The speed of chronic kidney disease progression and it‘s influencing factors

The speed of chronic kidney disease progression and it‘s influencing factors The main aim of this study is to determine the speed of chronic kidney disease (CKD) progression and it‘s influencing factors. The tasks of the research: 1. To calculate the speed of CKD progression in the group of subjects; 2. To determine which factors have an influence on CKD progression; 3. To create a mathematic model of the CKD progression. The methodology of the research – a retrospective cohort study. The study involved 32 patients in LUHS KK Nephrology department, that have been prepared for haemodialysis by forming an arteriovenous fistula. The data has been collected considering patients’ age, gender, main diagnose, time of observation and the outcome of CKD. In a purpose to determine the factors that influence the speed of CKD, the data of laboratory measures was also collected. It includes uric acid, calcium, phosphorus, parathyroid hormone, C reactive protein (CRP), haemoglobin, ferritin, the count of leukocytes, neutrophils, lymphocytes, eosinophils, monocytes, 24 hours proteinuria, creatinine, albumin/ creatinine ratio, common protein/creatinine ratio and eGFR. The speed of CKD progression has been calculated based on eGFR decline, using a linear regression model. The factors influencing CKD progression have been identified based on mean laboratory data’s measures, using the Cox regression model. Results and conclusions: The speed of CKD progression before forming arteriovenous fistula was -6,14 ml/min/1,73m2 per year. The speed of CKD progression after forming arteriovenous fistula was -4,64 ml/min/1,73m2 per year. The overall speed of CKD progression was -4, 23 ml/min/1,73m2 per year. The univariate Cox regression model showed that the age, phosphorus, CRP, neutrophils‘ count, monocytes/ lymphocytes ratio and platelets/lymphocytes ratio had made the impact for the speed of CKD progression. Only CRP and phosphorus were independent factors influencing the speed CKD progression and stood statistically significant in multivariate Cox regression model. The mathemathical CKD progression model is: : h0 (t) ∙ exp {1.127 ∙ CRB + 7.798 ∙ P }