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Blood pressure variability and risk of stroke in chronic kidney disease

Angeli, Fabioa; Reboldi, Gianpaolob; Verdecchia, Paoloc

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doi: 10.1097/HJH.0000000000002339
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Chronic kidney disease (CKD), defined as structural [increased albumin-to-creatinine ratio (ACR), abnormal imaging, histology, or urine sediment] or functional damage [estimated glomerular filtration rate (eGFR) lower than 60 ml/min per 1.73 m2] for at least 3 months [1], is a major public health problem with an estimated worldwide prevalence of approximately 10% [2–4].

Cardiovascular disease is the leading cause of death in patients with CKD [5]. In the last years, much focus has been given to the high rate of cardiac complications in CKD patients [6]; nonetheless, more attention should be given to the debilitating burden of cerebrovascular disease among CKD patients. Indeed, the risk of stroke in CKD has been reported to be significantly greater than that in the general population and a graded and independent relationship between eGFR and stroke risk has been clearly reported in several studies [7–10]. The prospective Atherosclerosis Risk in Communities study [8] demonstrated that CKD, defined as an eGFR less than 60 ml/min per 1.73 m2, increased the risk for stroke about two-fold [hazard ratio 1.81, 95% confidence interval (CI) 1.26--2.02], even after adjustment for traditional cardiovascular risk factors [8]. Similar results were documented by the multicenter Prevention Regimen for Effectively Avoiding Second Strokes Trial [10] and by a systematic review and meta-analysis of prospective studies for a total of 284 672 participants (follow-up 3.2–15 years, 7863 stroke events) [9]. These reports [9,10] showed a 43% increased risk of stroke among participants with an eGFR less than 60 ml/min per 1.73 m2 [relative risk (RR) 1.43, 95% CI 1.31--1.57; P < 0.001; normal reference: eGFR >60 ml/min per 1.73 m2 or >90 ml/min per 1.73 m2] [9], and very high risks among patients with an eGFR less than 40 ml/min per 1.73 m2 (RR: 1.77, 95% CI 1.32--2.38) [9,10]. As such, averting future cerebrovascular events in patients with a low eGFR should be a primary goal.

Among modifiable risk factors for cerebrovascular accidents in CKD, hypertension is the major contributor for both ischemic and hemorrhagic stroke with risk increasing with worsening blood pressure (BP) control [11,12]. In this context, current guidelines [13,14] recommend multiple readings before making a diagnosis of hypertension as well as before initiation and titration of BP-lowering drugs. Thus, BP variability recorded over multiple time-frames adds to the complexity in managing hypertension. The picture is further complicated by the evidence that elevated long-term (visit-to-visit) BP variability may be associated with adverse outcomes in CKD [15–18]. Higher visit-to-visit BP variability in patients with CKD has been associated with mortality and incident cardiovascular events [15–18]. In a recent retrospective analysis from Kaiser Permanente Northern California population [15], visit-to-visit BP variability was assessed over 6 months in a community-based cohort of 114 900 adults with CKD stages 3 and 4 (eGFR 15–59 ml/min per 1.73 m2). The highest versus the lowest quintile of the coefficient of variation was associated with higher adjusted rates of death (hazard ratio 1.22; 95% CI 1.11--1.34) and hemorrhagic stroke (hazard ratio 1.91; 95% CI 1.36--2.68). On the contrary; BP variability was inconsistently associated with heart failure and end-stage renal disease, and was not significantly associated with acute coronary syndrome or ischemic stroke.

For the limited amount of available data regarding the relationship between BP variability and stroke in CKD, results of the analysis by Li et al.[19] published in the current issue of the Journal are welcome. Briefly, the present post hoc analysis of the China Stroke Primary Prevention Trial (CSPPT) [19] evaluated the relation of visit-to-visit BP variability with the risk of first stroke, and examined any possible effect modifiers in hypertensive patients with mild-to-moderate CKD. Overall, data from 3091 hypertensive patients with eGFR 30–60 ml/min per 1.73 m2 and/or proteinuria at baseline were included. BP measurements were collected at baseline, randomization, and every 3 months thereafter. Standard deviation (SD) and coefficient of variation (calculated as SD divided by the mean) of BP were used as visit-to-visit parameters and were determined using all available BP measurements [19]. During the median follow-up time of 3.7 years, a first stroke occurred in 92 (3.0%) participants. After multivariable adjustment, including baseline SBP and mean SBP during the first 12-month treatment period, there was a significant direct relationship of SBP variability with the risk of first stroke (hazard ratio 1.41; 95% CI 1.17--1.69, per 1-SD increment). Moreover, the results were consistent for SD of DBP, and for coefficient of variation of SBP/DBP [19]. As acknowledged by the authors, this study suffers from some limitations, including its design and statistical plan; indeed, post hoc observations from a clinical trial should be treated with extreme caution irrespective of their statistical significance [20,21]. With this background in mind, some information and strengths of the study need to be mentioned.

