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1.
Front Neurol ; 12: 702927, 2021.
Article in English | MEDLINE | ID: covidwho-1337657

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) has been associated with coagulopathy, and D-dimer levels have been used to predict disease severity. However, the role of D-dimer in predicting mortality in COVID-19 patients with acute ischemic stroke (AIS) remains incompletely characterized. Methods: We conducted a retrospective cohort study using the Optum® de-identified COVID-19 Electronic Health Record dataset. Patients were included if they were 18 or older, had been hospitalized within 7 days of confirmed COVID-19 positivity from March 1, 2020 to November 30, 2020. We determined the optimal threshold of D-dimer to predict in-hospital mortality and compared risks of in-hospital mortality between patients with D-dimer levels below and above the cutoff. Risk ratios (RRs) were estimated adjusting for baseline characteristics and clinical variables. Results: Among 15,250 patients hospitalized with COVID-19 positivity, 285 presented with AIS at admission (2%). Patients with AIS were older [70 (60-79) vs. 64 (52-75), p < 0.001] and had greater D-dimer levels at admission [1.42 (0.76-3.96) vs. 0.94 (0.55-1.81) µg/ml FEU, p < 0.001]. Peak D-dimer level was a good predictor of in-hospital mortality among all patients [c-statistic 0.774 (95% CI 0.764-0.784)] and among patients with AIS [c-statistic 0.751 (95% CI 0.691-0.810)]. Among AIS patients, the optimum cutoff was identified at 5.15 µg/ml FEU with 73% sensitivity and 69% specificity. Elevated peak D-dimer level above this cut-off was associated with almost 3 times increased mortality [adjusted RR 2.89 (95% CI 1.87-4.47), p < 0.001]. Conclusions: COVID-19 patients with AIS present with greater D-dimer levels. Thresholds for outcomes prognostication should be higher in this population.

2.
J Community Health ; 45(4): 696-701, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-526762

ABSTRACT

The pandemic of novel Coronavirus (SARS-CoV-2) is currently spreading rapidly across the United States. We provide a comprehensive overview of COVID-19 epidemiology across the state of Texas, which includes vast rural & vulnerable communities that may be disproportionately impacted by the spread of this new disease. All 254 Texas counties were included in this study. We examined the geographic variation of COVID-19 from March 1 through April 8, 2020 by extracting data on incidence and case fatality from various national and state datasets. We contrasted incidence and case fatality rates by county-level demographic and healthcare resource factors. Counties which are part of metropolitan regions, such as Harris and Dallas, experienced the highest total number of confirmed cases. However, the highest incidence rates per 100,000 population were in found in counties of Donley (353.5), Castro (136.4), Matagorda (114.4) and Galveston (93.4). Among counties with greater than 10 cases, the highest CFR were observed in counties of Comal (10.3%), Hockley (10%), Hood (10%), and Castro (9.1%). Counties with the highest CFR (> 10%) had a higher proportion of non-Hispanic Black residents, adults aged 65 and older, and adults smoking, but lower number of ICU beds per 100,000 population, and number of primary care physicians per 1000 population. Although the urban areas of Texas account for the majority of COVID-19 cases, the higher case-fatality rates and low health care capacity in rural areas need attention.


Subject(s)
Coronavirus Infections/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , COVID-19 , Coronavirus Infections/mortality , Coronavirus Infections/transmission , Humans , Incidence , Mortality , Pneumonia, Viral/mortality , Pneumonia, Viral/transmission , Rural Population/statistics & numerical data , Texas/epidemiology , Urban Population/statistics & numerical data
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