1 research outputs found
Blood pressure control measures and cardiovascular outcomes: a prospective hypertensive cohort
We investigated whether blood pressure (BP) control measures, visit-to-visit BP variability, and time in therapeutic range (TTR) are associated with future cardiovascular outcomes in hypertensive patients. Among 1,408 hypertensive patients without cardiovascular disease, we prospectively evaluated the incident major cardiovascular events over 6 years. In newly diagnosed patients, antihypertensive drug treatment was initiated. We estimated two markers of on-treatment BP control, (1) visit-to-visit BPV as the coefficient of variation of office systolic BP (BP-CV), and (2) TTR calculated as the percentage of office systolic BP measurements within 120–140mmHg across visits. The hypertensive cohort (672 males, mean age 60 years, 31% newly diagnosed) had a mean systolic/diastolic BP of 142/87 mmHg. The mean number of visits was 4.9 ± 2.6, while the mean attained systolic/diastolic BP during follow-up was 137/79 mmHg using 2.7 ± 1.1 antihypertensive drugs. The BP-CV and TTR were 9.1 ± 4.1% and 45 ± 29%, respectively, and the incidence of the composite outcome was 8.3% (n = 117). After adjustment for relevant confounders and standardization to z-scores, BP-CV and TTR were associated with a 43% (95% CI, 27–62%) increase and a 33% (95% CI, 15–47%) reduction in the outcome. However, the joint evaluation of TTR and BP-CV in a common multivariable model indicated that a standardized change of TTR was associated with the outcome to a greater extent than BP-CV (mean hazard ratios of 30% vs. 24%, respectively). When combined with the higher BP standardized-CV quartile, the lower TTR quartile predicted the outcome by 2.3 times (95% CI, 1.1–5.4) compared to the inverse TTR and BP-CV quartile pattern. High BP-CV or low TTR was associated with future cardiovascular events in a cohort of treated hypertensive patients. As a determinant, the extent of TTR value appears greater than BP-CV when these measures are considered in the same multivariable model.</p