Exploring the prognostic relevance of visit-to-visit BP variability, all BP data preceding the occurrence of the outcome or censoring are generally used to compute BP variability. This is a main concern on the validity of results for the overlap of the variable-length exposure and outcome periods and a time-varying approach appears more appropriate and convenient. At this regard, Li et al.[19] included some sensitivity analyses to evaluate the impact of BP variability in some subgroups as defined by participants with greater than two BP measurements during the first 6 months or the first 18 months from randomization, and by the available number of BP measurements. Of note, results remained consistent across all these subgroups.

Furthermore, Li et al.[19] demonstrated that visit-to-visit BP variability is related to the risk of incident stroke independent of some confounding factors, including age, sex, diabetes, number of concomitant antihypertensive medications used, and treatment compliance. Even more important, estimates of long-term BP variability proved to be useful for prognosis after adjustment for the corresponding SBP treated as time-dependent variable in the survival models. Notwithstanding, it is not entirely clear whether the two metrics (SD and coefficient of variation) used to estimate BP variability add comparable predictive power to a model formed by simple, easily available clinical variables in patients with CKD.

Finally, long-term BP variability might also result from poor adherence to antihypertensive therapy. Kronish et al.[22] assessed the association between antihypertensive medication adherence and visit-to-visit BP variability in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). Participants who reported taking less than 80% of their antihypertensive medication at at least one study visit were categorized as nonadherent. SD independent of mean of BP was higher for nonadherent versus adherent participants (11.4 ± 4.9 versus 10.5 ± 4.5 for SBP; 6.8 ± 2.8 versus 6.2 ± 2.6 for DBP, each P < 0.001). SD independent of mean of BP remained higher among nonadherent than among adherent participants after multivariable adjustment. Of note, adjustment for nonadherence did not explain the association of visit-to-visit BP variability with higher fatal coronary heart disease or nonfatal myocardial infarction, stroke, heart failure, or mortality risk. Such results suggest that BP variability is associated with cardiovascular outcomes independent of medication adherence. Li et al.[19] further highlight this issue in CKD patients. In their analysis, BP measurements were taken at baseline, randomization, and every 3 months thereafter. BP variability was determined using all available BP measurements following the same prescription from the randomization visit to the 12-month visit. Specifically, Li and co-workers [19] removed from the determination of variability the BP values of the visit at which antihypertensive prescription were modified. Such attempt may have a role in limiting the confounding effect of nonadherence on prognosis.

In conclusion, as stroke is a leading cause of mortality and morbidity worldwide [11], and BP control may reduce subsequent cerebrovascular disease in patients with CKD [12], it is important to identify the CKD patients at increased risk of stroke and treat them more intensively [23–29]. To date, estimates of long-term BP variability may be considered as potentially useful for stroke risk stratification in CKD patients. However, available data are relatively limited and do not support conclusive recommendations. Such aspects need to be addressed in future studies in patients with CKD, also to clarify whether lowering BP variability reduces adverse outcomes. Last but not least, the biological mechanisms underlying the association between BP variability, CKD and stroke need to be more clearly determined (Fig. 1). Various mechanisms may be involved in the association between kidney dysfunction, high BP variability and cerebral blood flow [30–33] (Fig. 1). The brain and kidney share similar microvasculature and vasoregulation behavior. Both organs are perfused by low-resistance vascular circuits, which permit continuous high-volume blood flow during systole and diastole. Small vessels in other organs are protected by upstream vasoconstriction; conversely, small arteries in the brain and kidney are constantly exposed to fluctuations in pressure, and flow because of low vascular resistance and upstream vasodilation [30–33]. To maintain relatively constant blood flow to the brain with variable systemic BP, the brain vasculature displays cerebral autoregulation to minimize hypoperfusion during low BP states and hyperperfusion during high BP states [30–33]. Thus, elevated BP variability may increase susceptibility of brain and kidney to microvascular dysfunction, leading to endothelial dysfunction. Of note, cerebral autoregulation is a complex intrinsic control mechanism maintaining a constant blood flow by changing cerebral vascular resistance in response to changing BP, cerebral perfusion pressure, or metabolic needs, and depends on preserved endothelial function [30–33]. Similarly, endothelial dysfunction in the kidney holds a key position as a central link of the intricate and intertwining pathways involved in the pathogenesis of CKD [34–38]. Finally, both CKD and high BP variability promotes carotid atherosclerosis, platelet dysfunction, oxidative stress, inflammation, reduced cerebral oxygenation and development of atrial fibrillation [34–38] (Fig. 1). More specifically, the augmented mechanical stress on the vascular system (which leads to vascular remodeling) and the increased variability of blood flow by augmented BP variability increases sheer stress on endothelial cells advancing atherosclerosis [34–38]. Sheer stress-induced platelet activation at atherosclerotic stenotic sites, and subsequent hypercoagulability may lead to cerebrovascular events [34–38]. Thus, when CKD and elevated BP variability coexist, the risk of stroke is expected to dramatically increase.

