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Short-term blood pressure variability

does its prognostic value increase with ageing?

Palatini, Paolo

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doi: 10.1097/HJH.0000000000001799
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The association between ambulatory blood pressure (BP) and target organ damage (TOD) is well established [1–3]. However, whether this relationship persists into old age or even increases with ageing is not well known. In an article published in this issue of the Journal, Olesen et al.[4] showed that the association of ambulatory BP with four markers of TOD in healthy individuals was positively modified by age. The BP–TOD relationship was assessed separately for middle-aged (ages 41 and 51 years) and elderly (ages 61 and 71 years) healthy participants, allowing for comparisons between the two combined age groups. Although 24-h SBP (24hSBP) and DBP (24hDBP) were independently associated with left ventricular mass index (LVMI) in both subgroups, the association was much stronger among the elderly subjects in whom the effect was nearly doubled with a significant interaction between ambulatory BPs and age (P < 0.01). Similar results were obtained for large artery stiffness, especially for 24-h pulse pressure (24hPP), with a 5.9% increase in pulse wave velocity (PWV) for each 5-mmHg increment of 24hPP in the elderly subgroup compared with a 2.6% increase in PWV in the middle-aged subgroup (P for interaction <0.01). Even more striking were the results for kidney damage. In fact, a significant relationship of 24hSBP, 24hDBP, and 24hPP with urinary albumin : creatinine ratio (UACR) was observed only in the older subgroup, whereas no such relationship was found among the younger participants. The different association of 24hSBP and 24hPP with TOD according to age found in the current study may reflect the different role of SBP and PP in elderly compared with younger individuals. A different prognostic value of PP according to age was first demonstrated by Sesso et al. who compared the predictive value of PP for the development of cardiovascular disease among adult-to-elderly versus young-to-middle-aged men [5]. These authors found that in men of at least 60 years, there was a graded increase in risk of cardiovascular disease from the first-to-fourth quartile of PP, whereas among men of less than 60 years, PP was not a significant predictor of adverse outcome and only mean BP was associated with cardiovascular events. In the Hypertension and Ambulatory Recording Venetia Study of individuals 45 years of age or younger, even a negative association was found between PP and development of cardiovascular events in later life as participants in the highest PP tertile had a reduced risk of cardiovascular disease compared with those in the bottom tertile [6]. These data indicate that PP plays a different pathogenetic role in young and elderly individuals. As the authors of the present article [4] point out, PP in the elderly mainly reflects increased arterial stiffness, whereas in younger individuals, high PP is mainly due to increased cardiac output often as a consequence of a high alerting reaction to BP measurement [6].

Quite unexpectedly, in the current study, different age-related results were obtained for the association of ambulatory BP with carotid plaques [4]. The 24hSBP and 24hPP-carotid plaque relationship was weaker among the elderly than the younger participants, and for 24hDBP, there was even a negative interaction between age and BP on carotid plaques (P for interaction = 0.02). Although this finding is difficult to explain, it might be due to the low prevalence of the atherosclerotic disease in this population of healthy individuals which did not allow for a meaningful comparison between the two age groups.

The most intriguing findings of the Olesen et al. study [4] come from the analysis of BP variability (BPV). Whether parameters other than mean ambulatory BP level are predictive of target organ involvement is still a matter for debate. In the last few decades, interest has been focused especially on short-term BPV, but its significance in evaluating risk has not been clearly determined [7–10]. Part of the controversy may be due to the different methods used to compute BPV and/or to the different nature of TOD in published studies. In this respect, the study by Olesen et al.[4] provides new useful information, because the authors made an extensive assessment of TOD, evaluating the effect of BPV on the heart, arterial stiffness, atherosclerotic plaques, and the kidney, and used two different procedures to provide an estimate of BPV. Using average real variability (ARV) to measure BPV, the authors found that ARV of DBP was associated with LVMI and that the association was stronger in elderly [(2.7 (1.4–4.0) g/m2 for 1-mmHg increase in ARV)] than in middle-aged subjects [(1.3 (0.5–2.2) g/m2 for 1-mmHg increase in ARV)]. ARV of DBP was also independently associated with PWV with a 1.2% increase in PWV in middle-aged subjects and a 1.6% increase in PWV in elderly subjects for 1-mmHg increase in ARV. For UACR, a relationship with ARV in multivariable models was found only among the elderly subjects, whereas ARV was not an independent predictor of UACR among the younger participants. The association of ARV with presence of carotid plaques differed in the two age groups for SBP and DBP. In multivariate analyses, ARV of SBP was associated with the presence of plaque in elderly but not in younger subjects, whereas ARV of DBP was associated with plaque presence only in the middle-aged participants.

