14 results on '"Browning, Sean D."'
Search Results
2. Characteristics and Risk Factors of Hospitalized and Nonhospitalized COVID-19 Patients, Atlanta, Georgia, USA, March-April 2020
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Pettrone, Kristen, Burnett, Eleanor, Link-Gelles, Ruth, Haight, Sarah C., Schrodt, Caroline, England, Lucinda, Gomes, Danica J., Shamout, Mays, O'Laughlin, Kevin, Kimball, Anne, Blau, Erin F., Ladva, Chandresh N., Szablewski, Christine M., Tobin-DAngelo, Melissa, Oosmanally, Nadine, Drenzek, Cherie, Browning, Sean D., Bruce, Beau B., Silva, Juliana da, Gold, Jeremy A.W., Jackson, Brendan R., Morris, Sapna Bamrah, Natarajan, Pavithra, Fanfair, Robyn Neblett, Patel, Priti R., Rogers- Brown, Jessica, Rossow, John, Wong, Karen K., Murphy, David J., Blum, James M., Hollberg, Julie, Lefkove, Benjamin, Brown, Frank W., Shimabukuro, Tom, Midgley, Claire M., Tate, Jacqueline E., and Killerby, Marie E.
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Epidemics -- Risk factors -- Patient outcomes -- Demographic aspects -- United States ,Health - Abstract
Information about care-seeking behavior, symptom duration, and risk factors for progression to severe illness in nonhospitalized patients with coronavirus disease (COVID-19) aids in resource planning, disease identification, risk stratification, and [...]
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- 2021
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3. Early Detection and Surveillance of the SARS-CoV-2 Variant BA.2.86--Worldwide, July-October 2023
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Lambrou, Anastasia S., South, Erin, Ballou, Eliza S., Paden, Clinton R., Fuller, James A., Bart, Stephen M., Butryn, Deena M., Novak, Ryan T., Browning, Sean D., Kirby, Amy E., Welsh, Rory M., Cornforth, Daniel M., MacCannell, Duncan R., Friedman, Cindy R., Thornburg, Natalie J., Hall, Aron J., Hughes, Laura J., Mahon, Barbara E., Daskalakis, Demetre C., Shah, Nirav D., Jackson, Brendan R., and Kirking, Hannah L.
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Wastewater -- Health aspects ,Risk assessment -- Health aspects ,Travelers -- Health aspects ,Public health -- Health aspects ,Health - Abstract
Introduction CDC uses a diverse, multicomponent surveillance approach to track the emergence of new and potentially significant SARS-CoV-2 variants across the United States and globally. These surveillance systems include genomic, [...]
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- 2023
4. Perceived Age Discrimination: Implications for Mental Health and Life Satisfaction in Middle and Later Life—a Research Note
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Browning, Sean D., Penning, Margaret J., and Wu, Zheng
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- 2020
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5. Care-giver wellbeing: exploring gender, relationship-to-care-recipient and care-giving demands in the Canadian Longitudinal Study on Aging.
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Chappell, Neena L., Penning, Margaret, Kadlec, Helena, and Browning, Sean D.
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WELL-being ,CAREGIVER attitudes ,SERVICES for caregivers ,SOCIAL support ,BURDEN of care ,SATISFACTION ,HEALTH status indicators ,REGRESSION analysis ,SEX distribution ,SPOUSES ,COMPARATIVE studies ,SOCIOECONOMIC factors ,AGING ,PSYCHOLOGY of caregivers ,MENTAL depression ,INTERSECTIONALITY ,RESEARCH funding ,FAMILY relations ,LONGITUDINAL method - Abstract
The three-way intersection of gender, relationship-to-care-recipient and care-giving demands has not, to our knowledge, been examined in relation to the wellbeing of family care-givers. We explore inequalities in depressive symptoms and life satisfaction, comparing wives, husbands, daughters and sons providing very-intensive care (36+ hours/week) with those providing less care and disparities between these groups in the factors related to disadvantage. Data from the Canadian Longitudinal Study on Aging (N = 5,994) support the existence of differences between the groups. Very-intensive care-giving wives report the most depressive symptoms and lowest life satisfaction; less-intensive care-giving sons report the fewest depressive symptoms, and less-intensive care-giving daughters report the highest life satisfaction. However, group differences in life