BackgroundChronic heart failure is a very common condition in the elderly, characterized not only by high mortality rates, but also by a strong impact on health-related quality of life (HRQOL). Previous studies of HRQOL in elderly heart failure subjects have included mostly outpatients, and little is known about determinants of HRQOL in hospitalized elderly population, especially in Serbia. In this study, we tried to identify factors that influence HRQOL in elderly patients hospitalized with chronic heart failure in Serbia.MethodsThe study population consisted of 136 patients aged 65 years or older hospitalized for chronic heart failure. HRQOL was assessed using the Minnesota Living with Heart Failure questionnaire. Predictors of HRQOL were identified by multiple linear regression analysis.ResultsUnivariate analysis showed that patients with lower income, a longer history of chronic heart failure, and longer length of hospital stay, as well as those receiving aldosterone antagonists and digoxin, taking multiple medications, in a higher NYHA class, and showing signs of depression and cognitive impairment had significantly worse HRQOL. Presence of depressive symptoms (P<0.001), higher NYHA class (P=0.021), lower income (P=0.029), and longer duration of heart failure (P=0.049) were independent predictors of poor HRQOL.ConclusionDepressive symptoms, higher NYHA class, lower income, and longer duration of chronic heart failure are independent predictors of poor HRQOL in elderly patients hospitalized with chronic heart failure in Serbia. Further, there is an association between multiple medication usage and poor HRQOL, as well as a negative impact of cognitive impairment on HRQOL. Hence, measures should be implemented to identify such patients, especially those with depressive symptoms, and appropriate interventions undertaken in order to improve their HRQOL.
Background/Aims: Early initiation of renal replacement therapy (RRT) is recommended in order to improve the clinical outcome of patients who develop an acute kidney injury (AKI). However, markers that guide an early RRT initiation do not really exist currently. Methods: Urine and serum samples were prospectively collected from 120 AKI patients. Depending on the necessity of initiating RRT, patients were divided into 2 different groups: dialysis (n = 52) and non-dialysis (n = 68). Results: Comparative urinary proteomic analyses identified 4 different proteins (fatty acid binding proteins 1 and 3 (FABP1 and FABP3), β-2-microglobulin (B2M), cystatin-M (CST6)) that discriminate AKI patients with high risk for RRT. Western blot analysis confirmed the proteomics data for FABP1 and FABP3 but not for B2M and CST6. Validation analysis confirmed that the FABP1 and FABP3 fulfilled the requirement of functioning as markers for AKI patients with risk to dialysis (p < 0.001). Conclusion: The release of high amounts of FABP1 and FABP3 in urine of AKI patients could serve as a diagnostic/prognosis marker for RRT initiation in these patients.
Diabetic nephropathy (DN) is the main reason for end-stage renal disease. Microalbuminuria as the non-invasive available diagnosis marker lacks specificity and gives high false positive rates. To identify and validate biomarkers for DN, we used in the present study urine samples from four patient groups: diabetes without nephropathy, diabetes with microalbuminuria, diabetes with macroalbuminuria and proteinuria without diabetes. For the longitudinal validation, we recruited 563 diabetic patients and collected 1363 urine samples with the clinical data during a follow-up of 6 years. Comparative urinary proteomics identified four proteins Apolipoprotein A-I (APOA1), Beta-2-microglobulin (B2M), E-cadherin (CDH1) and Lithostathine-1-alpha (REG1A), which differentiated with high statistical strength (p < 0.05) between DN patients and the other groups. Label-free mass spectrometric quantification of the candidates confirmed the discriminatory value of E-cadherin and Lithostathine-1-alpha (p < 0.05). Immunological validation highlighted E-cadherin as the only marker able to differentiate significantly between the different DN stages with an area under the curve (AUC) of 0.85 (95%-CI: [0.72, 0.97]). The analysis of the samples from the longitudinal study confirmed the prognostic value of E-cadherin, the critical increase in urinary E-cadherin level was measured 20 ± 12.5 months before the onset of microalbuminuria and correlated significantly (p < 0.05) with the glomerular filtration rate measured by estimated glomerular filtration rate (eGFR).
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