Blood Pressure Variability and Cardiovascular Outcomes in Patients with Prior Stroke: a Secondary Analysis of PRoFESS

Abstract

Background and Purpose

Every year in the United States almost 185,000 ischemic strokes occur in patients with a prior stroke. Recurrent stroke has significantly higher morbidity and mortality. Among modifiable risk factors for recurrent stroke, hypertension is the most prevalent. Reducing systolic blood pressure (SBP) is standard of care for secondary stroke prevention. Recent literature suggests that increased blood pressure variability (BPV) is associated with primary stroke, although studies have not convincingly shown that it is associated with recurrent stroke, which was the goal of this analysis.

Methods

We conducted a secondary analysis of 17,916 patients in the Prevention Regimen for Effectively Avoiding Second Strokes (PRoFESS) trial, which is the largest trial of patients with potential recurrent stroke. We calculated BPV and evaluated its effect on recurrent stroke (composite and stratified by ischemic or hemorrhagic stroke), major cardiovascular events (death from cardiovascular causes, recurrent stroke, myocardial infarction, or new or worsening heart failure), and all-cause death.

Results

Both systolic and diastolic BPV were associated with recurrent stroke, major cardiovascular events, and all-cause death. The association with stroke was significant for ischemic, but not hemorrhagic, stroke. For every 10-point increase in BPV (systolic standard deviation, range = 0 – 54.2), the hazard ratio for a recurrent ischemic stroke was 1.15 (95% CI, 1.02–1.32, p=0.02), for major cardiovascular events was 1.19 (95% CI, 1.09–1.31, p<0.001), and for all-cause death was 1.24 (95% CI, 1.10–1.39, p<0.001).

Discussion

Our study adds to the growing body of literature suggesting that BPV is an important and potentially modifiable risk factor for ischemic stroke, cardiovascular events, and all-cause death. Specifically, it is the first study to demonstrate that increased BPV is associated with recurrent ischemic stroke and that diastolic BPV can be as important as systolic BPV. Future work should focus on evaluating whether actively reducing BPV, using widely available and inexpensive anti-hypertensive medications, reduces the risk of cardiovascular disease.

Introduction

Every year almost 185,000 ischemic strokes in the United States occur in patients with a history of prior stroke.¹ Recurrent strokes cause substantially higher morbidity and mortality than first-time strokes.^2–5 Hypertension is the most prevalent modifiable risk factor after stroke and blood pressure reduction is an important goal for stroke risk reduction.^6,7 Recent studies have suggested that increased blood pressure variability (BPV) may be as important as hypertension for risk of stroke, cardiovascular disease, renal failure, and mortality.⁸ The detrimental effect of increased BPV is largely independent of mean blood pressure, suggesting that it is a unique, and underappreciated, stroke risk factor.⁹

Although several studies have shown that higher outpatient visit-to-visit BPV is associated with an increased risk of incident stroke, none have focused specifically on patients with a prior history of symptomatic stroke.^10–12 Rothwell et al. demonstrated an association between visit-to-visit BPV and stroke risk in patients with prior transient ischemic attack, but their cohort had a relatively small number of stroke events with a variable number of blood pressure readings.¹¹ To more definitely evaluate this association, we analyzed data from the largest clinical trial of secondary stroke prevention: Prevention Regimen for Effectively Avoiding Second Strokes (PRoFESS).¹³ PRoFESS presents a unique opportunity to better understand BPV as a potentially modifiable risk factor for major adverse events after a first-time stroke. We hypothesized that patients with increased BPV would have a higher risk of recurrent stroke, as well as major cardiovascular events and all-cause death.

Methods

Cohort

This is a secondary analysis of the PRoFESS trial. Because of the sensitive nature of the data collected for this study, requests to access the dataset from qualified researchers trained in human subject confidentiality protocols may be sent to CSDR at clinicalstudydatarequest.com. PRoFESS included 20,033 adult patients ≥55 years old with an ischemic stroke within the past 90 days or patients aged 50–54 years and/or 90–120 days from stroke onset with at least two of the following risk factors: diabetes, hypertension, current smoker, obesity (body mass index >30), previous vascular disease (stroke, myocardial infarction, or peripheral arterial disease), end organ damage (retinopathy, left ventricular hypertrophy or microalbuminuria), or hyperlipidemia.^14,15 Exclusion criteria included hemorrhagic stroke at entry, recent coronary artery disease, recent major surgery, severe hepatic or renal insufficiency and uncontrolled hyper/hypotension. PRoFESS had a 2 × 2 factorial design with the following study drug combinations: aspirin/dipyridamole + placebo, aspirin/dipyridamole + telmisartan, clopidogrel + placebo, and clopidogrel + telmisartan. We obtained PRoFESS data from ClinicalStudyDataRequest.com, a consortium of anonymized clinical study data provided by a study sponsor, which is Boehringer Ingelheim GmbH for PRoFESS. Because the data was completely de-identified, local IRB approval was not required.