Although with some inconsistencies, the above findings indicate that in the elderly the impact of BPV on TOD is more pronounced than in younger individuals probably due to the different mechanisms that influence BPV at different ages. The clinical significance of short-term BPV within the 24 h in healthy individuals is still controversial. Some cohort studies have shown that short-term BPV is an independent predictor of cardiovascular disease in general populations [11–13], but little or no association has been found in other studies [14]. In the International Database on Ambulatory Blood Pressure (ABP) in relation to Cardiovascular Outcome, a large study of subjects enrolled in 11 countries, indices of short-term BPV improved the prediction of fatal and nonfatal cardiovascular outcomes only marginally [14]. In hypertensive individuals, BPV appeared to be an important contributor of cardiovascular events and of cardiovascular and total mortality producing a net improvement in patients’ risk-classification [15].

The discrepancy between the results of the various studies may be ascribed to the different characteristics of the study participants. As shown by the results of the Olesen et al. study [4], age in particular can be an important modulator of the relationship between BPV and adverse outcome. In that study, ARV of both SBP and DBPs was higher in the older than the middle-aged participants (P < 0.001). The mechanisms accounting for increased BPV in the old age may differ from those operating at younger ages. In the elderly, increased BPV may reflect a diffuse atherosclerotic process leading to increased stiffness of the large elastic arteries [16,17]. An impaired baroreflex function leading to orthostatic hypotension and to an impairment of cardiovascular control mechanisms is another factor that may contribute to increasing BPV in the old age [16,17]. In contrast, BPV in younger persons may merely reflect the effect of random BP fluctuations in response to the activities of everyday life.

One strength of the current study is that the authors tested not only the impact on TOD of 24-h BPV but also that of daytime BPV and night-time BPV separately. For LVMI, PWV, and UACR, the relationship of TOD with ARV was always stronger for night-time data, whereas the relationship of TOD with daytime ARV was weaker or even absent. The different association of TOD measures with the two 24-h subperiods is not surprising in light of previous findings from the literature. Among the studies that compared the prognostic value of daytime and night-time BPVs, most have found that BPV during the night-time had a greater predictive capacity [18,19]. In the ABP-International study, the cardiovascular risk prediction models including night-time BPV had the smallest Akaike information criterion and Bayesian information criterion indicating that the model including night-time BPV was the most informative one [15]. In keeping with the present findings, in that study daytime BPV did not achieve the level of statistical significance in any multivariable model [15]. Thus, the results by Olesen et al.[4] confirm that within the 24-h subperiods BPV during sleep is the most informative predictor of adverse outcome. The stronger association of night-time BPV with cardiovascular outcomes compared with daytime BPV is not surprising given the fact that patient's nocturnal BPV may be more reproducibly representative of patient's true BPV. During waking hours, BPV may reflect BP changes in response to random activities, including physical activities, BP response to stressful situations, and other environmental factors [15]. Also, a high night-time BPV may reflect episodes of sleep apnoea that in the long run may have detrimental effects on the cardiovascular system.

