title: The influence of metabolic syndrome and diabetes mellitus on the N-terminal pro-B-type natriuretic peptide level and its prognostic performance in patients with coronary artery disease.
abstract: OBJECTIVE
  Our aim was to investigate whether the presence of metabolic syndrome (MetS) and diabetes mellitus (DM) influenced the N-terminal pro-B-type natriuretic peptide (NT-proBNP) level and its prognostic performance in coronary artery disease (CAD).
  
  
  METHODS
  The present study enrolled a total of 1638 CAD patients. Multivariate regression analyses were carried out to relate NT-proBNP to metabolic components, nondiabetic MetS, DM, and MetS score. Furthermore, we examined the prognostic performance of NT-proBNP in patients with non-MetS, nondiabetic MetS, and DM.
  
  
  RESULTS
  NT-proBNP levels correlated inversely with BMI (β=-0.11, P=0.003) and correlated positively with fasting glucose (β=0.12, P=0.001). There were no significant relationships of NT-proBNP with other metabolic parameters. Compared with non-MetS, the presence of DM significantly increased NT-proBNP levels (P=0.004), whereas nondiabetic MetS did not influence NT-proBNP levels (P=0.954). During the median follow-up of 21 months, 109 all-cause deaths occurred. NT-proBNP levels independently predicted all-cause deaths irrespective of the presence of nondiabetic MetS and DM (Pinteraction=0.43).
  
  
  CONCLUSIONS
  DM, but not nondiabetic MetS, is associated with higher NT-proBNP levels. NT-proBNP can still predict death in patients with CAD, even with the confounding effect of MetS and diabetes.
authors.affiliation: Departments of aCardiology bGeneral Practice Medicine, West China Hospital, Sichuan University, Chengdu, China.
authors.forename: Fang-Yang
authors.initials: FY
authors.lastname: Huang
authors.forename: Yong
authors.initials: Y
authors.lastname: Peng
authors.forename: Xue-Xue
authors.initials: XX
authors.lastname: Deng
authors.forename: Bao-Tao
authors.initials: BT
authors.lastname: Huang
authors.forename: Tian-Li
authors.initials: TL
authors.lastname: Xia
authors.forename: Yi-Yue
authors.initials: YY
authors.lastname: Gui
authors.forename: Rui-Shuang
authors.initials: RS
authors.lastname: Liu
authors.forename: Yong
authors.initials: Y
authors.lastname: Yang
authors.forename: Xiao-Bo
authors.initials: XB
authors.lastname: Pu
authors.forename: Shi-Jian
authors.initials: SJ
authors.lastname: Chen
authors.forename: Fei
authors.initials: F
authors.lastname: Chen
authors.forename: Ye
authors.initials: Y
authors.lastname: Zhu
authors.forename: Mao
authors.initials: M
authors.lastname: Chen
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D016009:Chi-Square Distribution; D002681:China; D017023:Coronary Angiography; D003324:Coronary Artery Disease / Q000097:blood* / Q000175:diagnosis / Q000401:mortality; D016208:Databases, Factual; D003920:Diabetes Mellitus / Q000097:blood* / Q000175:diagnosis / Q000401:mortality; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D016014:Linear Models; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood* / Q000175:diagnosis / Q000401:mortality; D008875:Middle Aged; D015999:Multivariate Analysis; D020097:Natriuretic Peptide, Brain / Q000097:blood*; D010446:Peptide Fragments / Q000097:blood*; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D012307:Risk Factors; D015854:Up-Regulation
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D010446:Peptide Fragments; C109794:pro-brain natriuretic peptide (1-76); D020097:Natriuretic Peptide, Brain