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Clinical Kidney Journal
Article . 2021
Data sources: PubMed Central
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Clinical Kidney Journal
Article
License: cc-by-nc
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Risk prediction of COVID-19 incidence and mortality in a large multi-national hemodialysis cohort: implications for management of the pandemic in outpatient hemodialysis settings

Authors: Mathias Haarhaus; Carla Santos; Michael Haase; Pedro Veiga; Carlos Lucas; Fernando Macário;

Risk prediction of COVID-19 incidence and mortality in a large multi-national hemodialysis cohort: implications for management of the pandemic in outpatient hemodialysis settings

Abstract

Abstract Background Experiences from the first wave of the 2019 coronavirus disease (COVID-19) pandemic can aide in the development of future preventive strategies. To date, risk prediction models for COVID-19-related incidence and outcomes in haemodialysis (HD) patients are missing. Methods We developed risk prediction models for COVID-19 incidence and mortality among HD patients. We studied 38 256 HD patients from a multi-national dialysis cohort between March 3rd and July 3rd 2020. Risk prediction models were developed and validated, based on predictors readily available in outpatient haemodialysis units. We compared mortality among patients with and without COVID-19, matched for age, sex, and diabetes. Results During the observational period, 1 259 patients (3.3%) acquired COVID-19. Of these, 62% were hospitalised or died. Mortality was 22% among COVID-19 patients with odds ratios 219.8 (95% CI 80.6-359) to 342.7 (95% CI 60.6-13595.1), compared to matched patients without COVID-19. Since the first wave of the pandemic affected mostly European countries during the study, the risk prediction model for incidence of COVID-19 was developed and validated in European patients only (N = 22 826, AUCDev 0.64, AUCVal 0.69). The model for prediction of mortality was developed in all COVID-19 patients (AUCDev 0.71, AUCVal 0.78). Angiotensin receptor blockers were independently associated with a lower incidence of COVID-19 in European patients. Conclusions We identified modifiable risk factors for COVID-19 incidence and outcome in HD patients. Our risk prediction tools can be readily applied in clinical practice. The current study can aid in the development of preventive strategies for future waves of COVID-19.

Graphical Abstract Graphical Abstract

Subjects by Vocabulary

Microsoft Academic Graph classification: medicine.medical_specialty medicine.medical_treatment Disease Diabetes mellitus Internal medicine medicine Dialysis business.industry Incidence (epidemiology) Odds ratio medicine.disease Confidence interval Cohort Hemodialysis business

Keywords

coronavirus, AcademicSubjects/MED00340, Transplantation, SARS-CoV-2, COVID-19, mortality, haemodialysis, Nephrology, Original Article

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    impulse
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    Top 10%
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    27
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
27
Top 10%
Top 10%
Top 10%
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