Analysis and interpretation of 24-h blood pressure profiles: appropriate mathematical models may yield deeper understanding

Post-exercise hypotension in male spontaneously hypertensive rats: The issue of calculation method

In spontaneously hypertensive rats, exercise can lead to a post-exercise decrease in blood pressure, named post-exercise hypotension (PEH). This can be following physical training but also after a single bout of mild to moderate exercise when measured with tail-cuff or externalized catheter methods. Our aim was to assess the PEH obtained with different calculation methods and to compare the magnitude of this effect induced by a moderate-intensity continuous exercise or a high-intensity intermittent exercise. Thirteen 16-week-old male spontaneously hypertensive rats performed two types of aerobic exercise (continuous or intermittent) on a treadmill. Arterial pressure was recorded by telemetry for 24 h which was started 3 h before physical exercise. Based on the literature, PEH was first evaluated with two different baseline values, and then with three different approaches. We observed that the identification of PEH depended on the method used to measure the rest value, and that its amplitude was also influenced by the calculation approach and the type of exercise performed. Hence, the calculation method and the amplitude of the detected PEH can significantly influence their physiological and pathophysiological inferences.

Morning Blood Pressure Surge and Cardiovascular Disease Events and All-Cause Mortality in Blacks: The Jackson Heart Study

The cardiovascular disease (CVD) and mortality risk associated with morning blood pressure (BP) surge and its components among black adults, a population with high BP during the asleep period, is unknown. We studied Jackson Heart Study participants who completed 24-hour ambulatory BP monitoring at the baseline exam in 2000 to 2004 (n=761). The sleep-trough morning surge was calculated as the mean 2-hour postawakening systolic BP (SBP) minus the lowest nighttime SBP, preawakening morning surge as mean 2-hour postawakening SBP minus mean 2-hour preawakening SBP, and rising morning surge as the first postawakening SBP minus the last preawakening SBP. The primary outcome was the occurrence of CVD events including the composite of coronary heart disease or stroke. Over a median follow-up of 14.0 years, there were 74 CVD (coronary heart disease or stroke) events and 144 deaths. Higher tertiles of sleep-trough, preawakening, and rising SBP surge were not associated with CVD risk after multivariable adjustment. In contrast, the highest tertile of the individual components of morning surge, including postawakening SBP (tertiles 2 and 3 versus 1: hazard ratio [95% CI]: 1.58 [0.71-3.53] and 4.04 [1.91-8.52], respectively), lowest nighttime SBP (1.29 [0.59-2.84] and 2.87 [1.41-5.83]), preawakening SBP (1.26 [0.57-2.80] and 2.79 [1.32-5.93]), first postawakening SBP (1.60 [0.73-3.51] and 2.93 [1.40-6.16]), and last preawakening SBP (1.23 [0.57-2.68] and 2.99 [1.46-6.12]), was associated with increased CVD risk after multivariable adjustment. Among black adults, the components of morning SBP surge, but not morning SBP surge itself, were associated with increased CVD risk.

Morning surge in blood pressure using a random-effects multiple-component cosinor model

Blood pressure (BP) fluctuates throughout the day. The pattern it follows represents one of the most important circadian rhythms in the human body. For example, morning BP surge has been suggested as a potential risk factor for cardiovascular events occurring in the morning, but the accurate quantification of this phenomenon remains a challenge. Here, we outline a novel method to quantify morning surge. We demonstrate how the most commonly used method to model 24-hour BP, the single cosinor approach, can be extended to a multiple-component cosinor random-effects model. We outline how this model can be used to obtain a measure of morning BP surge by obtaining derivatives of the model fit. The model is compared with a functional principal component analysis that determines the main components of variability in the data. Data from the Mitchelstown Study, a population-based study of Irish adults (n = 2047), were used where a subsample (1207) underwent 24-hour ambulatory blood pressure monitoring. We demonstrate that our 2-component model provided a significant improvement in fit compared with a single model and a similar fit to a more complex model captured by b-splines using functional principal component analysis. The estimate of the average maximum slope was 2.857 mmHg/30 min (bootstrap estimates; 95% CI: 2.855-2.858 mmHg/30 min). Simulation results allowed us to quantify the between-individual SD in maximum slopes, which was 1.02 mmHg/30 min. By obtaining derivatives we have demonstrated a novel approach to quantify morning BP surge and its variation between individuals. This is the first demonstration of cosinor approach to obtain a measure of morning surge.