satisfaction disappear among very-intensive care-givers. Drawing on Intersectionality and Stress Process theories, data from regression analyses reveal a non-significant gender–relationship–demand interaction term, but, health, socio-economic and social support resources play a strong mediating role between care demand and wellbeing. Analyses of the eight groups separately reveal diversity in the care-giving experience. Among less-intensive care-givers, the mediating role of resources remains strong even as differences are evident. Among very-intensive care-givers, the role of resources is less and differences in wellbeing between the groups are magnified. Policy implications emphasise the imperative to personalise services to meet the varied needs of care-givers. [ABSTRACT FROM AUTHOR]
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- 2023
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6. Characteristics Associated with Hospitalization Among Patients with COVID-19 — Metropolitan Atlanta, Georgia, March–April 2020
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Killerby, Marie E., Link-Gelles, Ruth, Haight, Sarah C., Schrodt, Caroline A., England, Lucinda, Gomes, Danica J., Shamout, Mays, Pettrone, Kristen, O'Laughlin, Kevin, Kimball, Anne, Blau, Erin F., Burnett, Eleanor, Ladva, Chandresh N., Szablewski, Christine M., Tobin-D’Angelo, Melissa, Oosmanally, Nadine, Drenzek, Cherie, Murphy, David J., Blum, James M., Hollberg, Julie, Lefkove, Benjamin, Brown, Frank W., Shimabukuro, Tom, Midgley, Claire M., Tate, Jacqueline E., Browning, Sean D., Bruce, Beau B., da Silva, Juliana, Gold, Jeremy A.W., Jackson, Brendan R., Bamrah Morris, Sapna, Natarajan, Pavithra, Neblett Fanfair, Robyn, Patel, Priti R., Rogers-Brown, Jessica, Rossow, John, and Wong, Karen K.
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Adult ,Male ,medicine.medical_specialty ,Health (social science) ,Georgia ,Adolescent ,Epidemiology ,Health, Toxicology and Mutagenesis ,Pneumonia, Viral ,Disease ,03 medical and health sciences ,Young Adult ,0302 clinical medicine ,Health Information Management ,Risk Factors ,030225 pediatrics ,Acute care ,Diabetes mellitus ,medicine ,Outpatient clinic ,Humans ,030212 general & internal medicine ,Full Report ,Young adult ,Cities ,Pandemics ,Aged ,business.industry ,Medical record ,COVID-19 ,General Medicine ,Odds ratio ,Middle Aged ,medicine.disease ,Hospitalization ,Emergency medicine ,Female ,business ,Coronavirus Infections ,Kidney disease - Abstract
The first reported U.S. case of coronavirus disease 2019 (COVID-19) was detected in January 2020 (1). As of June 15, 2020, approximately 2 million cases and 115,000 COVID-19-associated deaths have been reported in the United States.* Reports of U.S. patients hospitalized with SARS-CoV-2 infection (the virus that causes COVID-19) describe high proportions of older, male, and black persons (2-4). Similarly, when comparing hospitalized patients with catchment area populations or nonhospitalized COVID-19 patients, high proportions have underlying conditions, including diabetes mellitus, hypertension, obesity, cardiovascular disease, chronic kidney disease, or chronic respiratory disease (3,4). For this report, data were abstracted from the medical records of 220 hospitalized and 311 nonhospitalized patients aged ≥18 years with laboratory-confirmed COVID-19 from six acute care hospitals and associated outpatient clinics in metropolitan Atlanta, Georgia. Multivariable analyses were performed to identify patient characteristics associated with hospitalization. The following characteristics were independently associated with hospitalization: age ≥65 years (adjusted odds ratio [aOR] = 3.4), black race (aOR = 3.2), having diabetes mellitus (aOR = 3.1), lack of insurance (aOR = 2.8), male sex (aOR = 2.4), smoking (aOR = 2.3), and obesity (aOR = 1.9). Infection with SARS-CoV-2 can lead to severe outcomes, including death, and measures to protect persons from infection, such as staying at home, social distancing (5), and awareness and management of underlying conditions should be emphasized for those at highest risk for hospitalization with COVID-19. Measures that prevent the spread of infection to others, such as wearing cloth face coverings (6), should be used whenever possible to protect groups at high risk. Potential barriers to the ability to adhere to these measures need to be addressed.