Inclusion, Exposure, and Outcomes

The study exposure period was BPV during the first year of PRoFESS. We included patients with ≥3 blood pressure readings (range 3–5, mean 4.9 readings). Blood pressure was measured in PRoFESS using protocol-based methodology and a validated semiautomatic monitor (Omron 705CP).¹⁶ The primary outcome was recurrent stroke, measured from after the exposure period to study termination, which we defined as the “follow-up period.” The secondary outcomes included: ischemic stroke, hemorrhagic stroke, major cardiovascular events (recurrent stroke, myocardial infarction, new or worsening heart failure, or cardiovascular death), and all-cause death. Subjects with primary or secondary outcome events prior to 1 year after randomization were excluded because the events occurred during the exposure period.

Statistical Analysis

BPV was calculated for systolic and diastolic blood pressure (SBP, DBP) using five statistical methodologies: standard deviation (SD), residual standard deviation (rSD), average real variability (ARV), successive variation (SV), and variation independent of mean (VIM) using blood pressure readings in the first year of PRoFESS. BPV calculation are: SD = $\sqrt{(\frac{1}{n–1}){\sum }_{(i=1)}^{\left(n\right)}{({BP}_i–{BP}_{mean})}^2}$; rSD = $\sqrt{\frac{{\sum (BP-BPest)}^2}{n-2}}$; ARV = $\left(\frac{1}{n–1}\right){\sum }_{\left(i=1\right)}^{\left(n-1\right)}\left|{BP}_{i+1}–{BP}_i\right|$; SV = $\sqrt{(1/(n–1)){\sum }_{(i=1)}^{(n-1)}{({BP}_{i+1}–{BP}_i)}^2)}$; and VIM = (BP_mean * SD/${\overline{x}}^p$). We selected these methodologies to account for the distribution and linear trends of blood pressure, and in an effort to reduce the impact of blood pressure mean on BPV.^17,18 Consistent with the recommendations of a recent meta-analysis, we represented BPV as a 10 point shift.¹⁹

Subject characteristics at randomization were summarized by treatment arm, to allow comparison to the original PRoFESS cohort, using chi-squared tests or ANOVA as appropriate. Cox regression models were constructed to determine if BPV was associated with recurrent stroke, major cardiovascular events, or all-cause death. The proportional hazards assumption was not met for treatment arm, so models were stratified by treatment arm to subsume the interaction of treatment arm with time. This method assumes that observations are conditionally independent within treatment arms, and the coefficients of the covariates are the same across treatment arms. All-cause death was treated as a competing event for all primary outcomes. Separate regression models were performed for each BPV measure, and models were adjusted for baseline age, sex, race, smoking, diabetes status, and Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification of the qualifying stroke.²⁰ Systolic variability models were also adjusted for baseline systolic blood pressure and diastolic variability models were adjusted for baseline diastolic blood pressure.

To explore if the association with BPV and our outcomes changed over the follow-up period, we conducted a sensitivity analysis that included a BPV*time-to-event interaction term. We conducted a second sensitivity analysis where we adjusted for mean blood pressure during the exposure period, although it should be noted that many of the statistical methods we used to calculate BPV also inherently adjust for mean blood pressure. All analysis was performed in SAS and we defined an α value of less than 0.05 as showing statistical significance.

Results

We included 17,896 of the 20,332 patients randomized in PRoFESS. Patients were censored for: 1,709 for having events during the exposure period, of which 913 were stroke, and 727 for having too few blood pressure readings. After the exposure period, there was a mean follow-up of 1.57±0.67 years. During the follow-up period, the primary outcome of recurrent stroke was met by 745/17,896 (4.2%), of which 639 were ischemic, 62 were hemorrhagic, and 44 were undetermined or both. The secondary outcome of major cardiovascular events was met by 1,303/17,896 (7.3%) and all-cause death by 756/17,896 (4.2%), of which 425 were due to vascular causes.