FIGURE 1
FIGURE 1:
Potential mechanisms linking elevated blood pressure variability, chronic kidney disease and risk of stroke (see text for details). BP, blood pressure variability; CBF, cerebral blood flow; CKD, chronic kidney disease.

ACKNOWLEDGEMENTS

Conflicts of interest

There are no conflicts of interest.

REFERENCES

1. The KDIGO Working Group. KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney Int Suppl 2013; 3:1–150.
2. Hill NR, Fatoba ST, Oke JL, Hirst JA, O’Callaghan CA, Lasserson DS, et al. Global prevalence of chronic kidney disease - a systematic review and meta-analysis. PLoS One 2016; 11:e0158765.
3. Jha V, Garcia-Garcia G, Iseki K, Li Z, Naicker S, Plattner B, et al. Chronic kidney disease: global dimension and perspectives. Lancet 2013; 382:260–272.
4. Angeli F, Gentile G, Trapasso M, Verdecchia P, Reboldi G. Role and prognostic value of individual ambulatory blood pressure components in chronic kidney disease. J Hum Hypertens 2018; 32:625–632.
5. Schiffrin EL, Lipman ML, Mann JF. Chronic kidney disease: effects on the cardiovascular system. Circulation 2007; 116:85–97.
6. Di Angelantonio E, Danesh J, Eiriksdottir G, Gudnason V. Renal function and risk of coronary heart disease in general populations: new prospective study and systematic review. PLoS Med 2007; 4:e270.
7. Hojs Fabjan T, Hojs R. Stroke and renal dysfunction. Eur J Intern Med 2014; 25:18–24.
8. Abramson JL, Jurkovitz CT, Vaccarino V, Weintraub WS, McClellan W. Chronic kidney disease, anemia, and incident stroke in a middle-aged, community-based population: the ARIC Study. Kidney Int 2003; 64:610–615.
9. Lee M, Saver JL, Chang KH, Liao HW, Chang SC, Ovbiagele B. Low glomerular filtration rate and risk of stroke: meta-analysis. BMJ 2010; 341:c4249.
10. Ovbiagele B, Bath PM, Cotton D, Sha N, Diener HC. and Investigators PR. Low glomerular filtration rate, recurrent stroke risk, and effect of renin-angiotensin system modulation. Stroke 2013; 44:3223–3225.
11. Benjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, et al. American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Heart Disease and Stroke Statistics-2018 update: a report from the American Heart Association. Circulation 2018; 137:e67–e492.
12. Cheung AK, Rahman M, Reboussin DM, Craven TE, Greene T, Kimmel PL, et al. SPRINT Research Group. Effects of Intensive BP Control in CKD. J Am Soc Nephrol 2017; 28:2812–2823.
13. Williams B, Mancia G, Spiering W, Agabiti Rosei E, Azizi M, Burnier M, et al. List of authors/Task Force members. 2018 Practice Guidelines for the management of arterial hypertension of the European Society of Hypertension and the European Society of Cardiology: ESH/ESC Task Force for the Management of Arterial Hypertension. J Hypertens 2018; 36:2284–2309.
14. Angeli F, Reboldi G, Trapasso M, Gentile G, Pinzagli MG, Aita A, Verdecchia P. European and US guidelines for arterial hypertension: similarities and differences. Eur J Intern Med 2019; 63:3–8.
15. Chang TI, Tabada GH, Yang J, Tan TC, Go AS. Visit-to-visit variability of blood pressure and death, end-stage renal disease, and cardiovascular events in patients with chronic kidney disease. J Hypertens 2016; 34:244–252.
16. Di Iorio B, Pota A, Sirico ML, Torraca S, Di Micco L, Rubino R, et al. Blood pressure variability and outcomes in chronic kidney disease. Nephrol Dial Transplant 2012; 27:4404–4410.
17. Mallamaci F, Minutolo R, Leonardis D, D’Arrigo G, Tripepi G, Rapisarda F, et al. Long-term visit-to-visit office blood pressure variability increases the risk of adverse cardiovascular outcomes in patients with chronic kidney disease. Kidney Int 2013; 84:381–389.
18. Mallamaci F, Tripepi G, D’Arrigo G, Borrelli S, Garofalo C, Stanzione G, et al. Blood pressure variability, mortality, and cardiovascular outcomes in chronic kidney disease patients. Clin J Am Soc Nephrol 2019; 14:233–240.
