Introduction: Up to 50% of patients with acute heart failure (AHF) have preserved left ventricular ejection fraction (HFPEF group)1. Due to diverse activated pathophysiological pathways, there should be a difference in biomarkers release in heart failure with preserved ejection fraction (HFPEF) and reduced ejection fraction (HFREF). BNP is the best studied biomarker in AHF, but we want to investigate difference in release of troponin (marker of myocytes stress and injury), tumor marker CA125 (marker of congestion and volume overload om HF) and cystatin C (marker of interstitial fibrosis).

Introduction: Data regarding prognostic factors of post-discharge mortality and adverse renal function outcome in acute kidney injury (AKI) hospital survivors are scarce and controversial. Objectives: We aimed to identify predictors of post-discharge mortality and adverse renal function outcome in AKI hospital survivors. Patients and Methods: The study group consisted of 84 AKI hospital survivors admitted to the tertiary medical center during 2-year period. Baseline clinical parameters, with renal outcome 3 months after discharge and 6-month mortality were evaluated. According survival and renal function outcome, patients were divided into two groups. Results: Patients who did not recover renal function were statistically significantly older (P < 0.007) with higher Charlson comorbidity index (CCI) score (P < 0.000) and more likely to have anuria and oliguria (P = 0.008) compared to those with recovery. Deceased AKI patients were statistically significantly older (P < 0.000), with higher CCI score (P < 0.000), greater prevalence of sepsis (P =0.004), higher levels of C-reactive protein (CRP) (P < 0.017) and ferritin (P < 0.051) and lower concentrations of albumin (P<0.01) compared to survivors. By multivariate analysis, independent predictors of adverse renal outcome were female gender (P =0.033), increasing CCI (P =0.000), presence of pre-existing chronic kidney disease (P =0.000) and diabetes mellitus (P =0.019) as well as acute decompensated heart failure (ADHF) (P =0.032), while protective factor for renal function outcome was higher urine output (P =0.009). Independent predictors of post-discharge mortality were female gender (P =0.04), higher CCI score (P =0.001) and sepsis (P =0.034). Conclusion: Female AKI hospital survivors with increasing burden of comorbidities, diagnosis of sepsis and ADHF seem to be at high-risk for poor post-discharge outcome.

Aim: The objective of this study was to evaluate prognostic impact of clinical factors on outcome of renal function in septic and non-septic acute kidney injury (AKI) patients. Methods: The prospective, observational, clinical study was performed at Nephrology Clinic and Clinic for Infectious Diseases, University Clinical Centre Sarajevo. One hundred patients with diagnosis of AKI were enrolled in the study, and divided into two groups: septic and non-septic AKI patients. Clinical parameters included causes and type of AKI, pre-existing comorbidities and different treatment modalities. Patients were followed up until discharge or death. Renal function outcome was defined by creatinine clearance values at discharge. Results: Septic AKI patients had significantly longer hospital stay (p=0.03), significantly worse renal function outcome (p<0.001), and higher burden of comorbidities (70.6% vs. 60.6%), compared to non-septic patients. Septic AKI patients were almost three times less likely to receive renal replacement therapy (8.8% vs. 24.4%) and they had significant delay in initiation of dialysis (p=0.03). By multivariate analysis, sepsis (95% CI 0.128-0.967, p=0.043) and hypertension (95% CI 0.114-0.788, p=0.015) were independent predictors of adverse renal function outcome in AKI patients. Postrenal type of AKI was independent predictor of renal function recovery in non-septic AKI patients (95% CI 1.174-92.264, p=0.035), while Failure, as third class of AKI, was independent predictor of non-recovered renal function only in septic AKI patients (95% CI 0.026 to 0.868, p=0.034). Conclusion: Septic AKI patients are clinically distinct compared to non-septic AKI patients with different prognostic factors and poorer renal function outcome.

Introduction: The diagnostic utility of B-type natriuretic peptide (BNP) has prompted interest in its use as an aid in the detection of early heart failure and assessment of diseases. The first objective of this study was measurement of BNP and troponin I (TnI) blood levels in patients with acute myocardial infarction (AMI) and unstable angina. The second objective of this study was to find a correlation between TnI and BNP in blood.Methods: The concentrations of BNP and TnI in 150 blood levels were determined using CMIA (chemiluminescent microparticle immunoassay) Architect and 2000 (Abbott diagnostics). The retrospective study included 100 patients who were hospitalized at the Department of Internal Medicine of the University Clinical Center Sarajevo and 50 healthy control. The reference blood range of BNP is 0-100 pg/mL and TnI is 0.00-0.4 ng/mL.Results: In the patients with AMI the mean value of BNP is 764.48 ± 639.52 pg/mL and TnI is 2.50 ± 2.28ng/mL. The patients with unstable angina have BNP 287.18 ± 593.20 pg/mL and TnI 0.10 ± 0.23 ng/mL. Our studies have shown that the correlation between BNP and TnI was statistically significant for p< 0.05 using Student t test with correlation coefficient r = 0.36. Conclusions: BNP and TnI levels can help to identify the patients with a high risk for cardiovascular diseases.

Background: For the assessment of the left ventricular function and infarct size in acute myocardial infarction, brain natriuretic peptide (BNP) and cardiac troponin I (cTnI) are useful for the prediction of a prognosis. The aim of the present study was to correlate left ventricular function and infarct size to the level of cTnI and BNP in acute myocardial infarction. Patients and Methods: We studied 40 patients (pts), with the first ST-segment elevation myocardial infarction (STEMI). We measured the level of BNP and cTnI on a single occasion at 96 hours after the onset of symptoms, and then compared it with echocardiography estimated systolic and diastolic ventricular function and infarct size — which was determined with numbers of ECG leads and classification into small and large infarct size (small infarct size 3-4 leads, large infarct size 6-9 leads). Results: Distribution of data was estimated by using the Shapiro-Wilk test. The data do not have normal distribution, so they are representative as a median and range. We used non-parametric statistic tests (Mann-Whitney tests) to compare and improve differences among the groups. For statistical correlation, we used the Sperman rank correlation. Data were analyzed using statistical program Arcus Quick Stat. There was significant inverse correlation between the level of BNP and EF (r = -0.504, P = 0.0016) and between BNP i E/A (r = -0.290, P = 0.00705). There was a strong inverse correlation between BNP and LV-EF in STEMI, such as between BNP and E/A, against cTnI no significant correlation with LV-EF and E/A in STEMI was found. There is no significant statistical difference between BNP and cTnI in small and large infarct size. Conclusion: A single BNP value at 96 hours after the onset symptoms of myocardial infarction proved useful for the estimation of LV systolic and diastolic function. In a direct comparison BNP disclosed a better performance for the estimation of LV-EF and E/A against cTnI. cTnI is useful for diagnosing early myocardial damage in acute myocardial infarction, suggesting an implementation of dual marker strategy in acute myocardial infarction for diagnostic and prognostic work-up.