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- 2020
7. Care-giver wellbeing: exploring gender, relationship-to-care-recipient and care-giving demands in the Canadian Longitudinal Study on Aging
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Chappell, Neena L., primary, Penning, Margaret, additional, Kadlec, Helena, additional, and Browning, Sean D., additional
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- 2021
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8. COVID-19 Clinical Phenotypes: Presentation and Temporal Progression of Disease in a Cohort of Hospitalized Adults in Georgia, United States
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da Silva, Juliana F, primary, Hernandez-Romieu, Alfonso C, additional, Browning, Sean D, additional, Bruce, Beau B, additional, Natarajan, Pavithra, additional, Morris, Sapna B, additional, Gold, Jeremy A W, additional, Neblett Fanfair, Robyn, additional, Rogers-Brown, Jessica, additional, Rossow, John, additional, Szablewski, Christine M, additional, Oosmanally, Nadine, additional, D’Angelo, Melissa Tobin, additional, Drenzek, Cherie, additional, Murphy, David J, additional, Hollberg, Julie, additional, Blum, James M, additional, Jansen, Robert, additional, Wright, David W, additional, Sewell, William, additional, Owens, Jack, additional, Lefkove, Benjamin, additional, Brown, Frank W, additional, Burton, Deron C, additional, Uyeki, Timothy M, additional, Patel, Priti R, additional, Jackson, Brendan R, additional, and Wong, Karen K, additional
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- 2020
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9. Predictors at Admission of Mechanical Ventilation and Death in an Observational Cohort of Adults Hospitalized With Coronavirus Disease 2019
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Jackson, Brendan R, primary, Gold, Jeremy A W, additional, Natarajan, Pavithra, additional, Rossow, John, additional, Neblett Fanfair, Robyn, additional, da Silva, Juliana, additional, Wong, Karen K, additional, Browning, Sean D, additional, Bamrah Morris, Sapna, additional, Rogers-Brown, Jessica, additional, Hernandez-Romieu, Alfonso C, additional, Szablewski, Christine M, additional, Oosmanally, Nadine, additional, Tobin-D’Angelo, Melissa, additional, Drenzek, Cherie, additional, Murphy, David J, additional, Hollberg, Julie, additional, Blum, James M, additional, Jansen, Robert, additional, Wright, David W, additional, Sewell, William M, additional, Owens, Jack D, additional, Lefkove, Benjamin, additional, Brown, Frank W, additional, Burton, Deron C, additional, Uyeki, Timothy M, additional, Bialek, Stephanie R, additional, Patel, Priti R, additional, and Bruce, Beau B, additional
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- 2020
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10. Predictors at Admission of Mechanical Ventilation and Death in an Observational Cohort of Adults Hospitalized With Coronavirus Disease 2019.
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Jackson, Brendan R, Gold, Jeremy A W, Natarajan, Pavithra, Rossow, John, Fanfair, Robyn Neblett, Silva, Juliana da, Wong, Karen K, Browning, Sean D, Morris, Sapna Bamrah, Rogers-Brown, Jessica, Hernandez-Romieu, Alfonso C, Szablewski, Christine M, Oosmanally, Nadine, Tobin-D'Angelo, Melissa, Drenzek, Cherie, Murphy, David J, Hollberg, Julie, Blum, James M, Jansen, Robert, and Wright, David W
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HOSPITALS ,ANTIHYPERTENSIVE agents ,COVID-19 ,SCIENTIFIC observation ,CONFIDENCE intervals ,VITAL signs ,PATIENTS ,PUBLIC health ,RETROSPECTIVE studies ,RANDOM forest algorithms ,ARTIFICIAL respiration ,HOSPITAL admission & discharge ,HOSPITAL care ,MEDICAL records ,ODDS ratio ,LONGITUDINAL method ,ADULTS - Abstract
Background Coronavirus disease (COVID-19) can cause severe illness and death. Predictors of poor outcome collected on hospital admission may inform clinical and public health decisions. Methods We conducted a retrospective observational cohort investigation of 297 adults admitted to 8 academic and community hospitals in Georgia, United States, during March 2020. Using standardized medical record abstraction, we collected data on predictors including admission demographics, underlying medical conditions, outpatient antihypertensive medications, recorded symptoms, vital signs, radiographic findings, and laboratory values. We used random forest models to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for predictors of invasive mechanical ventilation (IMV) and death. Results Compared with age <45 years, ages 65–74 years and ≥75 years were predictors of IMV (aORs, 3.12 [95% CI, 1.47–6.60] and 2.79 [95% CI, 1.23–6.33], respectively) and the strongest predictors for death (aORs, 12.92 [95% CI, 3.26–51.25] and 18.06 [95% CI, 4.43–73.63], respectively). Comorbidities associated with death (aORs, 2.4–3.8; P < .05) included end-stage renal disease, coronary artery disease, and neurologic disorders, but not pulmonary disease, immunocompromise, or hypertension. Prehospital use vs nonuse of angiotensin receptor blockers (aOR, 2.02 [95% CI, 1.03–3.96]) and dihydropyridine calcium channel blockers (aOR, 1.91 [95% CI, 1.03–3.55]) were associated with death. Conclusions After adjustment for patient and clinical characteristics, older age was the strongest predictor of death, exceeding comorbidities, abnormal vital signs, and laboratory test abnormalities. That coronary artery disease, but not chronic lung disease, was associated with death among hospitalized patients warrants further investigation, as do associations between certain antihypertensive medications and death. [ABSTRACT FROM AUTHOR]
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- 2021
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11. COVID-19 Clinical Phenotypes: Presentation and Temporal Progression of Disease in a Cohort of Hospitalized Adults in Georgia, United States.
