Epidemiology of CKD Regression in Patients under Nephrology Care

Abstract

Chronic Kidney Disease (CKD) regression is considered as an infrequent renal outcome, limited to early stages, and associated with higher mortality. However, prevalence, prognosis and the clinical correlates of CKD regression remain undefined in the setting of nephrology care. This is a multicenter prospective study in 1418 patients with established CKD (eGFR: 60-15 ml/min/1.73m²) under nephrology care in 47 outpatient clinics in Italy from a least one year. We defined CKD regressors as a ΔGFR ≥0 ml/min/1.73 m2/year. ΔGFR was estimated as the absolute difference between eGFR measured at baseline and at follow up visit after 18-24 months, respectively. Outcomes were End Stage Renal Disease (ESRD) and overall-causes Mortality.391 patients (27.6%) were identified as regressors as they showed an eGFR increase between the baseline visit in the renal clinic and the follow up visit. In multivariate regression analyses the regressor status was not associated with CKD stage. Low proteinuria was the main factor associated with CKD regression, accounting per se for 48% of the likelihood of this outcome. Lower systolic blood pressure, higher BMI and absence of autosomal polycystic disease (PKD) were additional predictors of CKD regression. In regressors, ESRD risk was 72% lower (HR: 0.28; 95% CI 0.14-0.57; p<0.0001) while mortality risk did not differ from that in non-regressors (HR: 1.16; 95% CI 0.73-1.83; p = 0.540). Spline models showed that the reduction of ESRD risk associated with positive ΔGFR was attenuated in advanced CKD stage. CKD regression occurs in about one-fourth patients receiving renal care in nephrology units and correlates with low proteinuria, BP and the absence of PKD. This condition portends better renal prognosis, mostly in earlier CKD stages, with no excess risk for mortality.

Fig 1. Selection algorithm of patients.

Fig 2. Plots of odds ratios and 95% confidence intervals (as indicated by the curvilinear dash lines) for likelihood of being regressor by level of proteinuria as continuous variable (reference level, 0.5g/24h).

The distribution of observations is shown as a rug plot on the x axis.

Fig 3. Restricted cubic splines to evaluate the non-linear relationship of eGFR change with ESRD at each GFR level: above 45 ml/min/1.73 m² (top), between 30 and 45 ml/min/1.73 m² (middle) and below 30 ml/min/1.73 m² (bottom).

The reference for the three GFR strata is 0 ml/min/1.73m² when ‎GFR level >45 ml/min/1.73 m² (top). Spline model is adjusted for age, gender, diabetes, BMI, previous CV disease, smoking, systolic BP, uric acid, hemoglobin, phosphate, cholesterol and 24h proteinuria measured at the follow up visit.