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Antimicrob Steward Healthc Epidemiol ; 2(1): e199, 2022.
Article in English | MEDLINE | ID: covidwho-2159991
Infect Control Hosp Epidemiol ; 42(2): 228-229, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-2096442


Coronavirus disease 2019 (COVID-19) has migrated to regions that were initially spared, and it is likely that different populations are currently at risk for illness. Herein, we present our observations of the change in characteristics and resource use of COVID-19 patients over time in a national system of community hospitals to help inform those managing surge planning, operational management, and future policy decisions.

COVID-19/epidemiology , COVID-19/therapy , Hospitalization/statistics & numerical data , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19/ethnology , COVID-19/mortality , Female , Hispanic or Latino/statistics & numerical data , Hospitals, Community , Humans , Male , Middle Aged , SARS-CoV-2/isolation & purification , Virginia/epidemiology , Young Adult
Clin Infect Dis ; 74(6): 1112-1116, 2022 03 23.
Article in English | MEDLINE | ID: covidwho-1709475


Whereas randomized clinical trials remain the gold standard for evaluating new therapies for infections, we argue that registries and observational studies early in the coronavirus disease 2019 (COVID-19) pandemic provided invaluable understanding of the natural history and preliminary data on risk factors and possible treatments. We review the data from the current pandemic, the history of registries in general, and their value in public health emergencies. Lessons from these experiences should be incorporated into rigorous planning for the next pandemic.

COVID-19 , Pandemics , Humans , Public Health , Registries , SARS-CoV-2
Infect Control Hosp Epidemiol ; 42(4): 399-405, 2021 04.
Article in English | MEDLINE | ID: covidwho-806030


OBJECTIVE: To determine risk factors for mortality among COVID-19 patients admitted to a system of community hospitals in the United States. DESIGN: Retrospective analysis of patient data collected from the routine care of COVID-19 patients. SETTING: System of >180 acute-care facilities in the United States. PARTICIPANTS: All admitted patients with positive identification of COVID-19 and a documented discharge as of May 12, 2020. METHODS: Determination of demographic characteristics, vital signs at admission, patient comorbidities and recorded discharge disposition in this population to construct a logistic regression estimating the odds of mortality, particular for those patients characterized as not being critically ill at admission. RESULTS: In total, 6,180 COVID-19+ patients were identified as of May 12, 2020. Most COVID-19+ patients (4,808, 77.8%) were admitted directly to a medical-surgical unit with no documented critical care or mechanical ventilation within 8 hours of admission. After adjusting for demographic characteristics, comorbidities, and vital signs at admission in this subgroup, the largest driver of the odds of mortality was patient age (OR, 1.07; 95% CI, 1.06-1.08; P < .001). Decreased oxygen saturation at admission was associated with increased odds of mortality (OR, 1.09; 95% CI, 1.06-1.12; P < .001) as was diabetes (OR, 1.57; 95% CI, 1.21-2.03; P < .001). CONCLUSIONS: The identification of factors observable at admission that are associated with mortality in COVID-19 patients who are initially admitted to non-critical care units may help care providers, hospital epidemiologists, and hospital safety experts better plan for the care of these patients.

COVID-19/pathology , Vital Signs , Age Factors , Aged , Aged, 80 and over , COVID-19/mortality , Female , Humans , Logistic Models , Male , Middle Aged , Oxygen/blood , Patient Admission/statistics & numerical data , Retrospective Studies , Risk Factors , United States/epidemiology