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Silva, Juliana F da, Hernandez-Romieu, Alfonso C, Browning, Sean D, Bruce, Beau B, Natarajan, Pavithra, Morris, Sapna B, Gold, Jeremy A W, Fanfair, Robyn Neblett, Rogers-Brown, Jessica, Rossow, John, Szablewski, Christine M, Oosmanally, Nadine, D'Angelo, Melissa Tobin, Drenzek, Cherie, Murphy, David J, Hollberg, Julie, Blum, James M, Jansen, Robert, Wright, David W, and Sewell, William
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COVID-19 ,LEUKOCYTE count ,DISEASE progression ,LYMPHOCYTE count ,MEDICAL care use - Abstract
Background The epidemiological features and outcomes of hospitalized adults with coronavirus disease 2019 (COVID-19) have been described; however, the temporal progression and medical complications of disease among hospitalized patients require further study. Detailed descriptions of the natural history of COVID-19 among hospitalized patients are paramount to optimize health care resource utilization, and the detection of different clinical phenotypes may allow tailored clinical management strategies. Methods This was a retrospective cohort study of 305 adult patients hospitalized with COVID-19 in 8 academic and community hospitals. Patient characteristics included demographics, comorbidities, medication use, medical complications, intensive care utilization, and longitudinal vital sign and laboratory test values. We examined laboratory and vital sign trends by mortality status and length of stay. To identify clinical phenotypes, we calculated Gower's dissimilarity matrix between each patient's clinical characteristics and clustered similar patients using the partitioning around medoids algorithm. Results One phenotype of 6 identified was characterized by high mortality (49%), older age, male sex, elevated inflammatory markers, high prevalence of cardiovascular disease, and shock. Patients with this severe phenotype had significantly elevated peak C-reactive protein creatinine, D-dimer, and white blood cell count and lower minimum lymphocyte count compared with other phenotypes (P < .01, all comparisons). Conclusions Among a cohort of hospitalized adults, we identified a severe phenotype of COVID-19 based on the characteristics of its clinical course and poor prognosis. These findings need to be validated in other cohorts, as improved understanding of clinical phenotypes and risk factors for their development could help inform prognosis and tailored clinical management for COVID-19. [ABSTRACT FROM AUTHOR]
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- 2021
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12. Framing Later Life Vulnerability during the COVID-19 Pandemic: A Content Analysis of Newspaper Coverage in Canada and the United States.
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Penning MJ, Browning SD, Haq KS, and Kidd B
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- Humans, Canada epidemiology, United States epidemiology, Aged, SARS-CoV-2, Pandemics, Risk Factors, Ageism psychology, COVID-19 epidemiology, Newspapers as Topic statistics & numerical data, Vulnerable Populations statistics & numerical data
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This study explores vulnerability narratives used in relation to older adults and others during the COVID-19 pandemic. A mixed-method content analysis was conducted of 391 articles published in two major newspapers in Canada and the USA during the first wave of the pandemic. The findings indicated that during the early months of the pandemic, limited attention was directed towards its impact on older adults or other 'vulnerable' subpopulations in both countries. Where evident, intrinsic (individual-level) risk factors were most consistently used to frame the vulnerability of older adults. In contrast, vulnerability was more likely to be framed as structural with regard to other subpopulations (e.g., ethno-racial minorities). These narratives also differed somewhat in Canadian and US newspapers. The framing of older adults as intrinsically vulnerable reflects ageist stereotypes and promotes downstream policy interventions. Greater attention is needed to the role of structural factors in influencing pandemic-related outcomes among older adults.
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- 2024
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13. Early Detection and Surveillance of the SARS-CoV-2 Variant BA.2.86 - Worldwide, July-October 2023.