The baseline characteristics, seen in Supplementary Table I, were not different in the four PRoFESS treatment arms. During the exposure period of PRoFESS’s first year, the mean±SD number of blood pressure readings was 4.9±0.4, mean systolic blood pressure was 139.13±14.0 mm Hg, and diastolic blood pressure was 81.4±8.33 mm Hg. When considering all four treatment arms, the BPV measures differed by treatment arm (Table 1). Specifically, patients randomized to telmisartan had higher BPV, with a SBP SD of 13.0±6.1 versus 12.3±5.9 mm Hg for patients randomized to placebo (p<0.001). After adjusting for mean systolic blood pressure, the difference in SBP SD remained significantly higher for patients randomized to telmisartan versus placebo, 13.3 mm Hg (95 % CI, 13.1–13.4) versus 12.1 mm Hg (95% CI, 11.9–12.2) (p<0.001).

Table 1.

Blood pressure variability by treatment arm.

Variable	Aspirin/Dipyridamole + Placebo (n=4,440)		Clopidogrel + Placebo (n=4,508)		Aspirin/Dipyridamole + Telmisartan (n=4,464)		Clopidogrel + Telmisartan (n=4,484)		P Value
	mean	SD	mean	SD	mean	SD	mean	SD
Systolic
Standard Deviation (SD) (range 0 – 54.2)	12.26	5.82	12.25	5.94	12.99	6.00	13.09	6.11	<.0001
Average real variability (ARV) (range 0–83.0)	13.66	7.42	13.70	7.67	14.51	7.72	14.63	7.76	<.0001
Successive variation (SV) (range 0–83.5)	16.10	8.34	16.15	8.65	17.08	8.68	17.21	8.78	<.0001
Residual Standard Deviation (RSD) (range 0–61.6)	11.34	6.22	11.37	6.38	12.04	6.39	12.16	6.52	<.0001
Variation independent of mean (VIM) (range 0–49.6)	12.22	5.70	12.16	5.80	13.05	5.96	13.12	6.05	<.0001
Diastolic
Standard Deviation (SD) (range 0–37.8)	7.45	3.48	7.36	3.36	7.82	3.48	7.72	3.54	<.0001
Average real variability (ARV) (range 0–60.0)	8.37	4.51	8.23	4.32	8.76	4.52	8.67	4.61	<.0001
Successive variation (SV) (range 0–75.0)	9.75	5.56	9.56	5.44	10.44	5.71	10.23	5.84	<.0001
Residual Standard Deviation (RSD) (range 0–61.6)	6.93	3.74	6.85	3.63	7.30	3.71	7.21	3.85	<.0001
Variation independent of mean (VIM) (range 0–36.4)	7.44	3.46	7.33	3.32	7.86	3.49	7.74	3.53	<.0001

For every 10-point increase in SBP SD, which had a range of 0 – 54.2, the hazard ratio for a recurrent stroke was 1.15 (95% CI, 1.02–1.30, p=0.02). The same association was seen for 5/5 measures of SBP BPV and 2/5 DBP BPV measures (Table 2). When the recurrent stroke outcome was separated out to the subtypes of recurrent ischemic stroke or incident hemorrhagic stroke, only recurrent ischemic stroke remained associated with BPV. This association was stronger than the composite recurrent stroke outcome (Table 2). For example, the hazard ratio for a 10 point increase in SBP SD for recurrent ischemic stroke was 1.18 (95% CI, 1.04–1.35, p=0.01). After dividing SBP rSD into tertiles, a Kaplan-Meier curve fit to the outcome of recurrent ischemic stroke illustrates the increasing risk with higher BPV (p=0.005) (Figure 1).

Table 2.

BPV’s association with the primary outcome of recurrent stroke and its subtypes.

