) at 12-months. In multivariable analyses, life stressors including financial insecurity, food insecurity, death of a close contact and new disability were the strongest independent predictors of worse mRS, Barthel Index, depression, fatigue, and sleep scores, and prolonged symptoms, with adjusted odds ratios ranging from 2.5 to 20.8. Other predictors of poor outcome included older age (associated with worse mRS, Barthel, t-MoCA, depression scores), baseline disability (associated with worse mRS, fatigue, Barthel scores), female sex (associated with worse Barthel, anxiety scores) and index COVID-19 severity (associated with worse Barthel index, prolonged symptoms). CONCLUSIONS:Life stressors contribute substantially to worse functional, cognitive and neuropsychiatric outcomes 12-months after COVID-19 hospitalization. Other predictors of poor outcome include older age, female sex, baseline disability and severity of index COVID-19.

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.

Although visual symptoms are common following concussion, quantitative measures of visual function are missing from concussion evaluation protocols on the athletic sideline. For the past half century, rapid automatized naming (RAN) tasks have demonstrated promise as quantitative neuro-visual assessment tools in the setting of head trauma and other disorders but have been previously limited in accessibility and scalability. The Mobile Interactive Cognitive Kit (MICK) App is a digital RAN test that can be downloaded on most mobile devices and can therefore provide a quantitative measure of visual function anywhere, including the athletic sideline. This investigation examined the feasibility of MICK App administration in a cohort of Division 1 college football players. Participants (n = 82) from a National Collegiate Athletic Association (NCAA) Division 1 football team underwent baseline testing on the MICK app. Total completion times of RAN tests on the MICK app were recorded; magnitudes of best time scores and between-trial learning effects were determined by paired t-test. Consistent with most timed performance measures, there were significant learning effects between the two baseline trials for both RAN tasks on the MICK app: Mobile Universal Lexicon Evaluation System (MULES) (p < 0.001, paired t-test, mean improvement 13.3 s) and the Staggered Uneven Number (SUN) (p < 0.001, mean improvement 3.3 s). This study demonstrated that the MICK App can be feasibly administered in the setting of pre-season baseline testing in a Division I environment. These data provide a foundation for post-injury sideline testing that will include comparison to baseline in the setting of concussion.

BACKGROUND:Spectral-domain (SD-) optical coherence tomography (OCT) can reliably measure axonal (peripapillary retinal nerve fiber layer [pRNFL]) and neuronal (macular ganglion cell + inner plexiform layer [GCIPL]) thinning in the retina. Measurements from 2 commonly used SD-OCT devices are often pooled together in multiple sclerosis (MS) studies and clinical trials despite software and segmentation algorithm differences; however, individual pRNFL and GCIPL thickness measurements are not interchangeable between devices. In some circumstances, such as in the absence of a consistent OCT segmentation algorithm across platforms, a conversion equation to transform measurements between devices may be useful to facilitate pooling of data. The availability of normative data for SD-OCT measurements is limited by the lack of a large representative world-wide sample across various ages and ethnicities. Larger international studies that evaluate the effects of age, sex, and race/ethnicity on SD-OCT measurements in healthy control participants are needed to provide normative values that reflect these demographic subgroups to provide comparisons to MS retinal degeneration. METHODS:Participants were part of an 11-site collaboration within the International Multiple Sclerosis Visual System (IMSVISUAL) consortium. SD-OCT was performed by a trained technician for healthy control subjects using Spectralis or Cirrus SD-OCT devices. Peripapillary pRNFL and GCIPL thicknesses were measured on one or both devices. Automated segmentation protocols, in conjunction with manual inspection and correction of lines delineating retinal layers, were used. A conversion equation was developed using structural equation modeling, accounting for clustering, with healthy control data from one site where participants were scanned on both devices on the same day. Normative values were evaluated, with the entire cohort, for pRNFL and GCIPL thicknesses for each decade of age, by sex, and across racial groups using generalized estimating equation (GEE) models, accounting for clustering and adjusting for within-patient, intereye correlations. Change-point analyses were performed to determine at what age pRNFL and GCIPL thicknesses exhibit accelerated rates of decline. RESULTS:The healthy control cohort (n = 546) was 54% male and had a wide distribution of ages, ranging from 18 to 87 years, with a mean (SD) age of 39.3 (14.6) years. Based on 346 control participants at a single site, the conversion equation for pRNFL was Cirrus = -5.0 + (1.0 × Spectralis global value). Based on 228 controls, the equation for GCIPL was Cirrus = -4.5 + (0.9 × Spectralis global value). Standard error was 0.02 for both equations. After the age of 40 years, there was a decline of -2.4 μm per decade in pRNFL thickness ( P < 0.001, GEE models adjusting for sex, race, and country) and -1.4 μm per decade in GCIPL thickness ( P < 0.001). There was a small difference in pRNFL thickness based on sex, with female participants having slightly higher thickness (2.6 μm, P = 0.003). There was no association between GCIPL thickness and sex. Likewise, there was no association between race/ethnicity and pRNFL or GCIPL thicknesses. CONCLUSIONS:A conversion factor may be required when using data that are derived between different SD-OCT platforms in clinical trials and observational studies; this is particularly true for smaller cross-sectional studies or when a consistent segmentation algorithm is not available. The above conversion equations can be used when pooling data from Spectralis and Cirrus SD-OCT devices for pRNFL and GCIPL thicknesses. A faster decline in retinal thickness may occur after the age of 40 years, even in the absence of significant differences across racial groups.

