Visit‐to‐visit office blood pressure variability combined with Framingham risk score to predict all‐cause mortality: A post hoc analysis of the systolic blood pressure intervention trial

Abstract

We aim to determine if visit‐to‐visit blood pressure variability (BPV) adds prognostic value for all‐cause mortality independently of the Framingham risk score (FRS) in the systolic blood pressure intervention trial (SPRINT). We defined BPV as variability independent of the mean (VIM) and the difference of maximum minus minimum (MMD) of the systolic blood pressure (SBP). Multivariable Cox proportional hazards models were used to estimate the hazard ratio (HR) and 95% confidence interval (CI). Based on FRS stratification, there were 1035, 2911, and 4050 participants in the low‐, intermediate‐, and high‐risk groups, respectively. During the trial, 230 deaths occurred since the 12th month with an average follow‐up of 2.5 years. In continuous analysis, 1‐SD increase of SBP VIM and MMD were significantly associated with all‐cause mortality (HR 1.18, 95% CI 1.05–1.32, p = .005; and HR 1.21, 95% CI 1.09–1.35, p < .001, respectively). In category analysis, the highest quintile of BPV compared with the lowest quintile had significantly higher risk of all‐cause mortality. Cross‐tabulation analysis showed that the 3rd tertile of SBP VIM in the high‐risk group had the highest HR of all‐cause mortality in total population (HR 4.99; 95% CI 1.57–15.90; p = .007), as well as in intensive‐therapy group (HR 7.48; 95% CI 1.01–55.45; p = .05) analyzed separately. Cross‐tabulation analysis of SBP MMD had the same pattern as VIM showed above. In conclusion, visit‐to‐visit BPV was an independent predictor of all‐cause mortality, when accounting for conventional risk factors or FRS. BPV combined with FRS conferred an increased risk for all‐cause mortality in the SPRINT trial.

Effect of visit-to-visit blood pressure variability on mild cognitive impairment and probable dementia in hypertensive patients receiving standard and intensive blood pressure treatment

“…Meanwhile, the statistical results measured by SD were also showed in Supplementary Tables S1, S2 . Besides, MMD (the difference of maximum minus minimum) meant the delta in blood pressure and Michiaki Nagai have demonstrated the association between MMD and cardiovascular disease ( 16 , 17 ). So, we also included the statistical results measured by MMD in Supplementary Tables S3, S4 .…”

Blood pressure and its variability: classic and novel measurement techniques

“…However, all-cause and cardiovascular mortality was significantly increased only in the highest BPV decile, implying that the pattern of this association might not be linear. The prognostic value of long-term BPV has the greatest amount of evidence, according to post hoc analyses of clinical trials with large cohorts of patients, which demonstrated significant associations between visit-to-visit BPV (mainly measured as standard deviation) and cardiovascular end points 25 , 69 – 78 .…”

“…Interestingly, diastolic BPV was strongly associated with coronary heart disease, especially in patients with a history of cardiovascular disease and low baseline BP levels, which might indicate a pathophysiological mechanism of reduced coronary perfusion during diastole in patients with diastolic BPV 76 . In an analysis of the SPRINT trial 77 , 78 , which enrolled patients with hypertension and high cardiovascular risk, all-cause mortality was independently associated with visit-to-visit systolic BPV quantified using VIM or maximum minus minimum BP levels, but was not associated with systolic BPV quantified using the coefficient of variation. Of note, despite the discrepancies in the findings of these trials, accurate BP evaluation is even more crucial when targeting the lower BP goals proposed by the currently recommended intensive treatment strategy.…”

Visit-To-Visit Blood Pressure Variability and Subthreshold Depressive Symptoms in Older Adults

“…Intraindividual BPV was calculated for each participant using the 3−4 BP measurements collected over the 12-month period as variation independent of mean (VIM), a commonly used index of visit-to-visit BPV that is uncorrelated with average BP levels across visits 8,17,18,21 and better predicts allcause mortality compared to other indices of BPV. 22 VIM was calculated as: VIM = SD/mean x , where the power x was derived from non-linear curve fitting of BP SD against average BP using the nls package in R, 23 as described elsewhere. 21 BPV was also calculated as maximum minus minimum (MMM) BP.…”