Faculty Bibliography

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:Early neurorehabilitation improves outcomes in patients with disorders of consciousness (DoC) after brain injury, but its applicability in COVID-19 is unknown. We describe our experience implementing an early neurorehabilitation protocol for patients with COVID-19-associated DoC in the intensive care unit (ICU) and evaluate factors associated with recovery. METHODS:During the initial COVID-19 surge in New York City between March 10 and May 20, 2020, faced with a disproportionately high number of ICU patients with prolonged unresponsiveness, we developed and implemented an early neurorehabilitation protocol, applying standard practices from brain injury rehabilitation care to the ICU setting. Twenty-one patients with delayed recovery of consciousness after severe COVID-19 participated in a pilot early neurorehabilitation program that included serial Coma Recovery Scale-Revised (CRS-R) assessments, multimodal treatment, and access to clinicians specializing in brain injury medicine. We retrospectively compared clinical features of patients who did and did not recover to the minimally conscious state (MCS) or better, defined as a CRS-R total score (TS) ≥ 8, before discharge. We additionally examined factors associated with best CRS-R TS, last CRS-R TS, hospital length of stay, and time on mechanical ventilation. RESULTS:Patients underwent CRS-R assessments a median of six (interquartile range [IQR] 3-10) times before discharge, beginning a median of 48 days (IQR 40-55) from admission. Twelve (57%) patients recovered to MCS after a median of 8 days (IQR 2-14) off continuous sedation; they had lower body mass index (p = 0.009), lower peak serum C-reactive protein levels (p = 0.023), higher minimum arterial partial pressure of oxygen (p = 0.028), and earlier fentanyl discontinuation (p = 0.018). CRS-R scores fluctuated over time, and the best CRS-R TS was significantly higher than the last CRS-R TS (median 8 [IQR 5-23] vs. 5 [IQR 3-18], p = 0.002). Earlier fentanyl (p = 0.001) and neuromuscular blockade (p = 0.015) discontinuation correlated with a higher last CRS-R TS. CONCLUSIONS:More than half of our cohort of patients with prolonged unresponsiveness following severe COVID-19 recovered to MCS or better before hospital discharge, achieving a clinical benchmark known to have relatively favorable long-term prognostic implications in DoC of other etiologies. Hypoxia, systemic inflammation, sedation, and neuromuscular blockade may impact diagnostic assessment and prognosis, and fluctuations in level of consciousness make serial assessments essential. Early neurorehabilitation of these patients in the ICU can be accomplished but is associated with unique challenges. Further research should evaluate factors associated with longer-term neurologic recovery and benefits of early rehabilitation in patients with severe COVID-19.

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.

Purpose/UNASSIGNED:To report 3 otherwise healthy patients with Herpes zoster reactivation shortly after administration of a mRNA vaccine against the novel COVID-19 virus. Observations/UNASSIGNED:Patient 1 is a 54 year old who presented with Herpes zoster meningitis complicated by enhancing nodular leptomeningeal lesions of the spinal cord. The subsequent two patients had Herpes zoster ophthalmicus of the cornea (Case 2) and eyelid (Case 3). All three presented within 2 weeks of receiving the Pfizer/BioNTech COVID-19 vaccine. Conclusions/UNASSIGNED:Herpes zoster may be a side effect of m RNA vaccination against the Sars-CoV2 vaccine and requires further investigation.

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.

BACKGROUND:Persistent cognitive symptoms have been reported following COVID-19 hospitalization. We investigated the relationship between demographics, social determinants of health (SDOH) and cognitive outcomes 6-months after hospitalization for COVID-19. METHODS:We analyzed 6-month follow-up data collected from a multi-center, prospective study of hospitalized COVID-19 patients. Demographic and SDOH variables (age, race/ethnicity, education, employment, health insurance status, median income, primary language, living arrangements, and pre-COVID disability) were compared between patients with normal versus abnormal telephone Montreal Cognitive Assessments (t-MOCA; scores<18/22). Multivariable logistic regression models were constructed to evaluate predictors of t-MoCA. RESULTS:Of 382 patients available for 6-month follow-up, 215 (56%) completed the t-MoCA (n = 109/215 [51%] had normal and n = 106/215 [49%] abnormal results). 14/215 (7%) patients had a prior history of dementia/cognitive impairment. Significant univariate predictors of abnormal t-MoCA included older age, ≤12 years of education, unemployment pre-COVID, Black race, and a pre-COVID history of cognitive impairment (all p < 0.05). In multivariable analyses, education ≤12 years (adjusted OR 5.21, 95%CI 2.25-12.09), Black race (aOR 5.54, 95%CI 2.25-13.66), and the interaction of baseline functional status and unemployment prior to hospitalization (aOR 3.98, 95%CI 1.23-12.92) were significantly associated with abnormal t-MoCA scores after adjusting for age, history of dementia, language, neurological complications, income and discharge disposition. CONCLUSIONS:Fewer years of education, Black race and unemployment with baseline disability were associated with abnormal t-MoCA scores 6-months post-hospitalization for COVID-19. These associations may be due to undiagnosed baseline cognitive dysfunction, implicit biases of the t-MoCA, other unmeasured SDOH or biological effects of SARS-CoV-2.

Background/UNASSIGNED:Prior to the COVID-19 pandemic, about half of patients from populations that sought care in neurology tried complementary and integrative therapies (CITs). With the increased utilization of telehealth services, we sought to determine whether patients also increased their use of virtual CITs. Methods/UNASSIGNED:We examined datasets from two separate cross-sectional surveys that included cohorts of patients with neurological disorders. One was a dataset from a study that examined patient and provider experiences with teleneurology visits; the other was a study that assessed patients with a history of COVID-19 infection who presented for neurologic evaluation. We assessed and reported the use of virtual (and non-virtual) CITs using descriptive statistics, and determined whether there were clinical characteristics that predicted the use of CITs using logistic regression analyses. Findings/UNASSIGNED: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. Interpretations/UNASSIGNED:Our investigation demonstrates that virtual CIT-related technologies were utilized in the treatment of neurologic conditions during the pandemic, particularly by those patients who deferred non-COVID-related care.

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