In their study, Boubouchairopoulou and coworkers demonstrate that blood pressure variability (BPV) is not interchangeable when assessed in the office, at home, or under ambulatory conditions [1]. Office BPV was lower than home BPV, and ambulatory BPV was higher than home BPV. Correlations and agreement between office and out-of-office BPV were weak and only marginally stronger between out-of-office measures. No BPV index demonstrated clear superiority. Regardless of the measure used for estimating BPV and the context (office, home, or ambulatory condition), significant determinants of higher BPV were female sex, increased age, elevated body mass index, cigarette smoking, and increased systolic BP.

The finding that short-term, mid-term, and long-term fluctuations are only weakly interrelated is not new. Measurements taken in the office, at home, or under ambulatory conditions reflect different situations and are affected by different pathophysiological, clinical, and behavioral factors that may influence cardiovascular system function (Fig. 1). Consequently, BPVs measured in different contexts do not reflect the same phenomenon. The value of the present work is the comparison of all three measures in the same subjects. The study adds and confirms two previous studies based on a smaller sample of subjects with different characteristics in which a less robust methodology for estimating BPV was used [2, 3].

Fig. 1
figure 1

Major types of blood pressure variability and their main determinants. BPV blood pressure variability

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Despite the poor agreement of BPV estimates between settings, the magnitude of the correlation was similar for the different measures of BPV (standard deviation or SD, coefficient of variation or CV, and variability independent of mean or VIM). Using the same analytical approach in the three settings allowed excluding potential bias effects of different methodologies applied to the calculation of BPV. Indeed, the methodology for calculating BPV is highly heterogeneous in various studies, and currently, there is no consensus on how to best measure BPV. Although the authors did not attempt to perform correlation analysis between BPV measures within each context, we may assume that the interrelation was high, and thus the different estimates may provide similar information in the same context. This hypothesis is suggested from studies linking BPV with an increased risk of adverse cardiovascular outcomes and mortality. According to these prognostic studies, different indices of BPV appear to predict outcome to a relatively similar extent, irrespective of the type of calculation employed (Table 1) [4,5,6,7,8,9,10,11,12].

Table 1 Risk of all-cause and cardiovascular mortality, and cardiovascular events according to the type of systolic blood pressure variability in major population studies and meta-analyses
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Despite its several merits, the paper of Boubouchairopoulou and coworkers is not exempt from some flaws. The office BP measurement was accomplished for most subjects via auscultatory measurement using a mercury sphygmomanometer. In only 15% of subjects was office BP measured with the same oscillometric technology used to measure home and ambulatory BP. Such an approach may have negatively affected the estimation of office BPV. As the digit preference phenomenon may influence auscultatory BP measurement, this may have contributed to blunting the extent of BP variations. Oscillometric BP measurement represents a more objective BP measurement and provides more realistic estimates of BPV: using the same oscillometric technology in the three settings would have rendered the results more robust.

BP measurements were made following the European Society of Hypertension recommendations [13]. However, the accuracy of BPV estimation is highly dependent on the number of measurements used for analysis. Although the median number of measurements obtained over the 24 h for the whole sample (n = 68) complied with current recommendations [14], some patients barely had a minimum number of readings (lower interquartile range in the whole sample = 64); this was insufficient to ensure an accurate estimation of BPV, which must ideally be based on readings obtained every 15–20 min, allowing the collection of 72–96 readings [15].

The authors used SD, CV, and VIM as measures of BPV. These are well-acknowledged estimates of BPV with their pros and cons [16]. Notably, CV and VIM, as opposed to SD, are unrelated to the effect of the average and should be preferred in the assessment of BPV. Disappointingly, the authors did not include average real variability (ARV), another widely used and studied measure of BPV independent of the mean. With SD and CV (as opposed to VIM, which relies on a statistical analysis), ARV can be easily calculated, and it shows a strong association with the progression of subclinical organ damage and cardiovascular events [17].

Finally, as correctly acknowledged by the authors, some crucial factors, such as physical activity and psychosocial or social factors known to potentially affect the magnitude of BP variations, could not be evaluated. These factors must be considered in future studies.

In conclusion, the study of Boubouchairopoulou and coworkers has the merit of demonstrating for the first time that BPV measured in the office, at home, and in ambulatory conditions provides different information. Hence, estimates of BP variations observed in different contexts should be considered equally helpful in providing a comprehensive picture of BP control in an individual patient. Of course, the lack of standard reference values for BPV and high-quality longitudinal data requires caution in interpreting the value of BPV.