title: [Determining factors of cardiac biomarkers in hemodialysed diabetic and non-diabetic patients].
abstract: BACKGROUND
  Cardiovascular diseases are highly prevalent in chronic renal failure patients, especially in diabetic population. Cardiac biomarkers such as pro-brain natriuretic peptide N-terminal piece (NT-proBNP), cardiac troponin T (cTnT) and high sensitive CRP (hs-CRP) are increasingly used for early detection.
  
  
  OBJECTIVE
  The authors analysed, which factors influence cardiac biomarker levels in hemodialysed patients and whether these factors depend on the presence of diabetes.
  
  
  METHODS
  In 28 diabetic and 40 non-diabetic patients on chronic hemodialysis was analysed the association between routine laboratory data, bioimpedance parameters, results of echocardiography and ambulatory blood pressure monitoring on cardiac biomarkers. Multivariate linear regression analysis (ANOVA) was applied for statistical evaluation.
  
  
  RESULTS
  The authors found stronger correlation (p = 0.034 vs. p = 0.001) between NT-proBNP and extracellular volume/total water volume hyperhydration ratio (ecv/twv) evaluated in diabetics than in non-diabetics. In case of cTnT, no relation was found with CaxP, iPTH, Kt/V, beta2-microglobulin, and serum uric acid levels. The hs-CRP was correlated with total cholesterol (p = 0.039) and EPO-dose (p = 0.03) in diabetics, while with serum fibrinogen (p = 0.025) in non-diabetics. The HbA1c didn't influence biomarkers in the diabetic group.
  
  
  CONCLUSIONS
  The factors having an impact on cardiac biomarker levels are similar in diabetic and non-diabetic hemodialysed patients. According to results the presence of end-stage renal disease in a cross-sectional survey probably overcomes the impact of diabetes and quality of glycaemic control on cardiac biomarker levels.
authors.affiliation: Diósgyori Kórház Belgyógyászat Miskolc. macsaim1@t-online.hu
authors.forename: Emília
authors.initials: E
authors.lastname: Mácsai
authors.forename: Júlia
authors.initials: J
authors.lastname: Széll
authors.forename: Erzsébet
authors.initials: E
authors.lastname: Ladányi
authors.forename: András
authors.initials: A
authors.lastname: Treszl
authors.forename: Barna
authors.initials: B
authors.lastname: Vásárhelyi
authors.forename: László
authors.initials: L
authors.lastname: Madácsy
mesh_terms: D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood*; D001834:Body Water; D002097:C-Reactive Protein / Q000378:metabolism; D002318:Cardiovascular Diseases / Q000097:blood* / Q000150:complications*; D002784:Cholesterol / Q000097:blood; D003430:Cross-Sectional Studies; D048909:Diabetes Complications / Q000097:blood*; D005260:Female; D005340:Fibrinogen / Q000378:metabolism; D006801:Humans; D007676:Kidney Failure, Chronic / Q000097:blood* / Q000150:complications* / Q000628:therapy; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D020097:Natriuretic Peptide, Brain / Q000097:blood; D010446:Peptide Fragments / Q000097:blood; D006435:Renal Dialysis; D012189:Retrospective Studies; D020107:Troponin T / Q000097:blood
chemical_list: D015415:Biomarkers; D010446:Peptide Fragments; D020107:Troponin T; C109794:pro-brain natriuretic peptide (1-76); D020097:Natriuretic Peptide, Brain; D005340:Fibrinogen; D002097:C-Reactive Protein; D002784:Cholesterol