High daytime and nighttime ambulatory pulse pressure predict poor cognitive function and mild cognitive impairment in hypertensive individuals

Abstract

High blood pressure accelerates normal aging stiffness process. Arterial stiffness (AS) has been previously associated with impaired cognitive function and dementia. Our aims are to study how cognitive function and status (mild cognitive impairment, MCI and normal cognitive aging, NCA) relate to AS in a community-based population of hypertensive participants assessed with office and 24-hour ambulatory blood pressure measurements. Six hundred ninety-nine participants were studied, 71 had MCI and the rest had NCA. Office pulse pressure (PP), carotid–femoral pulse wave velocity, and 24-hour ambulatory PP monitoring were collected. Also, participants underwent a brain magnetic resonance to study cerebral small–vessel disease (cSVD) lesions. Multivariate analysis–related cognitive function and cognitive status to AS measurements after adjusting for demographic, vascular risk factors, and cSVD. Carotid–femoral pulse wave velocity and PP at different periods were inversely correlated with several cognitive domains, but only awake PP measurements were associated with attention after correcting for confounders (beta = −0.22, 95% confidence interval (CI) −0.41, −0.03). All ambulatory PP measurements were related to MCI, which was independently associated with nocturnal PP (odds ratio (OR) = 2.552, 95% CI 1.137, 5.728) and also related to the presence of deep white matter hyperintensities (OR = 1.903, 1.096, 3.306). Therefore, higher day and night ambulatory PP measurements are associated with poor cognitive outcomes.

Keywords

Ambulatory blood pressure monitoring arterial stiffness cerebral small–vessel disease cognitive function mild cognitive impairment

Introduction

Aging and hypertension, among other vascular risk factors (VRFs), determine the risk of cardiovascular diseases and contribute to structural and functional changes in the arterial wall, which becomes less elastic and stiffer.¹

Arterial stiffness (AS) is a surrogate marker of major cardiovascular events in the general population² and in clinical settings (like stroke in hypertensive patients).³ Besides AS was associated with some features of cerebral small-vessel disease (cSVD) such as white matter changes and lacunar infarcts.^4,5

Moreover, AS was independently associated with cognitive function, in demented and nondemented individuals, and with cognitive decline and dementia in most⁶ but not all studies.^7,8 A relationship has also been suggested between AS and mild cognitive impairment (MCI).⁹ Studying MCI predictors is a priority because it is the main risk factor for conversion to dementia.¹⁰ However, some important limitations of these studies on AS in cognitive function, dementia, and especially MCI have to be acknowledged: most had small sample sizes, some used only screening tests for cognitive assessment, and most did not adjust AS by the presence of VRFs or cSVD.¹¹

Among the different indirect ways to assess AS, carotid–femoral pulse wave velocity (cf-PWV) is considered the reference standard. However, there are a number of external factors (i.e., white-coat hypertension phenomena, tobacco, alcohol, polyphenol consumption, etc.) that might affect these estimations, decreasing its predictive accuracy, particularly in routine clinical care.¹² Other indirect ways to estimate AS as calculating the pulse pressure (PP) can be achieved by techniques such as 24-hour ambulatory blood pressure monitoring (ABPM), which may provide relative advantages over a single evaluation at the clinic.

Our objectives are to describe how cognitive function and cognitive status (MCI and normal cognitive aging (NCA)) relate to AS in a community-based population of hypertensive patients. Specifically, we aimed to compare whether AS measured with different methodologies (cf-PWV versus office PP assessment; 24-hours daytime or nighttime PP assessment) relate differentially to these cognitive outcomes, and to study whether the effect of AS on cognitive function/status varies in the presence of cSVD.

Materials and methods

Study Population

Our study population is nested within the ISSYS project (Investigating Silent Strokes in hypersensitive individuals, a magnetic resonance imaging Study). This is an observational, prospective study in 1,037 hypertensive individuals in Spain. Inclusion criteria of the study were essential hypertension diagnosed at least 1 year before inclusion, age 50 to 70 years old, and no history of clinical stroke or dementia. Individuals who had contraindications for magnetic resonance imaging (MRI; i.e., carried a pacemaker or were claustrophobic) or those who had a terminal illness were excluded. ISSYS general aims are to investigate the prevalence of silent cerebrovascular lesions and cognitive impairment. The participants were selected at random from 14 primary care centers in the North area of Barcelona city. Our study protocol was published elsewhere.¹³

The study followed the Declaration of Helsinki and was approved by the Vall d’Hebron’s Research Hospital Ethics Committee, and all patients gave their informed written consent before inclusion.

