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Kidney Int ; 98(6): 1530-1539, 2020 12.
Artículo en Inglés | MEDLINE | ID: covidwho-713938

RESUMEN

Given the high risk of infection-related mortality, patients with end-stage kidney disease (ESKD) may be at increased risk with COVID-19. To assess this, we compared outcomes of patients with and without ESKD, hospitalized with COVID-19. This was a retrospective study of patients admitted with COVID-19 from 13 New York hospitals from March 1, 2020, to April 27, 2020, and followed through May 27, 2020. We measured primary outcome (in-hospital death), and secondary outcomes (mechanical ventilation and length of stay). Of 10,482 patients with COVID-19, 419 had ESKD. Patients with ESKD were older, had a greater percentage self-identified as Black, and more comorbid conditions. Patients with ESKD had a higher rate of in-hospital death than those without (31.7% vs 25.4%, odds ratio 1.38, 95% confidence interval 1.12 - 1.70). This increase rate remained after adjusting for demographic and comorbid conditions (adjusted odds ratio 1.37, 1.09 - 1.73). The odds of length of stay of seven or more days was higher in the group with compared to the group without ESKD in both the crude and adjusted analysis (1.62, 1.27 - 2.06; vs 1.57, 1.22 - 2.02, respectively). There was no difference in the odds of mechanical ventilation between the groups. Independent risk factors for in-hospital death for patients with ESKD were increased age, being on a ventilator, lymphopenia, blood urea nitrogen and serum ferritin. Black race was associated with a lower risk of death. Thus, among patients hospitalized with COVID-19, those with ESKD had a higher rate of in-hospital death compared to those without ESKD.


Asunto(s)
COVID-19/complicaciones , Fallo Renal Crónico/complicaciones , Adulto , Anciano , Anciano de 80 o más Años , COVID-19/mortalidad , Femenino , Humanos , Pacientes Internos , Fallo Renal Crónico/mortalidad , Tiempo de Internación/estadística & datos numéricos , Masculino , Persona de Mediana Edad , New York/epidemiología , Respiración Artificial/estadística & datos numéricos , Estudios Retrospectivos , Factores de Riesgo
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