title: Visit-to-visit variability in systolic blood pressure is correlated with diabetic nephropathy and atherosclerosis in patients with type 2 diabetes.
abstract: OBJECTIVE
  Recent studies make remarks on the effect of variability in systolic blood pressure (SBP) on the development of cardiovascular disease. The aim of this study was to investigate the relationship between the variability in SBP and the degree of diabetic nephropathy and atherosclerosis in patients with type 2 diabetes.
  
  
  METHODS
  We measured SBP in 422 consecutive patients with type 2 diabetes at every visit during a year, and we calculated the coefficient of variation (CV) of SBP. Then, we evaluated relationships of variability of SBP to degree of urinary albumin excretion (UAE), which is a useful marker for cardiovascular disease as well as diabetic nephropathy, ankle-brachial index (ABI) and pulse wave velocity (PWV).
  
  
  RESULTS
  CV of SBP positively correlated with logUAE (r=0.210, P<0.0001) or PWV (r=0.409, P<0.0001), whereas CV of SBP inversely correlated with ABI (r=-0.098, P=0.0463). Multiple regression analysis demonstrated that CV of SBP independently correlated with logUAE (β=0.149, P=0.0072), PWV (β=0.337, P<0.0001) or ABI (β=-0.162, P=0.0101).
  
  
  CONCLUSIONS
  Not only average SBP but also variability in SBP is correlated with diabetic nephropathy and atherosclerosis in patients with type 2 diabetes.
authors.affiliation: Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto 602-8566, Japan.
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Okada
authors.forename: Michiaki
authors.initials: M
authors.lastname: Fukui
authors.forename: Muhei
authors.initials: M
authors.lastname: Tanaka
authors.forename: Shinobu
authors.initials: S
authors.lastname: Inada
authors.forename: Yusuke
authors.initials: Y
authors.lastname: Mineoka
authors.forename: Naoko
authors.initials: N
authors.lastname: Nakanishi
authors.forename: Takafumi
authors.initials: T
authors.lastname: Senmaru
authors.forename: Kazumi
authors.initials: K
authors.lastname: Sakabe
authors.forename: Emi
authors.initials: E
authors.lastname: Ushigome
authors.forename: Mai
authors.initials: M
authors.lastname: Asano
authors.forename: Masahiro
authors.initials: M
authors.lastname: Yamazaki
authors.forename: Goji
authors.initials: G
authors.lastname: Hasegawa
authors.forename: Naoto
authors.initials: N
authors.lastname: Nakamura
mesh_terms: D000368:Aged; D000419:Albuminuria / Q000209:etiology / Q000503:physiopathology; D055109:Ankle Brachial Index; D050197:Atherosclerosis / Q000175:diagnosis / Q000209:etiology / Q000503:physiopathology*; D001794:Blood Pressure; D003430:Cross-Sectional Studies; D003924:Diabetes Mellitus, Type 2 / Q000150:complications / Q000175:diagnosis / Q000503:physiopathology*; D003925:Diabetic Angiopathies / Q000175:diagnosis / Q000209:etiology / Q000503:physiopathology*; D003928:Diabetic Nephropathies / Q000175:diagnosis / Q000209:etiology / Q000503:physiopathology*; D005260:Female; D006801:Humans; D007564:Japan; D008297:Male; D008875:Middle Aged; D009819:Office Visits; D011237:Predictive Value of Tests; D011673:Pulsatile Flow; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D013997:Time Factors