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Abstract: SA-OR06

Kidney Disease and COVID-19 Outcomes in the Temporal Analysis of Pandemic Waves

Session Information

Category: Coronavirus (COVID-19)

  • 000 Coronavirus (COVID-19)


  • Shang, Ning, Columbia University, New York, New York, United States
  • Kiryluk, Krzysztof, Columbia University, New York, New York, United States

COVID-19 continues to spread worldwide with considerable morbidity and mortality. CKD is among the most prevalent diseases related to COVID-19 mortality. AKI is a common COVID-19 complication. Distinct pandemic waves were observed as a function of specific COVID-19 variants, public health policies and vaccination status. Studies reported changing patient characteristics and outcomes by different waves. However, changes in the effect of clinical risk factors as a function of each wave have not been well studied. Here, we examine the temporal effects of pre-existing CKD (also KDIGO A and G stages) on COVID-19 outcomes by waves.


We used estimated effective reproduction numbers with US data to define distinct waves. We designed a COVID-19 algorithm based on WHO guidelines, N3C COVID-19 V2.2 and local data characteristics as having >=1 positive SARS-Cov-2 RT-PCR or antibody test, or >=3 diagnosis or problem codes if no relevant tests. Comorbidities and outcomes were captured electronically using published algorithms. We used logistic regression and survival analysis to identify predictors of COVID-19 outcomes for each wave.


Five national waves were identified and mapped to 4 distinct NYC waves observed at Columbia University Medical Center (CUMC). We identified 64246 COVID-19 cases at CUMC, 8% were severe, 18% were hospitalized. The risk of severe COVID-19 was associated with pre-existing CKD, heart disease, diabetes and hypertension in most waves; and lung disease, obesity and cancer in at least one wave. AKI occurred in 49% of severe cases and 35% of hospitalized ones. The risk of AKI was associated with heart failure, obesity, diabetes and cancer in most waves; and CKD, CAD, hypertension and stroke in one or two waves. The risk of AKI was not associated with pre-existing lung disease. A and G stages independently predicted severe COVID-19 and COVID-19 related AKI across all waves. Pre-existing albuminuria significantly predicted COVID-19 mortality independent of G-stage, diabetes, obesity, hypertension, cancer or cardiovascular disease throughout the entire pandemic.


Pre-existing kidney disease was among the strongest and most consistent clinical predictors of poor COVID-19 outcomes regardless of the pandemic wave. Even in the pandemic late phase, patients with decreased kidney function or albuminuria were at a higher risk of severe COVID-19, AKI and death.


  • NIDDK Support