Ключевые слова
COVID-19
monitoring algorithm
risk stratification
proteinuria
prognosis
Как цитировать
Аннотация
Introduction. Chronic kidney disease and coronavirus disease 2019 represent a high-risk intersection, yet renal follow-up after coronavirus disease 2019 remains insufficiently standardized. We developed and internally validated a risk-stratified clinical algorithm for monitoring and prognostic assessment of patients with chronic kidney disease after coronavirus disease 2019.
Materials and Methods. This was a prospective cohort study of 280 non-dialysis patients with chronic kidney disease stages G2-G5: 140 post-coronavirus disease 2019 and 140 controls. At 6 to 12 months, we assessed estimated glomerular filtration rate, proteinuria, and inflammatory, metabolic, and hematologic markers. Coronavirus disease 2019 severity and the occurrence of acute kidney injury during infection were recorded. Predictors of advanced chronic kidney disease stages G4-G5 were identified by multivariate logistic regression; algorithm performance was evaluated by calibration and receiver operating characteristic analysis.
Results. The decline in renal function was comparable between groups. In post-coronavirus disease 2019 patients, persistent proteinuria, elevated serum phosphate, and low hemoglobin independently predicted advanced chronic kidney disease (odds ratio 5.0, 1.8, 1.4, respectively (p<0.005). The model showed good internal performance (area under the curve approximately 0.88).
Conclusions. Coronavirus disease 2019 appears to amplify renal vulnerability. A structured, risk-based algorithm may improve early detection of renal deterioration and support personalized management.
Библиографические ссылки
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