Another strength of the Olesen et al. study [4] is the use of two different metrics, ARV, and SD, for assessing BPV. ARV is a parameter that calculates short-term BP fluctuations by using the difference between two adjacent measurements, thereby accounting for the order in which the BP measurements are obtained [20,21]. According to some authors, ARV has a greater prognostic value than measures of BP dispersion such as SD which ignores the order in which the measurements are obtained [22]. In a study by Pierdomenico et al.[23], ARV as either a categorical or a continuous variable was an independent predictor of cardiovascular events, whereas SD was not. However, in a study by Leoncini et al.[24], SD and ARV were both associated with the simultaneous presence of two or more signs of TOD in multivariable models. In keeping with the latter study, the present results [4] show that SD is as good as ARV in predicting TOD. For some TOD measures (PWV, UACR), associations were even stronger for SD indicating that this BPV metric, which is widespread and easy to calculate, can be used either for research or in clinical practice. On the other hand, within the frame of the Trial of Preventing Hypertension study, Levitan et al.[25] have shown that SD and ARV were closely correlated to each other (R = 0.83).

Although the results of the Olesen et al. study [4] provides interesting novel information on the relationship between BPV and TOD, an important limitation of the current study should be acknowledged. Several short-term BPV parameters such as ARV and SD are correlated with the mean level of ambulatory BP [1,16,17]. Thus, to establish the independent prognostic capacity of BPV for TOD and cardiovascular disease, these BPV parameters should be adjusted also for average BP in multivariable models. In the Olesen et al. study [4], when average ambulatory BP was included in the multivariable regression models, the associations between BPV and measures of TOD did not attain the level of statistical significance indicating that part of the BPV–TOD association was explained by the effect of the ambulatory BP level on TOD.

In conclusion, the study by Olesen et al.[4] has shown that age is an important modulator of the relationship of ambulatory BP level and variability with arterial stiffness, microvascular damage, and left ventricular hypertrophy. This suggests that high BP may have a more detrimental effect in elderly than younger adults and may account for the more beneficial effect of intensive BP lowering in older subjects [26]. The Olesen et al.'s [4] findings suggest that also BPV may play a role in determining TOD. These data, however, should be interpreted with the caveat that there was no longer a significant BPV–TOD association after adjustment for average BP in the regression models.


Conflicts of interest

There are no conflicts of interest.


