ABSTRACT
Introduction: Coronavirus Disease 2019 (COVID-19) is associated with an increased risk of stroke and worse stroke outcomes. A clinical score that can identify high-risk patients could enable closer monitoring and targeted preventative strategies. Methods: We used data from the AHA's COVID-19 CVD Registry to create a clinical score to predict the risk of stroke among patients hospitalized with COVID-19. We included patients aged >18 years who were hospitalized with COVID-19 at 122 centers from March 2020-March 2021. To build our score, we used demographics, preexisting comorbidities, home medications, and vital sign and lab values at admission. The outcome was a cerebrovascular event, defined as any ischemic or hemorrhagic stroke, TIA, or cerebral vein thrombosis. We used two separate analytical approaches to build the score. First, we used Cox regression with cross validation techniques to identify factors associated with the outcome in both univariable (p<0.10) and multivariable analyses (p<0.05), then assigned points for each variable based on corresponding coefficients. Second, we used regularized Cox regression, XGBoost, and Random Forest machine learning techniques to create an estimator using all available covariates. We used Harrel's C-statistic to measure discriminatory performance. Results: Among 21,420 patients hospitalized with COVID-19 (mean age 61 years, 54% men), 312 (1.5%) had a cerebrovascular event. Using traditional Cox regression, we created and internally validated a risk stratification score (CANDLE) (Fig) with a C-statistic of 0.66 (95% CI, 0.60-0.72). The machine learning estimator had similar discriminatory performance, with a C-statistic of 0.69 (95% CI, 0.65-0.72). For ischemic stroke or TIA, CANDLE's C-statistic was 0.67 (95% 0.59-0.76). Conclusion: We developed an easy-to-use clinical score, with similar performance to a machine learning estimator, to help stratify stroke risk among patients hospitalized with COVID-19.
ABSTRACT
Introduction: Reductions in hospital visits for stroke have been seen during the COVID-19 pandemic, partly reflecting perceived risks of in-hospital care. We recently implemented an evidence-based protocol for outpatient rapid evaluation of transient and minor, non-disabling stroke symptoms for patients seeking care 24 hours after symptom onset. We present our early experience through the pandemic. Methods: We conducted a retrospective review of patients evaluated in the RESCUE-TIA (Rapid Evaluation of minor Stroke and CerebrovascUlar Events including TIA) clinic from December 2019- August 2020. The clinic sees patients with TIA symptoms or with fixed, non-disabling deficits seeking care > 24 hours after symptom onset. We introduced telemedicine in March 2020. Magnetic resonance brain and vascular imaging is available within 24 hours of visit. We summarized patient characteristics and quality data with standard descriptive statistics. Results: A total of 21 patients were seen in the RESCUE-TIA clinic, including 15 patients during the height of the pandemic in NY;67% were seen by telemedicine. The median age was 75 years (interquartile range [IQR], 61-82), and 71% were women. The median NIH Stroke Score for patients with minor stroke was 0 (IQR, 0-1), and the median ABCD score for TIA patients was 3 (IQR, 2-3). Median time from symptom onset to evaluation was 3 days (IQR, 2.5-17.5). Median time from evaluation to laboratory diagnostics was 8 hours (IQR, 2-21), and to completion of imaging was 1 day (IQR, 0-5). Outpatient telemetry commenced in a median of 5 days (IQR, 1-9), and echocardiography was completed in a median of 8 days (IQR, 0-10). One patient was referred to the emergency room for a carotid occlusion. Final diagnoses were TIA (n=12), ischemic stroke (n=5), transient global amnesia (n=2), migraine (n=1), and non-aneurysmal, distal subarachnoid hemorrhage (n=1). Secondary prevention was initiated or optimized in 94% of TIA and stroke patients. Recurrent TIA occurred in 1 patient after 67 days, and ischemic stroke occurred in 1 patient 55 days after TIA. Conclusion: Timely outpatient evaluation of patients with recent TIA and minor, non-disabling stroke is feasible and may be useful during the pandemic, especially during emergency room crowding.
ABSTRACT
BACKGROUND AND PURPOSE: A large spectrum of neurologic disease has been reported in patients with coronavirus disease 2019 (COVID-19) infection. Our aim was to investigate the yield of neuroimaging in patients with COVID-19 undergoing CT or MR imaging of the brain and to describe associated imaging findings. MATERIALS AND METHODS: We performed a retrospective cohort study involving 2054 patients with laboratory-confirmed COVID-19 presenting to 2 hospitals in New York City between March 4 and May 9, 2020, of whom 278 (14%) underwent either CT or MR imaging of the brain. All images initially received a formal interpretation from a neuroradiologist within the institution and were subsequently reviewed by 2 neuroradiologists in consensus, with disputes resolved by a third neuroradiologist. RESULTS: The median age of these patients was 64 years (interquartile range, 50-75 years), and 43% were women. Among imaged patients, 58 (21%) demonstrated acute or subacute neuroimaging findings, the most common including cerebral infarctions (11%), parenchymal hematomas (3.6%), and posterior reversible encephalopathy syndrome (1.1%). Among the 51 patients with MR imaging examinations, 26 (51%) demonstrated acute or subacute findings; notable findings included 6 cases of cranial nerve abnormalities (including 4 patients with olfactory bulb abnormalities) and 3 patients with a microhemorrhage pattern compatible with critical illness-associated microbleeds. CONCLUSIONS: Our experience confirms the wide range of neurologic imaging findings in patients with COVID-19 and suggests the need for further studies to optimize management for these patients.