Cognitive Assessment

At baseline all participants were evaluated by means of a dementia screening test (Dementia Rating Scale second version, DRS-2).¹⁴ Total DRS-2 score goes from 0 to 144 points and is divided in several subscales (memory, attention, initiation/perseveration, conceptualization, and construction).

Seven hundred ninety-eight participants of the ISSYS had valid data on DRS-2, they were literate and did not have any condition that could interfere with their cognitive performance (e.g., severe sensory deficit, previous central nervous system disorder, uncontrolled metabolic diseases, or alcohol consumption) or dementia. All of them belonged to the same ethnic group (white Mediterranean).

In a further step, all participants who obtained age- and education-adjusted scores below 8 points (considered as a cutoff to suspect cognitive impairment) were reevaluated to assess cognitive status.¹⁴ In this second evaluation an extended cognitive, behavioral, and functional anamnesis and a standard physical and neurologic examination was performed. Besides, cognitive performance was determined using a battery of cognitive tests evaluating memory, attention, processing speed, executive function, motor, and visuospatial functions. Our cognitive protocol was published previously elsewhere.¹⁵ The diagnosis of MCI was established following previously published criteria by the neurologist and neuropsychologist who attended the patients, who were masked to other clinical data.¹⁶ In brief, MCI was considered when the subject or caregiver manifest an acquired cognitive impairment that lasted months to years and this alteration was shown on cognitive testing (performance mainly below 1.5 s.d. of the adjusted mean). The impairment did not (or minimally) interfere with daily instrumental activities. Those with delirium or altered consciousness at the time of diagnosis were excluded. Participants with a previous depression were considered for the present analysis if it was under treatment and controlled. Sixteen participants refused to be further evaluated.

All those with normal results in the screening tool (total DRS-2 > 8) or who did not fulfill criteria for cognitive impairment or MCI were considered as having NCA.

Brain Magnetic Resonance Imaging

All participants underwent a brain MRI with the same 1.5 Tesla MR.¹³ Magnetic resonance imaging examinations were rated by two neuroradiologists and a stroke neurologist who were also masked to clinical data. Presence and number of lacunar brain infarcts were assessed. Lacunar infarcts were considered when there was a lesion of tissue loss of 3- to 20-mm diameter in their widest dimension, with cerebrospinal fluid–like signal characteristics in all pulse sequences, and with the presence of a hyperintense rim surrounding it in fluid-attenuated inversion recovery sequences. Localization of lacunar infarcts was the basal ganglia, thalamus, internal or external capsules, or brainstem. Cortical infarcts were not considered for the analysis.

Presence and grade of white matter hyperintensities (WMHs) in fluid-attenuated inversion recovery or T2-weighted images were rated with a semiquantitative scale.¹⁷ White matter hyperintensities in periventricular and deep localizations were considered separately. For periventricular WMHs, the score was as follows: grade 0 = no WMHs, 1 = caps or pencil-thin lining, 2 = smooth ‘halo’, and 3 = irregular WMHs extending to the deep white matter. For deep WMHs, the score was 0 = no lesions, 1 = punctuate foci, 2 = beginning confluence of foci, and 3 = large confluent areas. Intrarater and interrater agreement for all the markers was good to excellent (k = 0.6 to 0.81).

Participants with either lacunar infarct(s) or WMHs⩾2 on Fazekas deep score or with both lesions were considered as having cSVD, otherwise were considered as not having cSVD.

Those participants who had incomplete, invalid, or no data from MRI (n = 52) were excluded for this analysis.

Office Arterial Stiffness Measurements

Office PP was calculated as the difference between mean systolic BP (SBP) and mean diastolic BP. Office BP was measured with a validated oscillometric OMRON (M6 CONFORT, Hoofddorp, The Netherlands) device after 5-minute rest.¹⁸ Systolic BP and diastolic BP were calculated as the mean of the last two out of three measurements.

Carotid–femoral pulse wave velocity was assessed in supine position after 10-minute rest using the oscillometric automatic VICORDER (SMT Medical, Würzburg, Germany) device.¹⁹ To obtain the measurement, two inflatable cuffs were placed, one smaller over the right carotid region to measure carotid pulse wave and one larger around the right upper thigh to measure the femoral pulse wave. Both cuffs were inflated to 60 mmHg and at least 10 consecutive carotid and femoral beats were recorded simultaneously. The distance between external notch and the center of the femoral cuff was measured with a tape over the body surface and used as the path distance. The transit time between the two cuffs was computed and cf-PWV calculated as the ratio between distance and transit time in meters per second (m/s) with an in-built cross-correlation algorithm. Participants with rhythm disorders were excluded to avoid interference with AS measurements (n = 65).

