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  • 1
    Publication Date: 2021-09-02
    Description: Background Most current evidence on risk factors for hospitalization because of coronavirus disease 2019 (COVID-19) comes from studies using data abstracted primarily from electronic health records, limited to specific populations, or that fail to capture over-the-counter medications and adjust for potential confounding factors. Properly understanding risk factors for hospitalization will help improve clinical management and facilitate targeted prevention messaging and forecasting and prioritization of clinical and public health resource needs. Objectives To identify risk factors for hospitalization using patient questionnaires and chart abstraction. Methods We randomly selected 600 of 1,738 laboratory-confirmed Colorado COVID-19 cases with known hospitalization status and illness onset during March 9–31, 2020. In April 2020, we collected demographics, social history, and medications taken in the 30 days before illness onset via telephone questionnaire and collected underlying medical conditions in patient questionnaires and medical record abstraction. Results Overall, 364 patients participated; 128 were hospitalized and 236 were non-hospitalized. In multivariable analysis, chronic hypoxemic respiratory failure with oxygen requirement (adjusted odds ratio [aOR] 14.64; 95% confidence interval [CI] 1.45–147.93), taking opioids (aOR 8.05; CI 1.16–55.77), metabolic syndrome (aOR 5.71; CI 1.18–27.54), obesity (aOR 3.35; CI 1.58–7.09), age ≥65 years (aOR 3.22; CI 1.20–7.97), hypertension (aOR 3.14; CI 1.47–6.71), arrhythmia (aOR 2.95; CI 1.00–8.68), and male sex (aOR 2.65; CI 1.44–4.88), were significantly associated with hospitalization. Conclusion We identified patient characteristics, medications, and medical conditions, including some novel ones, associated with hospitalization. These data can be used to inform clinical and public health resource needs.
    Electronic ISSN: 1932-6203
    Topics: Medicine , Natural Sciences in General
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  • 2
    Publication Date: 2021-09-24
    Description: Objectives Some studies suggested more COVID-19-associated hospitalizations among racial and ethnic minorities. To inform public health practice, the COVID-19-associated Hospitalization Surveillance Network (COVID-NET) quantified associations between race/ethnicity, census tract socioeconomic indicators, and COVID-19-associated hospitalization rates. Methods Using data from COVID-NET population-based surveillance reported during March 1–April 30, 2020 along with socioeconomic and denominator data from the US Census Bureau, we calculated COVID-19-associated hospitalization rates by racial/ethnic and census tract-level socioeconomic strata. Results Among 16,000 COVID-19-associated hospitalizations, 34.8% occurred among non-Hispanic White (White) persons, 36.3% among non-Hispanic Black (Black) persons, and 18.2% among Hispanic or Latino (Hispanic) persons. Age-adjusted COVID-19-associated hospitalization rate were 151.6 (95% Confidence Interval (CI): 147.1–156.1) in census tracts with 〉15.2%–83.2% of persons living below the federal poverty level (high-poverty census tracts) and 75.5 (95% CI: 72.9–78.1) in census tracts with 0%–4.9% of persons living below the federal poverty level (low-poverty census tracts). Among White, Black, and Hispanic persons living in high-poverty census tracts, age-adjusted hospitalization rates were 120.3 (95% CI: 112.3–128.2), 252.2 (95% CI: 241.4–263.0), and 341.1 (95% CI: 317.3–365.0), respectively, compared with 58.2 (95% CI: 55.4–61.1), 304.0 (95%: 282.4–325.6), and 540.3 (95% CI: 477.0–603.6), respectively, in low-poverty census tracts. Conclusions Overall, COVID-19-associated hospitalization rates were highest in high-poverty census tracts, but rates among Black and Hispanic persons were high regardless of poverty level. Public health practitioners must ensure mitigation measures and vaccination campaigns address needs of racial/ethnic minority groups and people living in high-poverty census tracts.
    Electronic ISSN: 1932-6203
    Topics: Medicine , Natural Sciences in General
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