elevated nocturnal BP clinic BP monitoring alone is inadequate. ABPM should become golden standard to confirm adequate BP control in patients with kidney disease.

INTRODUCTION Peritoneal dialysis and hemodialysis are complementary ways of treating end-stage renal failure. Changing the dialysis modality from hemodialysis to peritoneal dialysis is a rare and poorly studied phenomenon. MATERIALS AND METHODS Retrospective cohort study conducted on the population of adult patients with end-stage chronic renal failure who were treated at the Nephrology Clinic of the Clinical Center of the University of Sarajevo in the period from 2006 to 2023. A total of 109 adult patients, whose medical documentation was complete and who were in the peritoneal dialysis program at the Nephrology Clinic of the Clinical Center of the University of Sarajevo during the observed period, were included in this study. One group started the treatment with peritoneal dialysis, and the other with hemodialysis. Demographic data were collected for each patient: age, gender, underlying kidney disease, comorbidities (heart disease and diabetes), duration of treatment modality, data on modality change, complications and treatment outcomes. Data from physical and electronic patient histories were used. RESULTS Total of 109 adult patients were included in this study. They are divided into two groups. Group 1 (n=99) in which peritoneal dialysis was the first treatment modality and Group 2 (n=10) in which haemodialysis was the first treatment modality, but in which patients, after a certain time, were transferred to peritoneal dialysis. The median age of patients in Group 1 was 60 (-/-14.07) years and 54 (-/+12.23) years for Group 2. Within Group 1 the most common cause of terminal renal failure was diabetic nephropathy (n=40, 40.4%) and nephroangiosclerosis (n=24, 24.24%). The mean age of onset of peritoneal dialysis was 60 (-/-14.07) years, while the mean age of cessation of peritoneal dialysis was 63 (±13.69) years. The average duration of peritoneal dialysis treatment was 38.36(±34.14) months. During the stay at peritoneal dialysis, death was recorded in 63 patients (62.38%). The number of patients who replaced peritoneal dialysis treatment with hemodialysis was 26. The most common reason for switching to haemodialysis was insufficiency of peritoneal dialysis (n=13, 14%). After switching to haemodialysis, the average length of staying on it was 10.22 months. The reason for discontinuation of haemodialysis was death (n=17, ) or transplantation (n=1, 3.7%). Kaplan-Meier test shown worse outcome in patients with haemodialyis first than peritoneal dialysis first. CONCLUSION Changing the dialysis modality carries with it a high risk of mortality, especially in the first month. Changing the way of active treatment with dialysis speaks in favor of severe comorbidities.

Introduction: Heart failure (HF) still remains as one of the most common causes of hospital admission with a high mortality rate. Aim: To investigate the possible prognostic role of brain natriuretic peptide (BNP), high-sensitivity (hs) cardiac troponin (cTn) I, cystatin C, and cancer antigen 125 (CA125) in the prediction of decompensation after an index hospitalization and to investigate their possible additive prognostic value. Patients and Methods: Two hundred twenty-two patients hospitalized with acute HF were monitored and followed for 18 months. Results: BNP at discharge has the highest sensitivity and specificity in the prediction of decompensation. For a cutoff value of 423.3 pg/ml, sensitivity was 64.3% and specificity was 64.5%, with a positive predictive value of 71.6% and an area under the curve (AUC) of 0.69 (P < 0.001). The hazard risk (HR) for decompensation when the discharge BNP was above the cutoff value was 2.18. Cystatin C, at a cutoff value of 1.46 mg/L, had a sensitivity of 57% and specificity of 57.8%, with a positive predictive value of 65.8% and an AUC of 0.59 (P = 0.028). CA125, in the prediction of decompensation in patients with acute heart failure (AHF) and at a cutoff value of 80.5 IU/L, had a sensitivity of 60.5% and specificity of 53.3%, with a positive predictive value of 64.5% and an AUC of 0.59 (P = 0.022). The time till onset of decompensation was significantly shorter in patients with four versus three elevated biomarkers (P = 0.047), with five versus three elevated biomarkers (P = 0.026), and in patients with four versus two elevated biomarkers (P = 0.026). The HR for decompensation in patients with five positive biomarkers was 3.7 (P = 0.001) and in patients with four positive biomarkers was 2.5 (P = 0.014), compared to patients who had fewer positive biomarkers. Conclusion: BNP, cystatin C, and CA125 are predictors of decompensation, and their combined usage leads to better prediction of new decompensation.

