A new study finds that the cumulative systolic blood pressure load, which can be calculated from serial blood pressure measurements, may provide a better prediction of major cardiovascular events than conventional sphygmomanometers.
Our results indicate that cumulative blood pressure is an independent predictor of cardiovascular events and should be used in the future Cardiovascular risk Prediction algorithms,” conclude the authors, led by Nelson Wang, MD, George Institute for Global Health, Sydney, Australia.
study was Posted online In the Journal of the American College of Cardiology On September 12th.
The researchers explained that the management Hypertension It is traditionally centered around blood pressure measurements taken at a single time point, with adequate control specified that those measurements are below a pre-established target threshold.
However, this approach fails to recognize blood pressure as a continuous measure that fluctuates over time and does not recognize that the most recent measurement recorded may not reflect previous blood pressure control.
More recently, studies have identified time a patient spends below target blood pressure, or TIme in TaRgEt (TITRE), as a new marker of cardiovascular risk independent of mean blood pressure.
Although TITER has the added advantage of incorporating the duration of control, it is not able to quantify the magnitude of hypertension, the researchers note.
They noted that the optimal measure as a risk factor for cardiovascular disease would explain the magnitude and duration of hypertension.
This measure is the cumulative blood pressure load, defined as the area under the curve (AUC) expressed in units of mm Hg over time.
The only previous study of this scale was small, retrospective and calculated cumulative blood pressure from estimated ambulatory blood pressure monitoring over a short period (24 h).
Therefore, the aim of the current study was to estimate the relationship between cumulative systolic blood pressure over a longer period (24 months) and subsequent major cardiovascular events.
To do this, the researchers conducted a post-mortem analysis of 9,338 patients Type 2 diabetes In the ADVANCE-ON study.
Cumulative systolic blood pressure load was defined as the AUC of systolic blood pressure values above 130 mm Hg divided by the AUC of all systolic blood pressure values measured over a 24-month exposure period.
Over the 7.6 years of follow-up, 1469 major cardiovascular events, 1615 deaths, and 660 cardiovascular disease deaths occurred.
The results showed that each standard deviation increase in cumulative systolic blood pressure load was associated with a 14% increase in major cardiovascular events, a 13% increase in all-cause mortality, and a 21% increase in cardiovascular mortality.
Cumulative systolic blood pressure exceeded mean systolic blood pressure, time below target, and visit-to-visit systolic blood pressure changed to predict cardiovascular events and death, as well as risk discrimination and more correctly reclassified patients’ risk from other measures.
“Small improvements in risk prediction could have a significant impact when scaled up across large populations at high risk. Furthermore, cumulative systolic pressure may also be useful in designing future clinical trials,” the researchers say.
Although the current study only assessed the cumulative load of systolic blood pressure over 24 months, clinicians should be aware of the importance of this measurement over the lifespan, they note.
They conclude, “This approach underscores the importance of early blood pressure lowering interventions to reduce the cumulative load of systolic blood pressure experienced by each individual throughout their life.”
Based on these findings, the authors suggest that the cumulative load of systolic blood pressure and the variability of visit-to-visit systolic blood pressure “should be used in conjunction in future cardiovascular risk prediction algorithms.”
in accompanying openingDonald Lloyd-Jones, MD, Northwestern Feinberg School of Medicine, Chicago, Illinois, says that before these new procedures are routinely adopted, several additional questions must be addressed.
He noted that many patients in the current study already had cardiovascular disease and it was not known if the benefit was consistent between those with and those without cardiovascular disease. In addition, long-term data using blood pressure measurements in a real-world clinical setting would be desirable, and information on whether these new measures add additional value to existing risk prediction equations.
“Certainly, the following guidelines should reconsider all types of sphygmomanometers, and other potential predictors, to better estimate risk and identify patients with the greatest net benefit from risk-reducing therapies,” comments Lloyd-Jones.
“Ultimately, clinicians must utilize as much information as possible about their patients to understand the cardiovascular risks associated with blood pressure, to identify those who may be most likely to have occult or emerging subclinical organ damage, and to identify those who may have a network Especially benefits from early or intensive treatment.”
“These opportunities are more readily available with data integration that allows for the visualization of long-term blood pressure patterns and the integration of home monitoring and mobile monitoring data to monitor and control blood pressure levels outside the office.”