	Recurrent stroke, total (n events=745)		Recurrent stroke, Ischemic stroke subtype (n events=647)		Recurrent stroke, Hemorrhagic stroke subtype (n events=70)
BPV Variable, per 10 unit change	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value
Systolic
Standard deviation (SD) (range 0–54.2)	1.15 (1.02, 1.30)	0.02	1.18 (1.04, 1.35)	0.01	0.95 (0.62, 1.46)	0.81
Average real variability (ARV) (range 0–83.0)	1.10 (1.01, 1.21)	0.04	1.14 (1.03, 1.26)	<.01	0.91 (0.65, 1.27)	0.58
Successive variation (SV) (range 0–83.5)	1.11 (1.02, 1.20)	0.01	1.13 (1.04, 1.24)	0.005	0.95 (0.71, 1.27)	0.73
Residual Standard Deviation (RSD) (range 0–61.6)	1.18 (1.05, 1.31)	0.004	1.21 (1.07, 1.36)	0.002	0.93 (0.63, 1.38)	0.72
Variation independent of mean (VIM) (range 0–49.6)	1.14 (1.01, 1.30)	0.04	1.17 (1.03, 1.34)	0.02	0.93 (0.61, 1.44)	0.76
Diastolic
Standard Deviation (SD) (range 0–37.8)	1.22 (1.05, 1.42)	0.01	1.27 (1.08, 1.49)	0.004	1.01 (0.59, 1.73)	0.98
Average real variability (ARV) (range 0–60.0)	1.11 (0.98, 1.26)	0.09	1.16 (1.02, 1.32)	0.03	0.87 (0.55, 1.36)	0.54
Successive variation (SV) (range 0–75.0)	1.27 (1.05, 1.53)	0.01	1.32 (1.08, 1.61)	0.006	0.92 (0.48, 1.80)	0.82
Residual Standard Deviation (RSD) (range 0–42.7)	1.20 (0.97, 1.47)	0.09	1.26 (1.01, 1.57)	0.04	0.76 (0.36, 1.58)	0.46
Variation independent of mean (VIM) (range 0–36.4)	1.22 (0.99, 1.49)	0.06	1.28 (1.02, 1.59)	0.03	0.80 (0.38, 1.66)	0.54

^*All primary models control for competing risk of all-cause mortality. Coefficients represent a 10 point change in blood pressure variability. Models are adjusted for patient baseline characteristics of age, sex, race, smoking, TOAST classification of index stroke, and diabetes. Systolic variability models were also adjusted for baseline systolic blood pressure diastolic variability models were adjusted for baseline diastolic blood pressure.

Figure 1.

Days to recurrent ischemic stroke by survival function estimates for tertiles of systolic rSD. The y axis (survival function estimates) ranges from 0.92 to 1.0. The difference in the risk of recurrent stroke was significantly different in the tertiles (p=0.005).

We also found that BPV was a significant predictor of major cardiovascular events and all-cause death (Table 3). For major cardiovascular events, the hazard ratio for each 10 point increase in DBP SD (range 0 – 37.8) was 1.31 (95% CI, 1.12–1.53, p<0.001). For all-cause death, the sensitivity analysis did not show that the impact of BPV on our outcomes changed over time. These models included an interaction term of BPV*time-to-event and were not significant, apart from SBP BPV and all-cause death (Table 4). In the second sensitivity analysis, where we adjusted for corresponding mean blood pressure, the conclusions of our analysis persisted (Supplementary Tables II–III).

Table 3.

Blood pressure variability’s association with the secondary outcome of major cardiovascular events, all-cause death, or both.

	Major cardiovascular events (n events=1,303)		All-cause death (n events =756)		Major cardiovascular events or all-cause death (n events =1,600)
BPV Variable, per 10 unit change	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value
Systolic
Standard Deviation (SD) (range 0 – 54.2)	1.19 (1.09, 1.31)	<.001	1.24 (1.10, 1.39)	<.001	1.19 (1.09, 1.30)	<.001
Average real variability (ARV) (range 0–83.0)	1.14 (1.07, 1.22)	<.001	1.14 (1.05, 1.25)	0.003	1.15 (1.07, 1.23)	<.001
Successive variation (SV) (range 0–83.5)	1.14 (1.07, 1.21)	<.001	1.14 (1.05, 1.23)	0.001	1.14 (1.07, 1.21)	<.001
Residual Standard Deviation (RSD) (range 0–61.6)	1.20 (1.10, 1.30)	<.001	1.17 (1.05, 1.30)	0.005	1.20 (1.10, 1.30)	<.001
Variation independent of mean (VIM) (range 0–49.6)	1.18 (1.08, 1.30)	<.001	1.24 (1.10, 1.40)	<.001	1.19 (1.08, 1.30)	<.001
Diastolic
Standard Deviation (SD) (range 0–37.8)	1.32 (1.13, 1.54)	<.001	1.43 (1.17, 1.74)	<.001	1.31 (1.12, 1.53)	<.001
Average real variability (ARV) (range 0–60.0)	1.27 (1.13, 1.42)	<.001	1.19 (1.02, 1.39)	0.03	1.27 (1.13, 1.42)	<.001
Successive variation (SV) (range 0–75.0)	1.16 (1.06, 1.27)	0.002	1.12 (0.99, 1.27)	0.08	1.16 (1.06, 1.27)	0.002
Residual Standard Deviation (RSD) (range 0–61.6)	1.30 (1.13, 1.49)	<.001	1.24 (1.02, 1.49)	0.03	1.30 (1.13, 1.49)	<.001
Variation independent of mean (VIM) (range 0–36.4)	1.30 (1.12, 1.52)	<.001	1.43 (1.17, 1.75)	<.001	1.30 (1.11, 1.52)	<.001