BACKGROUND:Post-acute sequelae of COVID-19 (PASC) includes a heterogeneous group of patients with variable symptomatology, who may respond to different therapeutic interventions. Identifying phenotypes of PASC and therapeutic strategies for different subgroups would be a major step forward in management. METHODS:In a prospective cohort study of patients hospitalized with COVID-19, 12-month symptoms and quantitative outcome metrics were collected. Unsupervised hierarchical cluster analyses were performed to identify patients with: (1) similar symptoms lasting ≥4 weeks after acute SARS-CoV-2 infection, and (2) similar therapeutic interventions. Logistic regression analyses were used to evaluate the association of these symptom and therapy clusters with quantitative 12-month outcome metrics (modified Rankin Scale, Barthel Index, NIH NeuroQoL). RESULTS:Among 242 patients, 122 (50%) reported ≥1 PASC symptom (median 3, IQR 1-5) lasting a median of 12-months (range 1-15) post-COVID diagnosis. Cluster analysis generated three symptom groups: Cluster1 had few symptoms (most commonly headache); Cluster2 had many symptoms including high levels of anxiety and depression; and Cluster3 primarily included shortness of breath, headache and cognitive symptoms. Cluster1 received few therapeutic interventions (OR 2.6, 95% CI 1.1-5.9), Cluster2 received several interventions, including antidepressants, anti-anxiety medications and psychological therapy (OR 15.7, 95% CI 4.1-59.7) and Cluster3 primarily received physical and occupational therapy (OR 3.1, 95%CI 1.3-7.1). The most severely affected patients (Symptom Cluster 2) had higher rates of disability (worse modified Rankin scores), worse NeuroQoL measures of anxiety, depression, fatigue and sleep disorder, and a higher number of stressors (all P<0.05). 100% of those who received a treatment strategy that included psychiatric therapies reported symptom improvement, compared to 97% who received primarily physical/occupational therapy, and 83% who received few interventions (P = 0.042). CONCLUSIONS:We identified three clinically relevant PASC symptom-based phenotypes, which received different therapeutic interventions with varying response rates. These data may be helpful in tailoring individual treatment programs.

PURPOSE/OBJECTIVE:To describe cases of unilateral cone-rod dysfunction presenting in two middle-aged females. METHODS:This case series highlights two middle-aged female patients with progressive visual decline in one eye. Fundus photography, fundus autofluorescence (FAF), spectral-domain optical coherence tomography (SD-OCT), multi-focal electroretinogram (mfERG), full-field electroretinogram(ffERG), and genetic testing were obtained. RESULTS:In the first patient, mfERG showed an extinguished response and ffERG demonstrated markedly reduced a-wave and b-wave amplitudes (more pronounced under photopic conditions) in the right eye. SD-OCT showed attenuation of the ellipsoid zone of the right eye. Similar findings were appreciated in the second patient. Genetic testing in the first patient identified three heterozygous variants in PRPH2, RCBTB1, and USH2A. The second patient was found to have heterozygous variants in BBS1 and ABCA4. CONCLUSION/CONCLUSIONS:These two cases add to the literature of case reports of unilateral cone-rod and rod-cone dystrophies. However, the underlying etiology of the unilateral pattern of cone-rod dysfunction and the significance of the heterozygous mutations found in both cases remains uncertain.

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).

One sentence summary: The purpose of this investigation was to expand the evidence base on CITs delivered by telehealth by evaluating CIT use in patients who presented to a large urban tertiary care neurology practice and to examine predictors of CIT use during the pandemic.
Background(s): Patients with neurological disorders may seek treatment options in addition to those recommended by their providers. Prior to the COVID-19 pandemic, about half of patients from populations that sought care in neurology tried complementary and integrative therapies (CITs). Given the reductions in in-person visits and the increases in teleneurology visits, we sought to determine whether patients increased their use of virtual complementary and integrative therapies.
Method(s): By examining two separate datasets that included cohorts of patients with neurological disorders, we assessed patients' use of virtual (and non-virtual) CITs and determined whether there were clinical characteristics that predicted their use. The two studies that comprised this report included one that examined patient and provider experiences with teleneurology visits, and another that assessed patients with a history of COVID-19 infection who presented for neurologic evaluation.
Result(s): Patients who postponed medical treatment for non-COVID- 19- related problems during the pandemic were more likely to seek CITs. Virtual exercise, virtual psychotherapy and relaxation/meditation smartphone applications were the most frequent types of virtual CITs chosen by patients. In both studies, age was a key demographic factor associated with mobile/ virtual CIT usage.
Conclusion(s): Data from our investigations demonstrated that, in addition to its other roles in teleneurology, CIT-related technologies might be utilized in the treatment of neurologic conditions

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.