Epidemiological Surveillance of the Impact of the COVID-19 Pandemic on Stroke Care Using Artificial Intelligence.

BACKGROUND AND PURPOSE: The degree to which the coronavirus disease 2019 (COVID-19) pandemic has affected systems of care, in particular, those for time-sensitive conditions such as stroke, remains poorly quantified. We sought to evaluate the impact of COVID-19 in the overall screening for acute stroke utilizing a commercial clinical artificial intelligence platform. METHODS: Data were derived from the Viz Platform, an artificial intelligence application designed to optimize the workflow of patients with acute stroke. Neuroimaging data on suspected patients with stroke across 97 hospitals in 20 US states were collected in real time and retrospectively analyzed with the number of patients undergoing imaging screening serving as a surrogate for the amount of stroke care. The main outcome measures were the number of computed tomography (CT) angiography, CT perfusion, large vessel occlusions (defined according to the automated software detection), and severe strokes on CT perfusion (defined as those with hypoperfusion volumes >70 mL) normalized as number of patients per day per hospital. Data from the prepandemic (November 4, 2019 to February 29, 2020) and pandemic (March 1 to May 10, 2020) periods were compared at national and state levels. Correlations were made between the inter-period changes in imaging screening, stroke hospitalizations, and thrombectomy procedures using state-specific sampling. RESULTS: A total of 23 223 patients were included. The incidence of large vessel occlusion on CT angiography and severe strokes on CT perfusion were 11.2% (n=2602) and 14.7% (n=1229/8328), respectively. There were significant declines in the overall number of CT angiographies (-22.8%; 1.39-1.07 patients/day per hospital, P<0.001) and CT perfusion (-26.1%; 0.50-0.37 patients/day per hospital, P<0.001) as well as in the incidence of large vessel occlusion (-17.1%; 0.15-0.13 patients/day per hospital, P<0.001) and severe strokes on CT perfusion (-16.7%; 0.12-0.10 patients/day per hospital, P<0.005). The sampled cohort showed similar declines in the rates of large vessel occlusions versus thrombectomy (18.8% versus 19.5%, P=0.9) and comprehensive stroke center hospitalizations (18.8% versus 11.0%, P=0.4). CONCLUSIONS: A significant decline in stroke imaging screening has occurred during the COVID-19 pandemic. This analysis underscores the broader application of artificial intelligence neuroimaging platforms for the real-time monitoring of stroke systems of care.

Determining the Optimal Cognitive Screening Tool in Older People With Diabetes.

Background: Self-care is an important perspective to aging and transitional states in diabetes management. Population studies have shown that lower cognitive function is associated with worse self-care abilities. Several guidelines have emphasized the importance of assessing cognitive function in older people with diabetes and tailoring treatment plan accordingly. Those guidelines do not specify which tools are the most appropriate for this population. One approach to delineate which tools should be used is to assess which tools best correlate with self-care capacity. Objective: To assess which cognitive assessment tools best correlate with self-care capacity in older people with type 2 diabetes. Methods: Cross-sectional study, conducted amongst individuals with diabetes over the age of 60. The association between self-care capacity indices and different cognitive assessment tools was examined. Principal Component self-care constructs were determined and the association between these and the different cognitive assessment tools was examined. Results: A significant association was found between the Principal Component self-care construct and the Montreal Cognitive Assessment and MindstreamsTM scores. In a stepwise regression model including only the Montreal Cognitive Assessment score, a significant association was found between this score and the Principal Component self-care construct. The same was not found in a model that included only the MindstreamsTM scores. Conclusions: The Montreal Cognitive Assessment, previously validated as a brief cognitive screening tool, may be useful as an adjunct to assess the self-care capacity of older individuals with diabetes. Future studies in the clinic are needed to evaluate if using this tool may improve treatment plans.

Supporting a comprehensive and coordinated evaluation of the elderly with diabetes by integrating cognitive and physical assessment in the evaluation process.

BACKGROUND: Successful ageing with diabetes is challenged by co-morbidities, which may present barriers to self-care. Currently, measurement of physical and cognitive status is not part of routine care of the older person with diabetes, and these are not taken into account when devising the treatment plan. OBJECTIVE: To describe a novel approach that integrates cognitive and physical assessment into the routine evaluation of the older person with diabetes and the tailor-made treatment plan devised accordingly. To provide estimates of the relative contribution of cognitive and physical disabilities in this population. METHODS: Cognitive and physical assessments were added to the standard evaluation. A composite measure of cognitive and of physical status categorizing each individual to intact, mild, or severe impairment was generated. In addition, all recommendations provided were categorized and tabulated. RESULTS: Of 119 individuals, over the age of 60 with type 2 diabetes who were referred because of difficulties in managing their disease, 16% and 3% of individuals met the criteria for severe cognitive/physical impairment, respectively, and 42% and 21% met the criteria for mild cognitive/physical impairment; 72%, 12.5%, 61% received recommendations related to intensification of physical activity, cognitive treatment, change in pharmacological agents, respectively. 25% were referred for further emotional treatment. CONCLUSIONS: These data suggest that a substantial proportion of individuals with diabetes over the age of 60 may have cognitive/physical impairment. It highlights the importance of measuring these as part of the multidisciplinary evaluation and being able to provide a tailor made treatment plan.