^*Coefficients represent a 10 point change in blood pressure variability. Models are adjusted for baseline patient characteristics of age, sex, race, smoking, TOAST classification of index stroke, and diabetes. Systolic variability models were also adjusted for baseline systolic blood pressure and diastolic variability models were adjusted for baseline diastolic blood pressure.

Table 4.

BPV’s association with our primary and secondary outcomes over time. The presented Hazard ratios (HR) are for the interaction of the BPV variable and time. If the HR< 1 and p value is significant, the effect of BPV decreases over time. If the HR> 1 and p value is significant, the effect of BPV increases over time.

	Recurrent Stroke		Recurrent ischemic stroke		Major cardiovascular events		All-cause death
BPV Variable*Time, per 10 unit change	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value
Systolic
Standard Deviation (SD)	1.06 (0.89, 1.26)	0.55	1.03 (0.85, 1.25)	0.74	1.10 (0.96, 1.25)	0.16	1.23 (1.04, 1.45)	0.01
Average real variability (ARV)	1.00 (0.87, 1.15)	0.99	0.98 (0.84, 1.13)	0.76	1.06 (0.96, 1.17)	0.28	1.17 (1.03, 1.33)	0.02
Successive variation (SV)	1.02 (0.90, 1.15)	0.76	1.00 (0.88, 1.14)	0.96	1.06 (0.97, 1.16)	0.22	1.15 (1.02, 1.28)	0.02
Residual Standard Deviation (RSD)	1.00 (1.00, 1.00)	0.91	0.98 (0.83, 1.17)	0.84	1.06 (0.94, 1.19)	0.36	1.22 (1.05, 1.42)	0.01
Variation independent of mean (VIM)	1.00 (1.00, 1.00)	0.56	1.03 (0.85, 1.25)	0.75	1.10 (0.96, 1.26)	0.16	1.23 (1.04, 1.46)	0.02
Diastolic
Standard Deviation (SD)	0.99 (0.73, 1.36)	0.97	0.98 (0.70, 1.37)	0.92	0.95 (0.75, 1.21)	0.68	0.96 (0.71, 1.30)	0.79
Average real variability (ARV)	0.94 (0.74, 1.19)	0.63	0.95 (0.74, 1.22)	0.7	0.99 (0.83, 1.18)	0.9	0.96 (0.76, 1.22)	0.75
Successive variation (SV)	1.01 (0.84, 1.22)	0.9	0.99 (0.81, 1.21)	0.95	1.02 (0.89, 1.18)	0.75	0.97 (0.80, 1.17)	0.76
Residual Standard Deviation (RSD)	0.98 (0.74, 1.31)	0.9	0.97 (0.71, 1.31)	0.82	1.01 (0.81, 1.26)	0.92	0.98 (0.74, 1.31)	0.9
Variation independent of mean (VIM)	0.99 (0.72, 1.36)	0.96	0.98 (0.70, 1.38)	0.92	0.95 (0.75, 1.20)	0.68	0.96 (0.71, 1.30)	0.8

^**All outcomes (except all-cause death) control for competing risk of all-cause death. Coefficients are scaled to represent a 10-point change in blood pressure variability and a year increase in time. Models are adjusted for age, sex, race, smoking, TOAST classification of index stroke, and diabetes.

