A reliable index for the prognostic significance of blood pressure variability

J Hypertens. 2005 Mar;23(3):505-11. doi: 10.1097/01.hjh.0000160205.81652.5a.


Objectives: This study presents a reliable index inspired by the total variability concept of real analysis in mathematics, called average real variability (ARV), for the prognostic significance of blood pressure variability (BPV) overcoming the pitfalls of the commonly used standard deviation (SD).

Background: Recent studies have suggested that an increase in BPV is associated with an increase in subsequent cardiovascular events/complications. However, there are other studies where the cited association was not found or was lost in the presence of other well-known risk factors. An explanation for these apparently contradictory results may be the selection of the variability index used (SD).

Methods: Ambulatory blood pressure monitoring in 312 subjects aged > or = 55 years. Logistic regression models and survival methods were used to establish the prognostic significance of awake systolic BPV: in particular, (i) the performance of ARV versus SD, and (ii) the value of BPV relative to other well-known risk factors.

Results: The analyses using the ARV index show a statistically significant relative risk equal to 4.548 (P = 0.006) for the group with high BPV with respect to the low BPV group (reference level); in contrast, the corresponding relative risk associated to the SD index was not statistically significant. Furthermore, ARV exhibited a similar predictive value to systolic blood pressure.

Conclusions: The proposed ARV index is a more reliable representation of time series variability than SD and may be less sensitive to the relative low sampling frequency of the ambulatory blood pressure monitoring devices. The results suggest that ARV adds prognostic value to the ABPM and could prompt the use of therapeutic measures to control BPV.

Publication types

  • Validation Study

MeSH terms

  • Aged
  • Blood Pressure Monitoring, Ambulatory / statistics & numerical data*
  • Blood Pressure*
  • Humans
  • Hypertension / diagnosis
  • Hypertension / mortality*
  • Logistic Models
  • Longitudinal Studies
  • Middle Aged
  • Models, Cardiovascular*
  • Predictive Value of Tests
  • Prognosis
  • Proportional Hazards Models
  • Reproducibility of Results
  • Risk Factors