Ben Caplin1,2, Damien Ashby3, Kieran McCafferty4, Richard Hull5, Elham Asgari6, Martin L Ford7,8, Nicholas Cole9, Marilina Antonelou10,2, Sarah A Blakey3, Vinay Srinivasa4, Dandisonba C B Braide-Azikwe7, Tayeba Roper6, Grace Clark2, Helen Cronin7, Nathan J Hayes11, Bethia Manson2, Alexander Sarnowski5, Richard Corbett3, Kate Bramham7,8, Eirini Lioudaki7,8, Nicola Kumar6, Andrew Frankel3, David Makanjuola9, Claire C Sharpe7,8, Debasish Banerjee5, Alan D Salama10,2. 1. Department of Renal Medicine, University College London, London, United Kingdom b.caplin@ucl.ac.uk. 2. Renal Services, Royal Free London NHS Foundation Trust, London, United Kingdom. 3. Kidney and Transplant Services, Imperial College Healthcare NHS Trust, London, United Kingdom. 4. Renal Service, Barts Health NHS Trust, London, United Kingdom. 5. Renal Department, St. George's University Hospitals NHS Foundation Trust, London, United Kingdom. 6. Kidney Services, Guy's and St. Thomas' NHS Foundation Trust, London, United Kingdom. 7. Department of Renal Medicine, King's College Hospital NHS Foundation Trust, London, United Kingdom. 8. Faculty of Life Sciences & Medicine, Kings College London, London, United Kingdom. 9. South West Thames Renal and Transplantation Unit, Epsom and St. Helier University Hospitals NHS Trust, London, United Kingdom. 10. Department of Renal Medicine, University College London, London, United Kingdom. 11. Renal Services, North Middlesex University Hospital NHS Trust, London, United Kingdom.
Abstract
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.
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.
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