Exploring diurnal variation using piecewise linear splines: an example using blood pressure

Background

There are many examples of physiological processes that follow a circadian cycle and researchers are interested in alternative methods to illustrate and quantify this diurnal variation. Circadian blood pressure (BP) deserves additional attention given uncertainty relating to the prognostic significance of BP variability in relation to cardiovascular disease. However, the majority of studies exploring variability in ambulatory blood pressure monitoring (ABPM) collapse the data into single readings ignoring the temporal nature of the data. Advanced statistical techniques are required to explore complete variation over 24 h.

Methods

We use piecewise linear splines in a mixed-effects model with a constraint to ensure periodicity as a novel application for modelling daily blood pressure. Data from the Mitchelstown Study, a cross-sectional study of Irish adults aged 47–73 years (n = 2047) was utilized. A subsample (1207) underwent 24-h ABPM. We compared patterns between those with and without evidence of subclinical target organ damage (microalbuminuria).

Results

We were able to quantify the steepest rise and fall in SBP, which occurred just after waking (2.23 mmHg/30 min) and immediately after falling asleep (−1.93 mmHg/30 min) respectively. The variation about an individual’s trajectory over 24 h was 12.3 mmHg (standard deviation). On average those with microalbuminuria were found to have significantly higher SBP (7.6 mmHg, 95% CI 5.0–10.1) after adjustment for age, sex and BMI. Including an interaction term between each linear spline and microalbuminuria did not improve model fit.

Conclusion

We have introduced a practical method for the analysis of ABPM where we can determine the rate of increase or decrease for different periods of the day. This may be particularly useful in examining chronotherapy effects of antihypertensive medication. It offers new measures of short-term BP variability as we can quantify the variation about an individual’s trajectory but also allows examination of the variation in slopes between individuals (random-effects).

Electronic supplementary material

The online version of this article (doi:10.1186/s12982-017-0055-5) contains supplementary material, which is available to authorized users.

Heterogeneity of prognostic studies of 24-hour blood pressure variability: systematic review and meta-analysis

In addition to mean blood pressure, blood pressure variability is hypothesized to have important prognostic value in evaluating cardiovascular risk. We aimed to assess the prognostic value of blood pressure variability within 24 hours. Using MEDLINE, EMBASE and Cochrane Library to April 2013, we conducted a systematic review of prospective studies of adults, with at least one year follow-up and any day, night or 24-hour blood pressure variability measure as a predictor of one or more of the following outcomes: all-cause mortality, cardiovascular mortality, all cardiovascular events, stroke and coronary heart disease. We examined how blood pressure variability is defined and how its prognostic use is reported. We analysed relative risks adjusted for covariates including the appropriate mean blood pressure and considered the potential for meta-analysis. Our analysis of methods included 24 studies and analysis of predictions included 16 studies. There were 36 different measures of blood pressure variability and 13 definitions of night- and day-time periods. Median follow-up was 5.5 years (interquartile range 4.2–7.0). Comparing measures of dispersion, coefficient of variation was less well researched than standard deviation. Night dipping based on percentage change was the most researched measure and the only measure for which data could be meaningfully pooled. Night dipping or lower night-time blood pressure was associated with lower risk of cardiovascular events. The interpretation and use in clinical practice of 24-hour blood pressure variability, as an important prognostic indicator of cardiovascular events, is hampered by insufficient evidence and divergent methodologies. We recommend greater standardisation of methods.