Twenty-Four-Hours Ambulatory Blood Pressure Monitoring

Twenty-four-hours–ABPM recordings were performed at working days with the automated Spacelabs 90217-5Q (Spacelabs Healthcare, Issaquah, WA, USA) device, validated according to the protocol of the British Hypertension Society.²⁰ Participants were asked to fill a questionnaire regarding sleeping and awaking periods and to follow their usual activities, although avoiding intense physical exercise and excessive movement on their nondominant arm during measurements. Readings were performed every 20 minutes during daytime (0600 to 2259 hours) and every 30 minutes during nighttime (2300 to 0559 hours).

Twenty-four-hours–ABPM data were not considered in those with<70% valid measurements, <2 measurements per hour during daytime, and <1 during the sleeping period or in those participants who refused to be tested.

Flowchart of the study taking into account cognitive diagnosis, brain MRI, and valid AS measurements is presented in Figure 1.

Figure 1.

Study flowchart. ABPM, ambulatory blood pressure monitoring; cf-PWV, carotid–femoral pulse wave velocity; DRS-2, Dementia Rating Scale second version; MCI, mild cognitive impairment; MRI, magnetic resonance imaging; NCA, normal cognitive aging; PP, pulse pressure.

Definition of Covariates

Education was calculated as the maximum years of formal education accomplished from childhood to early adulthood. Baseline total cholesterol was measured on an automated clinical chemistry analyzer (Olympus AU2700, Diamond Diagnostics, Holliston, MA, USA). Diabetes mellitus was defined by clinical records, history of diabetes, or being under oral glucose–lowering drugs or insulin. Smoking habit was defined as active or inactive. Blood pressure–lowering drug (BPLD) compliance was evaluated by means of Morisky-Green scale.¹³ The use of several common BPLDs was considered for this study: dihydropyridine calcium–channel blockers, thiazides, β-blockers, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and also statin and antiplatelet use.

Statistical Analysis

For cognitive function analysis, DRS-2 total and subscale scores were transformed into Z scores (individual mean − sample mean/s.d.) to obtain distributions centered in 0 (s.d. = 1). Initiation/perseveration and conceptualization subscales were averaged to obtain an executive function score.

In univariate analysis, we related demographics, VRFs, AS measurements, and cSVD with both cognitive function (total, attention, executive function, and memory scores) and cognitive status (MCI and NCA). Categorical variables were compared using Pearson's χ², whereas T-test or Mann–Whitney U-tests were used for continuous variables depending on their distribution. Correlations with cognitive function scores were assessed by means of Spearman's test.

To determine whether AS measurements in the office or obtained during the ABPM recordings were independently associated with cognitive function and cognitive status, multivariate models were performed.

Each model tested the effect of a different office (PP or cf-PWV) or ABPM-related (24 hours, day or night PP) AS measurement with cognitive outcome and was adjusted by age, sex, education, diabetes, total cholesterol, smoking, heart rate, BPLDs, statins, antiplatelet treatment (when appropriate), SBP of the period being analyzed (model 1), and additionally by number of lacunar infarcts and deep WMHs (model 2). The selection of these covariates as confounders was based either in the results of our analysis or in the previous literature concerning cognitive function and cognitive status. Heart rate was included since it influences AS measurements. Interactions between PP and cSVD lesions were tested but none was significant.

In the case of cognitive function linear regression models were used and results are given as beta and 95% confidence interval (CI). For cognitive status, logistic regression models were performed and results were given as odds ratio (OR), CI of 95%. Statistical significance was set at P-values < 0.05. All analyses were performed using SPSS version 17.0. (SPSS Inc., Chicago, IL, USA)

Results

Baseline Characteristics

The mean age of the sample was 62.8 years and 50.1% were women. Almost all participants (95%) received BPLDs and were long-standing hypersensitive individuals (median time since diagnosis was 8 years). Few participants had moderate to severe periventricular (4.6%) and deep (8.6%) WMHs and 7.5% had lacunar infarcts.

Regarding AS measurements, cf-PWV was 10.6 (±2.2) m/s. Office, 24-hour, daytime, and nighttime PP values are shown in Table 1. Office PP was higher than any of the other ABPM-related PP measurements.

Table 1.

Descriptive characteristics of the study sample.

