ASN's Mission

To create a world without kidney diseases, the ASN Alliance for Kidney Health elevates care by educating and informing, driving breakthroughs and innovation, and advocating for policies that create transformative changes in kidney medicine throughout the world.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005

email@asn-online.org

202-640-4660

The Latest on Twitter

Kidney Week

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)

Authors

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

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.

Methods

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.

Results

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.

Conclusion

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.

Funding

  • NIDDK Support