Blood pressure variability, cardiovascular risk, and risk for renal disease progression

The adverse cardiovascular consequences of high blood pressure (BP) not only depend on absolute BP values, but also on BP variability (BPV). Evidence has been provided that independently of mean BP levels, BP variations in the short- and long-term are associated with the development, progression and severity of cardiac, vascular and renal organ damage, and with an increased risk of CV events and mortality. Alterations in BPV have also been shown to be predictive of the development and progression of renal damage, which is of relevance if considering that impaired renal function in a hypertensive patient constitutes a very potent predictor of future CV events and mortality even in treated subjects. This review will address whether antihypertensive treatment should target alterations in BPV, in addition to reducing absolute BP levels, in order to achieve the highest CV and renal protection in hypertensive and renal patients.

Relationship between short-term blood pressure variability and large-artery stiffness in human hypertension: findings from 2 large databases

Short-term blood pressure (BP) variability predicts cardiovascular complications in hypertension, but its association with large-artery stiffness is poorly understood and confounded by methodologic issues related to the assessment of BP variations over 24 hours. Carotid-femoral pulse wave velocity (cfPWV) and 24-hour ambulatory BP were measured in 911 untreated, nondiabetic patients with uncomplicated hypertension (learning population) and in 2089 mostly treated hypertensive patients (83% treated, 25% diabetics; test population). Short-term systolic BP (SBP) variability was calculated as the following: (1) SD of 24-hour, daytime, or nighttime SBP; (2) weighted SD of 24-hour SBP; and (3) average real variability (ARV), that is, the average of the absolute differences between consecutive SBP measurements over 24 hours. In the learning population, all of the measures of SBP variability showed a direct correlation with cfPWV (SD of 24-hour, daytime, and nighttime SBP, r=0.17/0.19/0.13; weighted SD of 24-hour SBP, r=0.21; ARV, r=0.26; all P<0.001). The relationship between cfPWV and ARV was stronger than that with 24-hour, daytime, or nighttime SBP (all P<0.05) and similar to that with weighted SD of 24-hour SBP. In the test population, ARV and weighted SD of 24-hour SBP had stronger relationships with cfPWV than SD of 24-hour, daytime, or nighttime SBP. In both populations, SBP variability indices independently predicted cfPWV along with age, 24-hour SBP, and other factors. We conclude that short-term variability of 24-hour SBP shows an independent, although moderate, relation to aortic stiffness in hypertension. This relationship is stronger with measures of BP variability focusing on short-term changes, such as ARV and weighted 24-hour SD.

Left ventricular hypertrophy and clinical outcomes in hypertensive patients

The prevalence of left ventricular hypertrophy (LVH) rises with severity of hypertension (HT), age, and obesity. Its prevalence ranges from 20% in mildly hypertensive patients to almost 100% in those with severe or complicated HT. However, the diagnosis of LVH is not straightforward, and the definitions and criteria used in clinical studies lack consistency. While many factors play a role in the onset and progression of LVH, blood pressure (BP) is recognized as a central factor. Twenty-four-hour BP measurements are more closely related to LVH than conventional BP readings taken in the clinician's office. Increased renin-angiotensin system (RAS) activity also plays an important role in the development of LVH, and various studies show a correlation between plasma renin activity and left ventricular mass (LVM). LVH is a recognized marker of HT-related target organ damage, and a strong and independent risk factor for adverse cardiovascular (CV) outcomes. CV risk increases with increasing LVM, and decreases with regression of LVH in response to antihypertensive treatment. Therefore the detection, prevention, and reversal of LVH are important goals in HT management. Most antihypertensive drugs can attenuate BP and LVH. However, each drug class may induce LVH regression to a different extent and these extents seldom correlate with the degree of BP reduction achieved. Data from the few large comparative studies in this area suggest that certain classes of antihypertensive drugs and/or their combinations are more effective than others. In particular, calcium channel blockers and drugs that target the RAS, such as angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), appear to have a specific effect on LVH, independent of BP reduction. Guidelines, therefore, have recommended these drug classes for the treatment of hypertensive patients with LVH.