Discussion

In a large cohort of patients with recent ischemic stroke, we found that higher BPV was associated with an increased risk of recurrent ischemic stroke, major cardiovascular events, and all-cause death. This association was not changed by the time to event, suggesting the risk remained elevated throughout the follow-up period. Contrary to prior studies,²¹ we show that diastolic BPV, in addition to systolic BPV, is associated with recurrent ischemic stroke. We did not find that BPV influenced the risk of incident hemorrhagic stroke. Our analysis of the ATACH-2 trial data,²² as well as studies that analyzed the FAST-MAG and INTERACT2 trial data, have shown that increased systolic BPV in the days following hemorrhagic stroke is associated with worse functional outcome.^23,24 However, the small number of hemorrhagic strokes may have limited the power to detect an association between BPV and hemorrhagic stroke in this cohort.

Rothwell et al.’s study of BPV in patients with prior TIA found markedly higher hazard ratios for ischemic stroke,¹¹ ranging from 3–4, but drew from a smaller data set than ours and, as such, had wider confidence intervals. Our hazard ratios for ischemic stroke are similar to those in Muntner et al.’s analysis of BPV in the ALLHAT trial, but less than 15% of that cohort had a history of stroke,¹⁰ making it difficult to draw conclusions about recurrent ischemic stroke. This study adds to the growing body of literature demonstrating that negative cerebrovascular and cardiovascular outcomes are closely related to increased BPV, independent of mean blood pressure.^10–12 We also found that telmisartan was associated with increased BPV when compared with placebo. This is consistent with Webb et al.’s meta-analysis that demonstrated angiotensin receptor blockers, as well as ACE-inhibitors and beta-blockers, increase BPV compared to calcium-channel blockers such as amlodipine.²⁵ However, we did not find that an interaction term between treatment arm and the study outcomes was significant for our outcomes (all p>0.05), suggesting that the mild increase in BPV seen in patients receiving telmisartan may not impact the risk of recurrent ischemic stroke, major cardiovascular events, and all-cause death.

Our analysis has notable strengths including the largest population yet studied of patients with a prior history of stroke, high-quality data from a landmark randomized controlled trial, and a substantial period of patient follow-up with relatively high event rates. The limitations of our study include that the number of blood pressure readings from the first year (mean of 4.9) was not standardized, is on the lower end of what prior studies have used to calculate BPV, and the time intervals between measurements varied. This may have resulted in less precise estimations of BPV. Additionally, we excluded patients who experienced events in the first year of the study, which may have biased our analysis by removing the patients with highest recurrence risk. However, this was necessary to create an exposure period for BPV measurement. PRoFESS only enrolled 369 patients with atrial fibrillation (1.8% of the cohort). As a result of this underrepresentation, the findings of our analysis do not apply to patients with cardioembolic stroke.

Most importantly, because PRoFESS was not designed to answer our hypothesis, it is impossible to know if higher BPV is causal of stroke, cardiovascular events, and death; or is merely an epiphenomenon. While the mechanism by which BPV may exert a negative influence on neurologic or cardiovascular outcomes remains unknown, the negative effects of increased BPV have been previously reported in divergent vascular beds such as the brain and heart, but also the eye and kidney.^8,26–29 The brain and other vascular beds use significant resources to maintain dynamic autoregulation and a relatively constant blood flow across a wide range of blood pressures.³⁰ In disease states, the ability to autoregulate blood flow can be impaired, which may predispose patients with prior stroke, such as those in our cohort, to be susceptible to the fluctuations in flow generated by increased variability of blood pressure.^31,32 Despite not knowing the causal mechanism, the independent association of high BPV with poor outcomes is compelling and this analysis provides evidence that the association is seen in the vulnerable population of patients with a history of prior stroke.

Conclusion

In a large cohort of patients with prior ischemic stroke, elevation of both diastolic and systolic BPV are associated with recurrent ischemic stroke, major cardiovascular events, and all-cause death. Prospective research of BPV in patients at high risk of cardiovascular disease is needed to provide definitive evidence of a causal relationship. To date, there have been no randomized controlled trials that have attempted to therapeutically reduce BPV.³³ Several common antihypertensive medications, including calcium channel blockers such as amlodipine and thiazide diuretics such as clorthalidone, have been shown to reduce BPV, which could also be treated by protocol-based medication titration.²⁵ The reduction of BPV could be combined with blood pressure reduction to achieve synergistic risk reduction. Reducing BPV would be an inexpensive and widely available intervention, which could be administered in a range of healthcare settings to reduce cardiovascular morbidity and mortality.

Acronyms

BPV

blood pressure variability

SD

standard deviation

rSD

residual standard deviation

ARV

average real variability

SV

successive variation

VIM

variation independent of mean