Models for screening and prediction of chronic kidney disease progression

Abstract

The course of chronic kidney disease (CKD) in its early stages is typically asymptomatic; therefore, in a significant proportion of patients, the disease is diagnosed incidentally or when clinical manifestations (hypertension, edema, etc.) appear. The current approach to risk stratification, diagnosis, and progression in CKD is based on analyzing the relationship between estimated glomerular filtration rate (eGFR) and albuminuria (primarily the albumin-to-creatinine ratio, ACR) using validated calculators. This study evaluated calculators for determining the probability of developing CKD (SCORED, QKidney, CKD-PC Incident CKD Risk) and its progression (Kidney Failure Risk Equation, KFRE). It was demonstrated that the most clinically useful sequence is as follows: risk-based selection of patients for testing, confirmation of CKD presence based on eGFR and ACR, and assessment of the rate of progression in patients with G3–G5 CKD using KFRE. A practical algorithm for the use of these tools by family physicians and nephrologists is proposed.