Identificazione dei fenotipi clinici dell’insufficienza renale cronica che predicono la progressione della malattia. Un’applicazione della tecnica degli alberi decisionali

The primary aim of this dissertation to identify subgroups of patients with chronic kidney disease (CKD) who have a differential risk of progression of illness and the secondary aim is compare 2 equations to estimate the glomerular filtration rate (GFR). To this purpose, the PIRP (Prevention of Progressive Kidney Disease) registry was linked with the dialysis and mortality registries. The outcome of interest is the mean annual variation of GFR, estimated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. A decision tree model was used to subtype CKD patients, based on the non-parametric procedure CHAID (Chi-squared Automatic Interaction Detector). The independent variables of the model include gender, age, diabetes, hypertension, cardiac diseases, body mass index, baseline serum creatinine, haemoglobin, proteinuria, LDL cholesterol, tryglycerides, serum phoshates, glycemia, parathyroid hormone and uricemia. The decision tree model classified patients into 10 terminal nodes using 6 variables (gender, age, proteinuria, diabetes, serum phosphates and ischemic cardiac disease) that predict a differential progression of kidney disease. Specifically, age <=53 year, male gender, proteinuria, diabetes and serum phosphates >3.70 mg/dl predict a faster decrease of GFR, while ischemic cardiac disease predicts a slower decrease. The comparison between GFR estimates obtained using MDRD4 and CKD-EPI equations shows a high percentage agreement (>90%), with modest discrepancies for high and low age and serum creatinine levels. The study results underscore the need for a tight follow-up schedule in patients with age <53, and of patients aged 54 to 67 with diabetes, to try to slow down the progression of the disease. The result also emphasize the effective management of patients aged>67, in whom the estimated decrease in glomerular filtration rate corresponds with the physiological decrease observed in the absence of kidney disease, except for the subgroup of patients with proteinuria, in whom the GFR decline is more pronounced.