Background: To evaluate atherosclerotic changes in carotid arteries (CCA) in uremic patients before and after 18 months of continuous ambulatory peritoneal dialysis (CAPD) treatment, and to evaluate the impact of dyslipidemia and CAPD treatment on vascular remodeling. Materials and Methods: We conducted a longitudinal, prospective study during 2020 and 2021 at the Clinic for Nephrology, Clinical Center University of Sarajevo. Patients with end-stage renal disease were included and were followed during 18 months of CAPD treatment. All patients were treated using commercially prepared biocompatible balanced dialysis solutions. Carotid intima-media thickness (IMT) and atherosclerotic plaques on the common carotid artery (CCA) were measured by echotomography. Results: A total of 50 patients were included and were followed during 18 months of CAPD treatment. Lipid values in the serum of patients with CAPD were significantly lower after 18 months of CAPD treatment compared to the values before treatment, while the value of high-density lipoprotein (HDL) was significantly increased after 18 months of CAPD treatment. The values of IMT and the diameter of the CCA compared to the basal values were significantly lower (P < 0.001). Conclusion: We demonstrated significantly lower lipid values and higher HDL levels following CAPD treatment. Correct selection of the targeted pharmacological intervention can substantially impact the regression of vascular changes in patients on peritoneal dialysis.

BACKGROUND Atherosclerotic cardiovascular diseases (ASCVD) are still the leading cause of morbidity and mortality in Bosnia and Herzegovina. Elevated LDL-cholesterol is established as a strong marker of cardiovascular risk. Some researchers believe that measuring triglyceride levels gives a good assessment of the residual risk for ASCVD besides the measurement of LDL-cholesterol. OBJECTIVE The aim of this study was to evaluate the overall prevalence of major risk factors for ASCVD, lipid profile and 10-year fatal cardiovascular risk using the HeartSCORE scoring system. Further we want to evaluate the prevalence and relationship between elevated triglyceride levels and high 10-year fatal cardiovascular risk calculated as a HeartSCORE. METHODS This is a cross-sectional study conducted on 832 volunteers aged between 40 and 65 years without a diagnosis of diabetes and without known preexisting cardiovascular disease, as a part of the preventive program conducted at the Familly Medicine office. Data were collected for ASCVD risk factors and lipid panel (total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides). 10-year fatal cardiovascular risk was calculated using the HeartSCORE scoring system for countries with high CV risk. RESULTS Among 832 participants included, 565 (67.9%) were female, and 267 (32.1%) were male. We found high prevalence of hypertension (27.7%), obesity (32.2%), and smoking (36.2%). All lipid parameters, except HDL-C, were not optimal. Only 17.4% of participants had normal estimated HeartSCORE risk, while more than one-third (33.9%) had high or very high estimated HeartSCORE risk. Although we found a higher percentage of participants with elevated triglycerides in groups with higher HeartScore, there was a very weak positive correlation between values of triglycerides and the 10-year risk of a fatal cardiovascular event (r= 0.249, p= 0.000). CONCLUSION High prevalence of major known risk factors and high estimated HeartSCORE risk indicate a high overall risk for ASCVD in the sample. The proportion of participants with elevated triglycerides was increased in patients with high HeartSCORE risk what implicates importance of trygliceride measurement.

Background: In the last two decades diagnostic criteria for acute kidney injury (AKI) were developed: Risk, Injury, Failure, Loss of Kidney Function, End-Stage Kidney Disease (RIFLE), Acute Kidney Injury Network (AKIN), and Kidney Disease: Improving Global Outcomes (KDIGO) classifications. Objective: The study aimed to determine the incidence of AKI based on the RIFLE, AKIN, and KDIGO criteria, as well as analyze their predictive value for mortality and renal function outcome. Methods: This was a single-center prospective study of patients diagnosed with AKI. Acute kidney injury was defined and classified according to the RIFLE, AKIN, and KDIGO criteria. The outcomes were renal function outcome and in-hospital mortality. Results: The incidence rates of AKI based on the RIFLE, AKIN, and KDIGO criteria were 13.4%, 14-36%, and 14.64%, respectively. Multiple regression analysis showed that higher stages of AKI according to the KDIGO criteria were independently associated with non-recovery of renal function (p=0.011). However, the predictive ability of RIFLE, AKIN and KDIGO classifications for renal function recovery was poor (Area Under the Receiver Operating Characteristics-AUROC=0.599, AUROC=0.637, AUROC=0.659, respectively). According to the RIFLE and AKIN criteria, in-hospital mortality was statistically significantly higher in stage Failure/3 (p=0.0403 and p=0.0329, respectively) compared to stages Risk/1 and Injury/2. Receiver Operating Characteristics (ROC) analysis showed that all three classifications had poor predictive ability for in-hospital mortality (AUROC=0.675, AUROC=0.66, AUROC=0.681). Conclusions: KDIGO classification is an independent predictor of renal function non-recovery. However, by ROC analysis, all three classifications have poor predictive ability for renal function outcome and mortality.