title: The combination of chronic kidney disease and increased arterial stiffness is a predictor for stroke and cardiovascular disease in hypertensive patients.
abstract: To clarify the clinical utility of pulse wave velocity (PWV) and chronic kidney disease (CKD) in hypertension, we analyzed the prognostic impact of PWV and CKD on cerebrocardiovascular disease in hypertensive patients. This study consisted of 531 patients with essential hypertension (male/female=292/239, mean age=61.7±12.3, mean follow-up=7.0±3.0 years) and was performed between January 1998 and June 2004. We used questionnaires to assess stroke (n=57), cardiovascular diseases (CVDs; myocardial infarction, angina and congestive heart failure; n=44) and death (n=53) as primary end points. At baseline, we evaluated the carotid-femoral PWV (9.1±1.8 m s(-1)), the glomerular filtration rate and urinary protein excretions. We divided these subjects into those in the highest quartile of PWV and other subjects and into CKD (n=149) and non-CKD (n=458). We evaluated the prognostic influences of PWV and CKD with Kaplan-Meier analysis and Cox's proportional hazard model. PWV in CKD (9.6±1.9 m s(-1)) was higher than in non-CKD (8.8±1.6 m s(-1); P<0.0001), and creatinine was slightly decreased in the highest PWV group (1.09±0.35 mg dl(-1), P<0.0001). On the basis of Kaplan-Meier analysis, the highest PWV group (PWV>10.1 m s(-1); P=0.0003) and the CKD group (P=0.0005) showed significantly higher proportions of stroke and CVD events. In addition, the highest PWV group showed the highest percentage of stroke (P=0.0007), and the CKD group showed the highest proportion of CVD (P<00001). High PWV and CKD were independent predictors for stroke and CVD (P=0.0332) by Cox's proportional hazard model. These data suggest that increased aortic stiffness and CKD may be predictors for stroke and cardiovascular events in hypertensive patients.
authors.affiliation: Department of Geriatric Medicine, Osaka University Graduate School of Medicine, Suita City, Osaka, Japan. ohishi@geriat.med.osaka-u.ac.jp
authors.forename: Mitsuru
authors.initials: M
authors.lastname: Ohishi
authors.forename: Yuji
authors.initials: Y
authors.lastname: Tatara
authors.forename: Norihisa
authors.initials: N
authors.lastname: Ito
authors.forename: Yasushi
authors.initials: Y
authors.lastname: Takeya
authors.forename: Miyuki
authors.initials: M
authors.lastname: Onishi
authors.forename: Yoshihiro
authors.initials: Y
authors.lastname: Maekawa
authors.forename: Nozomi
authors.initials: N
authors.lastname: Kato
authors.forename: Kei
authors.initials: K
authors.lastname: Kamide
authors.forename: Hiromi
authors.initials: H
authors.lastname: Rakugi
mesh_terms: D000368:Aged; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D002339:Carotid Arteries / Q000503:physiopathology; D002908:Chronic Disease; D015331:Cohort Studies; D015897:Comorbidity; D023381:Endpoint Determination; D005260:Female; D005263:Femoral Artery / Q000503:physiopathology; D005500:Follow-Up Studies; D005919:Glomerular Filtration Rate / Q000502:physiology; D006801:Humans; D006973:Hypertension / Q000453:epidemiology* / Q000503:physiopathology*; D053208:Kaplan-Meier Estimate; D007674:Kidney Diseases / Q000453:epidemiology* / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D012307:Risk Factors; D020521:Stroke / Q000453:epidemiology*; D059289:Vascular Stiffness / Q000502:physiology*