19. Li Y, Zhou H, Liu M, Liang M, Wang G, Wang B, et al. Association of visit-to-visit variability in blood pressure and first stroke risk in hypertensive patients with chronic kidney disease. J Hypertens 2020; 38:610–617.
20. Rothwell PM. Treating individuals 2. Subgroup analysis in randomised controlled trials: importance, indications, and interpretation. Lancet 2005; 365:176–186.
21. Reboldi G, Angeli F, Verdecchia P. Multivariable analysis in cerebrovascular research: practical notes for the clinician. Cerebrovasc Dis 2013; 35:187–193.
22. Kronish IM, Lynch AI, Oparil S, Whittle J, Davis BR, Simpson LM, et al. The association between antihypertensive medication nonadherence and visit-to-visit variability of blood pressure: findings from the antihypertensive and lipid-lowering treatment to prevent heart attack trial. Hypertension 2016; 68:39–45.
23. Angeli F, Verdecchia P, Reboldi G. Tight blood pressure control saves lives in hypertensive patients with chronic kidney disease. Hypertension 2019; 73:1172–1173.
24. Angeli F, Verdecchia P, Reboldi GP, Gattobigio R, Bentivoglio M, Staessen JA, Porcellati C. Calcium channel blockade to prevent stroke in hypertension: a meta-analysis of 13 studies with 103,793 subjects. Am J Hypertens 2004; 17:817–822.
25. Reboldi G, Angeli F, Cavallini C, Gentile G, Mancia G, Verdecchia P. Comparison between angiotensin-converting enzyme inhibitors and angiotensin receptor blockers on the risk of myocardial infarction, stroke and death: a meta-analysis. J Hypertens 2008; 26:1282–1289.
26. Reboldi G, Gentile G, Angeli F, Verdecchia P. The 2018 ESC/ESH hypertension guidelines: Should nephrologists always stop at the lower boundary? J Nephrol 2018; 31:621–626.
27. Verdecchia P, Gentile G, Angeli F, Reboldi G. Beyond blood pressure: evidence for cardiovascular, cerebrovascular, and renal protective effects of renin-angiotensin system blockers. Ther Adv Cardiovasc Dis 2012; 6:81–91.
28. Verdecchia P, Reboldi G, Angeli F, Gattobigio R, Bentivoglio M, Thijs L, et al. Angiotensin-converting enzyme inhibitors and calcium channel blockers for coronary heart disease and stroke prevention. Hypertension 2005; 46:386–392.
29. Verdecchia P, Reboldi G, Angeli F, Trimarco B, Mancia G, Pogue J, et al. Systolic and diastolic blood pressure changes in relation with myocardial infarction and stroke in patients with coronary artery disease. Hypertension 2015; 65:108–114.
30. Armstead WM. Cerebral blood flow autoregulation and dysautoregulation. Anesthesiol Clin 2016; 34:465–477.
31. Carlstrom M, Wilcox CS, Arendshorst WJ. Renal autoregulation in health and disease. Physiol Rev 2015; 95:405–511.
32. Schiller A, Covic A. Kidney and brain--a renal perspective of ‘Les Liaisons Dangereuses’. Nephrol Dial Transplant 2010; 25:1370–1373.
33. Sedaghat S, Vernooij MW, Loehrer E, Mattace-Raso FU, Hofman A, van der Lugt A, et al. Kidney function and cerebral blood flow: the Rotterdam Study. J Am Soc Nephrol 2016; 27:715–721.
34. Ghoshal S, Freedman BI. Mechanisms of stroke in patients with chronic kidney disease. Am J Nephrol 2019; 50:229–239.
35. Webb AJ, Rothwell PM. Blood pressure variability and risk of new-onset atrial fibrillation: a systematic review of randomized trials of antihypertensive drugs. Stroke 2010; 41:2091–2093.
36. Kario K. Blood pressure variability in hypertension: a possible cardiovascular risk factor. Am J Hypertens 2004; 17:1075–1076.
37. Mancia G, Parati G, Hennig M, Flatau B, Omboni S, Glavina F, et al. Relation between blood pressure variability and carotid artery damage in hypertension: baseline data from the European Lacidipine Study on Atherosclerosis (ELSA). J Hypertens 2001; 19:1981–1989.
38. Ikeda Y, Handa M, Kawano K, Kamata T, Murata M, Araki Y, et al. The role of von Willebrand factor and fibrinogen in platelet aggregation under varying shear stress. J Clin Invest 1991; 87:1234–1240.
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