title: Pulse pressure amplification a mechanical biomarker of cardiovascular risk.
abstract: OBJECTIVE
  The aim of this study was to determine whether the carotid/brachial (C/B) ratio is an independent predictor of cardiovascular (CV) risk.
  
  
  BACKGROUND
  Brachial and carotid pulse pressure (PP) are independent predictors of CV risk, mainly in elderly patients. Because PP is physiologically lower at the brachial than at the carotid arterial site, PP amplification is represented by the C/B ratio and could independently predict CV risk.
  
  
  METHODS
  In a Paris population (n = 834), brachial and carotid PP were measured from sphygmomanometry and pulse wave analysis. With stepwise multiple regression, carotid PP was calculated from a nomogram including age, sex, body height, brachial PP, and plasma glucose. This model was applied to 125,151 subjects, followed for 12 years, during which 3,997 deaths occurred (735 of CV origin). With Cox regression analysis, multi-adjusted hazard ratios (HRs) were calculated for 1 SD increase of brachial PP, calculated carotid PP, and C/B ratio.
  
  
  RESULTS
  Brachial PP was significantly associated with both CV and all-cause mortality (HR: 1.16, 95% confidence interval [CI]: 1.13 to 1.19, and HR: 1.13, 95% CI: 1.10 to 1.17, respectively). Calculated carotid PP predicted a similar risk (HR: 1.21, 95% CI: 1.15 to 1.28, and HR: 1.18, 95% CI: 1.12 to 1.25, respectively). Finally, the C/B ratio was a strong risk predictor (HR: 1.22, 95% CI: 1.12 to 1.32, and HR: 1.41, 95% CI: 1.14 to 1.73, respectively). Addition of drug treatment and other confounding variables did not statistically modify the results.
  
  
  CONCLUSIONS
  Brachial PP, calculated carotid PP, and C/B PP amplification all predict CV mortality. In contrast to brachial and carotid PP, the C/B ratio is less dependent on blood pressure calibration and thus can be directly applicable to large population studies.
authors.affiliation: Department of Geriatrics CHU de Nancy, and INSERM U691, University of Nancy, Nancy, France.
authors.forename: Athanase
authors.initials: A
authors.lastname: Benetos
authors.forename: Frédérique
authors.initials: F
authors.lastname: Thomas
authors.forename: Laure
authors.initials: L
authors.lastname: Joly
authors.forename: Jacques
authors.initials: J
authors.lastname: Blacher
authors.forename: Bruno
authors.initials: B
authors.lastname: Pannier
authors.forename: Carlos
authors.initials: C
authors.lastname: Labat
authors.forename: Paolo
authors.initials: P
authors.lastname: Salvi
authors.forename: Harold
authors.initials: H
authors.lastname: Smulyan
authors.forename: Michel E
authors.initials: ME
authors.lastname: Safar
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism; D001794:Blood Pressure / Q000502:physiology*; D001827:Body Height; D001916:Brachial Artery / Q000503:physiopathology*; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000401:mortality / Q000503:physiopathology*; D002339:Carotid Arteries / Q000503:physiopathology*; D002423:Cause of Death; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D006973:Hypertension / Q000175:diagnosis / Q000401:mortality / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D012016:Reference Values; D012044:Regression Analysis; D018570:Risk Assessment / Q000706:statistics & numerical data; D012737:Sex Factors; D055815:Young Adult
chemical_list: D015415:Biomarkers; D001786:Blood Glucose