Surge Capacity in the COVID-19 Era: a Natural Experiment of Neurocritical Care in General Critical Care.

BACKGROUND: COVID-19 surges led to significant challenges in ensuring critical care capacity. In response, some centers leveraged neurocritical care (NCC) capacity as part of the surge response, with neurointensivists providing general critical care for patients with COVID-19 without neurologic illness. The relative outcomes of NCC critical care management of patients with COVID-19 remain unclear and may help guide further surge planning and provide broader insights into general critical care provided in NCC units. METHODS: We performed an observational cohort study of all patients requiring critical care for COVID-19 across four hospitals within the Emory Healthcare system during the first three surges. Patients were categorized on the basis of admission to intensive care units (ICUs) staffed by general intensivists or neurointensivists. Patients with primary neurological diagnoses were excluded. Baseline demographics, clinical complications, and outcomes were compared between groups using univariable and propensity score matching statistics. RESULTS: A total of 1141 patients with a primary diagnosis of COVID-19 required ICU admission. ICUs were staffed by general intensivists (n = 1071) or neurointensivists (n = 70). Baseline demographics and presentation characteristics were similar between groups, except for patients admitted to neurointensivist-staffed ICUs being younger (59 vs. 65, p = 0.027) and having a higher PaO2/FiO2 ratio (153 vs. 120, p = 0.002). After propensity score matching, there was no correlation between ICU staffing and the use of mechanical ventilation, renal replacement therapy, and vasopressors. The rates of in-hospital mortality and hospice disposition were similar in neurointensivist-staffed COVID-19 units (odds ratio 0.9, 95% confidence interval 0.31-2.64, p = 0.842). CONCLUSIONS: COVID-19 surges precipitated a natural experiment in which neurology-trained neurointensivists provided critical care in a comparable context to general intensivists treating the same disease. Neurology-trained neurointensivists delivered comparable outcomes to those of general ICUs during COVID-19 surges. These results further support the role of NCC in meeting general critical care needs of neurocritically ill patients and as a viable surge resource in general critical care.

Adaptive resources allocation CUSUM for binomial count data monitoring with application to COVID-19 hotspot detection

In this paper, we present an efficient statistical method (denoted as 'Adaptive Resources Allocation CUSUM') to robustly and efficiently detect the hotspot with limited sampling resources. Our main idea is to combine the multi-arm bandit (MAB) and change-point detection methods to balance the exploration and exploitation of resource allocation for hotspot detection. Further, a Bayesian weighted update is used to update the posterior distribution of the infection rate. Then, the upper confidence bound (UCB) is used for resource allocation and planning. Finally, CUSUM monitoring statistics to detect the change point as well as the change location. For performance evaluation, we compare the performance of the proposed method with several benchmark methods in the literature and showed the proposed algorithm is able to achieve a lower detection delay and higher detection precision. Finally, this method is applied to hotspot detection in a real case study of county-level daily positive COVID-19 cases in Washington State WA) and demonstrates the effectiveness with very limited distributed samples.