Faculty Bibliography

OBJECTIVE:To outline changes made to a neurology residency program in response to coronavirus disease 2019 (COVID-19). METHODS:In early March 2020, the first cases of COVID-19 were announced in the United States. New York City quickly became the epicenter of a global pandemic, and our training program needed to rapidly adapt to the increasing number of inpatient cases while being mindful of protecting providers and continuing education. Many of these changes unfolded over days, including removing residents from outpatient services, minimizing the number of residents on inpatient services, deploying residents to medicine services and medical intensive care units, converting continuity clinic patient visits to virtual options, transforming didactics to online platforms only, and maintaining connectedness in an era of social distancing. We have been able to accomplish this through daily virtual meetings among leadership, faculty, and residents. RESULTS:Over time, our program has successfully rolled out initiatives to service the growing number of COVID-related inpatients while maintaining neurologic care for those in need and continuing our neurologic education curriculum. CONCLUSION/CONCLUSIONS:It has been necessary and feasible for our residency training program to undergo rapid structural changes to adapt to a medical crisis. The key ingredients in doing this successfully have been flexibility and teamwork. We suspect that many of the implemented changes will persist long after the COVID-19 crisis has passed and will change the approach to neurologic and medical training.

The COVID-19 pandemic is causing world-wide social dislocation, operational and economic dysfunction, and high rates of morbidity and mortality. Medical practices are responding by developing, disseminating and implementing unprecedented changes in health care delivery. Telemedicine has rapidly moved to the frontline of clinical practice due to the need for prevention and mitigation strategies; these have been encouraged, facilitated, and enabled by changes in government rules and regulations and payer-driven reimbursement policies.We describe our neurology department's situational transformation from in-person outpatient visits to a largely virtual neurology practice in response to the COVID-19 pandemic. Two key factors enabled our rapid deployment of virtual encounters in neurology and its subspecialties. The first was a well-established robust information technology infrastructure supporting virtual urgent care services at our institution; this connected physicians directly to patients using both the physician's and the patient's own mobile devices. The second is the concept of one patient, one chart, facilitated by a suite of interconnected electronic medical record (EMR) applications on several different device types.We present our experience with conducting general teleneurology encounters using secure synchronous audio and video connections integrated with an EMR. This report also details how we perform virtual neurological examinations that are clinically meaningful, and how we document, code and bill for these virtual services. Many of these processes can be used by other neurology providers, regardless of their specific practice model. We then discuss potential roles for teleneurology after the COVID-19 global pandemic has been contained.

OBJECTIVE:Tests of rapid automatized naming (RAN) have been used for decades to evaluate neurological conditions. RAN tests require extensive brain pathways involving visual perception, memory, eye movements and language. To the extent that different naming tasks capture varied visual pathways and related networks, we developed the Staggered Uneven Number (SUN) test of rapid number naming to complement existing RAN tests, such as the Mobile Universal Lexicon Evaluation System (MULES). The purpose of this investigation was to determine values for time scores for SUN, and to compare test characteristics between SUN and MULES. METHODS:We administered the SUN and MULES tests to healthy adult volunteers in a research office setting. MULES consists of 54 color photographs; the SUN includes 145 single- and multi-digit numbers. Participants are asked to name each number or picture aloud. RESULTS: = 0.43, P = .001). Learning effects between first and second trials were greater for the MULES; participants improved (reduced) their time scores between trials by 5% on SUN and 16% for MULES (P < .0001, Wilcoxon signed-rank test). CONCLUSION/CONCLUSIONS:The SUN is a new vision-based test that complements presently available picture- and number-based RAN tests. These assessments may require different brain pathways and networks for visual processing, visual memory, language and eye movements.

OBJECTIVE:To investigate the incidence and spectrum of neuroimaging findings and their prognostic role in hospitalized COVID-19 patients in New York City. METHODS:This is a retrospective cohort study of 3218 COVID-19 confirmed patients admitted to a major healthcare system (three hospitals) in New York City between March 1, 2020 and April 13, 2020. Clinical data were extracted from electronic medical records, and particularly data of all neurological symptoms were extracted from the imaging reports. Four neuroradiologists evaluated all neuroimaging studies for acute neuroimaging findings related to COVID-19. RESULTS:14.1% of admitted COVID-19 patients had neuroimaging and this accounted for only 5.5% of the total imaging studies. Acute stroke was the most common finding on neuro-imaging, seen in 92.5% of patients with positive neuro-imaging studies, and present in 1.1% of hospitalized COVID-19 patients. Patients with acute large ischemic and hemorrhagic stroke had much higher mortality risk adjusted for age, BMI and hypertension compared to those COVID-19 patients without neuroimaging. (Odds Ratio 6.02 by LR; Hazard Ratio 2.28 by CRR). CONCLUSIONS:Our study demonstrates acute stroke is the most common neuroimaging finding among hospitalized COVID-19 patients. Detection of an acute stroke is a strong prognostic marker of poor outcome. Our study also highlights the fact there is limited use of neuroimaging in these patients due to multiple logistical constraints.