Modification over time of pulse wave velocity parallel to changes in aortic BP, as well as in 24-h ambulatory brachial BP

• Published in: Journal of human hypertension Vol. 30; no. 3; pp. 186 - 190
• Main Authors: Oliveras, A, Segura, J, Suarez, C, García-Ortiz, L, Abad-Cardiel, M, Vigil, L, Gómez-Marcos, M A, Sans Atxer, L, Martell-Claros, N, Ruilope, L M, de la Sierra, A
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01-03-2016; Nature Publishing Group
• Subjects: 692/308; 692/499; Aged; Ambulatory care; Aorta; Arterial Pressure; Blood pressure; Blood Pressure Monitoring, Ambulatory; Care and treatment; Diabetes; Diabetes mellitus (non-insulin dependent); Epidemiology; Female; Health Administration; Humans; Hypertension; Male; Management; Measurement techniques; Medicine; Medicine & Public Health; Metabolic syndrome; Middle Aged; Mortality; original-article; Public Health; Pulse Wave Analysis; Risk factors; Spain; Type 2 diabetes; Vascular Stiffness; Velocity; Spain
• ISSN: 0950-9240; 1476-5527
• DOI: 10.1038/jhh.2015.62

Arterial stiffness as assessed by carotid–femoral pulse wave velocity (cfPWV) is a marker of preclinical organ damage and a predictor of cardiovascular outcomes, independently of blood pressure (BP). However, limited evidence exists on the association between long-term variation (Δ) on aortic BP (aoBP) and ΔcfPWV. We aimed to evaluate the relationship of ΔBP with ΔcfPWV over time, as assessed by office and 24-h ambulatory peripheral BP, and aoBP. AoBP and cfPWV were evaluated in 209 hypertensive patients with either diabetes or metabolic syndrome by applanation tonometry (Sphygmocor) at baseline(b) and at 12 months of follow-up(fu). Peripheral BP was also determined by using validated oscillometric devices (office(o)-BP) and on an outpatient basis by using a validated (Spacelabs-90207) device (24-h ambulatory BP). ΔcfPWV over time was calculated as follows: ΔcfPWV=[(cfPWV
fu
–cfPWV
b
)/cfPWV
b
] × 100. ΔBP over time resulted from the same formula applied to BP values obtained with the three different measurement techniques. Correlations (Spearman ‘Rho’) between ΔBP and ΔcfPWV were calculated. Mean age was 62 years, 39% were female and 80% had type 2 diabetes. Baseline office brachial BP (mm Hg) was 143±20/82±12. Follow-up (12 months later) office brachial BP (mm Hg) was 136±20/79±12. ΔcfPWV correlated with ΔoSBP (Rho=0.212;
P
=0.002), Δ24-h SBP (Rho=0.254;
P
<0.001), Δdaytime SBP (Rho=0.232;
P
=0.001), Δnighttime SBP (Rho=0.320;
P
<0.001) and ΔaoSBP (Rho=0.320;
P
<0.001). A multiple linear regression analysis included the following independent variables: ΔoSBP, Δ24-h SBP, Δdaytime SBP, Δnighttime SBP and ΔaoSBP. ΔcfPWV was independently associated with Δ24-h SBP (β-coefficient=0.195;
P
=0.012) and ΔaoSBP (β-coefficient= 0.185;
P
=0.018). We conclude that changes in both 24-h SBP and aoSBP more accurately reflect changes in arterial stiffness than do office BP measurements.