Elastic pulse pressure predicts total, CVD mortality in hypertensive patients

14 Jun 2020
Is there enough attention being paid to incremental care?Is there enough attention being paid to incremental care?

Elastic pulse pressure (elPP), but not systolic stiffening PP (stPP), is a risk factor for total and cardiovascular disease (CVD) mortality, particularly among treated hypertensive patients, even when adjusted for mean arterial pressure (MAP) and conventional risk factors in the subpopulations with slower pulse rate, a Japan study has shown.

A total of 1,745 participants (mean age, 61.4 years; 65 percent women) were included, of whom 580 died (212 of CVD) and 290 had a stroke during 17 years of follow-up. PP showed a robust association with elPP (r, 0.89) and less with stPP (r, 0.58). The association between the two PP components was weak (r, 0.15).

The hazard ratio (HR) of PP per 1 SD increment after the adjustment was 1.095 (95 percent confidence interval [CI], 0.973–1.232) for total mortality, 1.207 (95 percent CI, 1.000–1.456) for CVD mortality, and 0.983 (95 percent CI, 0.829–1.166) for stroke morbidity. Corresponding HRs for elPP and stPP did not reach statistical significance.

However, elPP (per 1 SD increment) predicted total (327 deaths; HR, 1.231, 95 percent CI, 1.082–1.401) and CVD mortality (131 deaths; HR, 1.294, 95 percent CI, 1.069–1.566) among participants with median pulse rate 68.5 bpm (n=872).

ElPP also predicted total (177 deaths; HR, 1.357, 95 percent CI, 1.131–1.628) and CVD mortality (77 deaths; HR, 1.417, 95 percent CI, 1.092–1.839) in the subgroup of treated individuals with hypertension and pulse rate 68.5 bpm (n=309). Of note, neither PP nor its components predicted stroke morbidity.

This study included participants of the Ohasama study without history of CVD. The investigators derived the PP components from 24-h systolic and diastolic blood pressure using a model based on the nonlinear pressure–volume relationship in arteries expressing pressure stiffness relationship.

Cox regression models were used to estimate outcome predictive power, with adjustments for age, sex, body mass index, smoking, alcohol drinking, diabetes mellitus, total cholesterol, antihypertensive treatment, and MAP, whenever appropriate.

J Hypertens 2020;38:1286-1292