UCL  IRIS
Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at https://www.ucl.ac.uk/finance/research/rs-contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
Risk of COVID-19 Disease, Dialysis Unit Attributes, and Infection Control Strategy among London In-Center Hemodialysis Patients
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Article
  • Authors:
    Caplin B, Ashby D, McCafferty K, Hull R, Asgari E, Ford M, Cole N, Antonelou M, Blakey S, Srinivasa V, Braide-Azikiwe D, Roper T, Clark G, Cronin H, Hayes N, Manson B, Sarnowski A, Corbett R, Bramham K, Lioudaki E, Kumar N, Frankel A, Makanjuola D, Sharpe C, Banerjee D, Salama A
  • Publisher:
    American Society of Nephrology
  • Publication date:
    01/06/2021
  • Journal:
    Clinical Journal of the American Society of Nephrology
  • Status:
    Published
  • Country:
    United States
  • Print ISSN:
    1555-9041
  • PII:
    CJN.03180321
  • Language:
    eng
Abstract
Background Patients receiving in-center hemodialysis treatment face unique challenges during the 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. Methods We explored the role of variables including community disease burden, dialysis unit attributes (size, layout) and infection control strategies, on rates of COVID-19 among patients receiving in center hemodialysis in London, UK, between March 2nd 2020 and May 31st 2020. The two outcomes were defined as (i) a positive test for infection or admission with suspected COVID19 and (ii) admission to the hospital with suspected infection. Associations were examined using a discrete-time multi-level time-to-event analysis. Results Data on 5,755 patients, dialysing in 51 units were analysed. 990 (17%) tested positive and 465 (8%) were admitted with suspected COVID-19 between 2nd March and 31st May 2020. Outcomes were associated with age, diabetes, local community COVID-19 rates and dialysis unit size. Greater number of available side rooms and 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.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Author
Renal Medicine
Author
Renal Medicine
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by