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Lambrou AS, South E, Ballou ES, Paden CR, Fuller JA, Bart SM, Butryn DM, Novak RT, Browning SD, Kirby AE, Welsh RM, Cornforth DM, MacCannell DR, Friedman CR, Thornburg NJ, Hall AJ, Hughes LJ, Mahon BE, Daskalakis DC, Shah ND, Jackson BR, and Kirking HL
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- Humans, SARS-CoV-2 genetics, Wastewater, Wastewater-Based Epidemiological Monitoring, COVID-19
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Early detection of emerging SARS-CoV-2 variants is critical to guiding rapid risk assessments, providing clear and timely communication messages, and coordinating public health action. CDC identifies and monitors novel SARS-CoV-2 variants through diverse surveillance approaches, including genomic, wastewater, traveler-based, and digital public health surveillance (e.g., global data repositories, news, and social media). The SARS-CoV-2 variant BA.2.86 was first sequenced in Israel and reported on August 13, 2023. The first U.S. COVID-19 case caused by this variant was reported on August 17, 2023, after a patient received testing for SARS-CoV-2 at a health care facility on August 3. In the following month, eight additional U.S. states detected BA.2.86 across various surveillance systems, including specimens from health care settings, wastewater surveillance, and traveler-based genomic surveillance. As of October 23, 2023, sequences have been reported from at least 32 countries. Continued variant tracking and further evidence are needed to evaluate the full public health impact of BA.2.86. Timely genomic sequence submissions to global public databases aided early detection of BA.2.86 despite the decline in the number of specimens being sequenced during the past year. This report describes how multicomponent surveillance and genomic sequencing were used in real time to track the emergence and transmission of the BA.2.86 variant. This surveillance approach provides valuable information regarding implementing and sustaining comprehensive surveillance not only for novel SARS-CoV-2 variants but also for future pathogen threats., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.
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- 2023
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14. Characteristics and Clinical Outcomes of Adult Patients Hospitalized with COVID-19 - Georgia, March 2020.
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Gold JAW, Wong KK, Szablewski CM, Patel PR, Rossow J, da Silva J, Natarajan P, Morris SB, Fanfair RN, Rogers-Brown J, Bruce BB, Browning SD, Hernandez-Romieu AC, Furukawa NW, Kang M, Evans ME, Oosmanally N, Tobin-D'Angelo M, Drenzek C, Murphy DJ, Hollberg J, Blum JM, Jansen R, Wright DW, Sewell WM 3rd, Owens JD, Lefkove B, Brown FW, Burton DC, Uyeki TM, Bialek SR, and Jackson BR
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- Adolescent, Adult, Black or African American statistics & numerical data, Aged, Aged, 80 and over, COVID-19, Cohort Studies, Comorbidity, Coronavirus Infections ethnology, Georgia epidemiology, Hospitalization statistics & numerical data, Humans, Middle Aged, Pandemics, Pneumonia, Viral ethnology, Risk Factors, Treatment Outcome, Young Adult, Coronavirus Infections epidemiology, Coronavirus Infections therapy, Pneumonia, Viral epidemiology, Pneumonia, Viral therapy
- Abstract
SARS-CoV-2, the novel coronavirus that causes coronavirus disease 2019 (COVID-19), was first detected in the United States during January 2020 (1). Since then, >980,000 cases have been reported in the United States, including >55,000 associated deaths as of April 28, 2020 (2). Detailed data on demographic characteristics, underlying medical conditions, and clinical outcomes for persons hospitalized with COVID-19 are needed to inform prevention strategies and community-specific intervention messages. For this report, CDC, the Georgia Department of Public Health, and eight Georgia hospitals (seven in metropolitan Atlanta and one in southern Georgia) summarized medical record-abstracted data for hospitalized adult patients with laboratory-confirmed* COVID-19 who were admitted during March 2020. Among 305 hospitalized patients with COVID-19, 61.6% were aged <65 years, 50.5% were female, and 83.2% with known race/ethnicity were non-Hispanic black (black). Over a quarter of patients (26.2%) did not have conditions thought to put them at higher risk for severe disease, including being aged ≥65 years. The proportion of hospitalized patients who were black was higher than expected based on overall hospital admissions. In an adjusted time-to-event analysis, black patients were not more likely than were nonblack patients to receive invasive mechanical ventilation
† (IMV) or to die during hospitalization (hazard ratio [HR] = 0.63; 95% confidence interval [CI] = 0.35-1.13). Given the overrepresentation of black patients within this hospitalized cohort, it is important for public health officials to ensure that prevention activities prioritize communities and racial/ethnic groups most affected by COVID-19. Clinicians and public officials should be aware that all adults, regardless of underlying conditions or age, are at risk for serious illness from COVID-19., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. James M. Blum reports personal fees from Clew Medical, outside the submitted work. No other potential conflicts of interest were disclosed.- Published
- 2020
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