1. Mancia G, Parati G. Ambulatory blood pressure monitoring and organ damage. Hypertension 2000; 36:894–900.
2. Devereux RB, Pickering TG. Relationship between the level, pattern and variability of ambulatory blood pressure and target organ damage in hypertension. J Hypertens 1991; 8:S34–S38.
3. Fagard RH, Staessen JA, Thijs L. Relationship between changes in left ventricular mass and in clinic and ambulatory blood pressure in response to antihypertensive therapy. J Hypertens 1997; 15:1493–1502.
4. Olesen TB, Pareek M, Stidsen JV, Blicher MK, Rasmussen S, Vishram-Nielsen JKK. Impact of age on the association between 24-h ambulatory blood pressure measurements and target organ damage. J Hypertens 2018; 36:1895–1901.
5. Sesso HD, Stampfer MJ, Rosner B, Hennekens CH, Gaziano JM, Manson JE, Glynn RJ. Systolic and diastolic blood pressure, pulse pressure, and mean arterial pressure as predictors of cardiovascular disease risk in men. Hypertension 2000; 36:801–807.
6. Saladini F, Fania C, Mos L, Mazzer A, Casiglia E, Palatini P. Office pulse pressure is a predictor of favourable outcome in young-to-middle-aged subjects with stage 1 hypertension. Hypertension 2017; [Epub ahead of print].
7. Palatini P, Penzo M, Racioppa A, Zugno E, Guzzardi G, Anaclerio M, et al. Clinical relevance of night-time blood pressure and daytime blood pressure variability. Arch Intern Med 1992; 152:1855–1860.
8. Frattola A, Parati G, Cuspidi C, Albini F, Mancia G. Prognostic value of 24-hour blood pressure variability. J Hypertens 1993; 11:1133–1137.
9. Sasaki S, Yoneda Y, Fujita H, Uchida A, Takenaka K, Takesako T, et al. Association of blood pressure variability with induction of atherosclerosis in cholesterol-fed rats. Am J Hypertens 1994; 7:453–459.
10. Verdecchia P, Borgioni C, Ciucci A, Gattobigio R, Schillaci G, Sacchi N, et al. Prognostic significance of blood pressure variability in essential hypertension. Blood Press Monit 1996; 1:3–11.
11. Kikuya M, Hozawa A, Ohkubo T, Tsuji I, Michimata, Matsubara M, et al. Prognostic significance of blood pressure and heart rate variabilities: the Ohasama Study. Hypertension 2000; 36:901–906.
12. Mancia G, Bombelli M, Facchetti R, Madotto F, Corrao G, Trevano FQ, et al. Long-term prognostic value of blood pressure variability in the general population: results of the Pressioni Arteriose Monitorate e LoroAssociazioni Study. Hypertension 2007; 49:1265–1270.
13. Sander D, Kukla C, Klingelhofer J, Winbeck K, Conrad B. Relationship between circadian blood pressure patterns and progression of early carotid atherosclerosis: a 3-year follow-up study. Circulation 2000; 102:1536–1541.
14. Hansen TW, Thijs L, Li Y, Boggia J, Kikuya M, Bjorklund-Bodegard K, et al. Prognostic value of reading to-reading blood pressure variability over 24 hours in 8938 subjects from 11 populations. Hypertension 2010; 55:1049–1057.
15. Palatini P, Reboldi G, Beilin LJ, Casiglia E, Eguchi K, Imai Y, et al. Added predictive value of night-time blood pressure variability for cardiovascular events and mortality: the Ambulatory Blood Pressure-International Study. Hypertension 2014; 64:487–493.
16. Mancia G. Short- and long-term blood pressure variability: present and future. Hypertension 2012; 60:512–517.
17. Parati G, Ochoa JE, Lombardi C, Bilo G. Assessment and management of blood pressure variability. Nat Rev Cardiol 2013; 10:143–155.
18. Eguchi K, Ishikawa J, Hoshide S, Pickering TG, Schwartz JE, Shimada K, et al. Night time blood pressure variability is a strong predictor for cardiovascular events in patients with type 2 diabetes. Am J Hypertens 2009; 22:46–51.
19. Ozawa M, Tamura K, Okano Y, Matsushita K, Yanagi M, Tsurumi-Ikeya Y, et al. Identification of an increased short-term blood pressure variability on ambulatory blood pressure monitoring as a coronary risk factor in diabetic hypertensives. Clin Exp Hypertens 2009; 31:259–270.
20. van Gestel AJ, Camen G, Clarenbach CF, Sievi N, Rossi VA, Kohler M. Quantifying the speed of fluctuations in systolic blood pressure. Hypertens Res 2013; 36:1039–1044.
21. Zakopoulos NA, Tsivgoulis G, Barlas G, Papamichael C, Spengos K, Manios E, et al. Time rate of blood pressure variation is associated with increased common carotid artery intima–media thickness. Hypertension 2005; 45:505–512.
22. Mena LJ, Felix VG, Melgarejo JD, Maestre GE. 24-Hour blood pressure variability assessed by average real variability: a systematic review and meta-analysis. J Am Heart Assoc 2017; 6:e006895.
23. Pierdomenico SD, Di Nicola M, Esposito AL, Di Mascio R, Ballone E, Lapenna D, et al. Prognostic value of different indices of blood pressure variability in hypertensive patients. Am J Hypertens 2009; 22:842–847.
24. Leoncini G, Viazzi F, Storace G, Deferrari G, Pontremoli R. Blood pressure variability and multiple organ damage in primary hypertension. J Hum Hypertens 2013; 27:663–670.
25. Levitan EB, Kaciroti N, Oparil S, Julius S, Muntner P. Relationships between metrics of visit-to-visit variability of blood pressure. J Hum Hypertens 2013; 27:589–593.
26. Wright JT Jr, Williamson JD, Whelton PK, Snyder JK, Sink KM, Rocco MV, et al. A randomized trial of intensive versus standard blood-pressure control. N Engl J Med 2015; 373:2103–2116.
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