Risk of COVID-19 Disease, Dialysis Unit Attributes, and Infection Control Strategy among London In-Center Hemodialysis Patients
| Autor: | Elham Asgari, Claire C. Sharpe, Nicholas Cole, Helen Cronin, Bethia Manson, Kate Bramham, Grace Clark, Tayeba Roper, Richard Hull, Martin. Ford, Eirini Lioudaki, Marilina Antonelou, Debasish Banerjee, Nicola Kumar, Sarah Blakey, Nathan Hayes, Vinay Srinivasa, Richard Corbett, Andrew H. Frankel, Damien Ashby, Kieran McCafferty, Alexander Sarnowski, Ben Caplin, Alan D. Salama, David Makanjuola, D. B. Braide-Azikiwe |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Isolation (health care) Epidemiology medicine.medical_treatment Population Disease Critical Care and Intensive Care Medicine Asymptomatic Renal Dialysis medicine Humans Infection control education Disease burden Dialysis Transplantation education.field_of_study SARS-CoV-2 business.industry COVID-19 Original Articles Nephrology Evidence-Based Practice Emergency medicine Kidney Failure Chronic Hemodialysis medicine.symptom business |
| Zdroj: | Clin J Am Soc Nephrol |
| ISSN: | 1555-905X |
| Popis: | BACKGROUND AND OBJECTIVES: Patients receiving in-center hemodialysis treatment face unique challenges during the coronavirus disease 2019 (COVID-19) pandemic, specifically the need to attend for treatment that prevents self-isolation. Dialysis unit attributes and isolation strategies that might reduce dialysis center COVID-19 infection rates have not been previously examined. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We explored the role of variables, including community disease burden, dialysis unit attributes (size and layout), and infection control strategies, on rates of COVID-19 among patients receiving in-center hemodialysis in London, United Kingdom, between March 2, 2020 and May 31, 2020. The two outcomes were defined as (1) a positive test for infection or admission with suspected COVID-19 and (2) admission to the hospital with suspected infection. Associations were examined using a discrete time multilevel time-to-event analysis. RESULTS: Data on 5755 patients dialyzing in 51 units were analyzed; 990 (17%) tested positive and 465 (8%) were admitted with suspected COVID-19 between March 2 and May 31, 2020. Outcomes were associated with age, diabetes, local community COVID-19 rates, and dialysis unit size. A greater number of available side rooms and the introduction of mask policies for asymptomatic patients were inversely associated with outcomes. No association was seen with sex, ethnicity, or deprivation indices, nor with any of the different isolation strategies. CONCLUSIONS: Rates of COVID-19 in the in-center hemodialysis population relate to individual factors, underlying community transmission, unit size, and layout. |
| Databáze: | OpenAIRE |
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