Characteristics	All (N = 699)
Office characteristics
Age, years	62.8 (5.3)
Sex, female	350 (50.1%)
Education, years	8 (7, 12)
Office SBP, mm Hg	142.7 (15.8)
Office DBP, mm Hg	77.5 (71.0, 83.5)
Office PP, mm Hg	65.2 (13.4)
BP-lowering drugs	664 (95.0%)
Poor compliance of BP-lowering drugs	309 (44.2%)
Hypertension duration, years	8 (5,12)
Heart rate, bpm	69.1 (11.1)
Diabetes mellitus	160 (22.9%)
Total cholesterol, mg/dL	218.0 (188.0, 245.0)
Current smoker	104 (14.9%)
Cf-PWV, m/s	10.6 (2.2)
Treatments
Dihydropyridine calcium–channel blocker	104 (15.5%)
Thiazide	316 (47.1%)
β-Blocker	151 (22.5%)
Angiotensin-converting enzyme inhibitor	189 (28.2%)
Angiotensin receptor blocker	319 (47.5%)
Statin	277 (41.3%)
Antiplatelet	122 (18.2%)
Ambulatory blood pressure monitoring
24-hour SBP, mm Hg	126.4 (12.3)
24-hour DBP, mm Hg	76.6 (71.3, 81.0)
24-hour PP, mm Hg	49.9 (10.5)
Day SBP, mm Hg	132.2 (12.3)
Day DBP, mm Hg	81.1 (75.7, 86.2)
Day PP, mm Hg	69.4 (8.0)
Night SBP, mm Hg	117.1 (14.6)
Night DBP, mm Hg	69.2 (63.4, 74.6)
Night PP, mm Hg	47.6 (11.3)
Cerebral small–vessel disease
Lacunar infarcts, any	51 (7.5%)
Number of lacunar infarcts
None	648 (92.5%)
Single	38 (5.6%)
Multiple	13 (1.9%)
Periventricular WMH score (Fazekas scale)
Grade < 2	667 (95.4%)
Grade ⩾2	32 (4.6%)
Deep WMH score (Fazekas scale)
Grade < 2	639 (91.4%)
Grade ⩾2	60 (8.6%)

Abbreviations: BP, blood pressure; bpm, beats per minute; cf-PWV, carotid–femoral pulse wave velocity; DBP, diastolic BP; PP, pulse pressure; SBP, systolic BP; WMH, white matter hyperintensity.

For continuous variables mean (s.d.) or median (interquartile range) and for categorical variables count (%) are given.

Factors Related to Cognitive Function

Demographical characteristics such as age (correlation coefficient r ranging from −0.11 to −0.29) and education (r ranging from 0.23 to 0.49) were correlated to global, attention, memory, or executive functions as expected. As it is shown in Supplementary Table 1, cognitive function was also different in men and women and smokers and nonsmokers. Concerning BPLDs, we found that those who were on angiotensin-converting enzyme inhibitors had lower attention score than those who were not (P < 0.05).

Regarding measures of AS, cf-PWV was inversely correlated with executive function (P = 0.02) and total (P = 0.06) scores. As for PP, all measurements (office and all ABPM-related measurements) were negatively correlated to all cognitive subscales (all P < 0.05), except memory, with the strongest correlations for total DRS-2.

Regarding cSVD lesions, whereas the number of lacunar infarcts was not related to cognitive function, higher WMH grade, especially in deep localization, was inversely related to total and some cognitive subscales (all P⩽0.01).

Next, we evaluated whether all these AS-related measurements were independently associated with cognitive function after adjustment by age, sex, education, BPLDs, antiplatelet and statin treatments (when appropriate), SBP of the period analyzed and other VRFs (model 1), and after further correction for cSVD lesions (model 2) in several linear regression models (one for each cognitive subscale and for each office or ABPM-related PP measurement). After adjustment, most associations were lost and only daytime PP remained as independent predictor for attention (beta = −0.22, 95% CI − 0.40, −0.04, model 1) together with education (for the rest of analyses, data not shown). Further adjustment for cSVD yielded similar results for daytime PP (beta = −0.22, 95% CI − 0.41, −0.03, model 2) and education (beta = 0.07, 95% CI 0.05, 0.10; for rest of the analyses, data not shown).

Factors Associated with Cognitive Status (Mild Cognitive Impairment and Normal Cognitive Aging)

Regarding cognitive status, our univariate analysis showed that MCI participants had less education years than NCA (8 [5, 8] versus 8 [7, 12] P < 0.05), who were more on thiazide treatment (62.7% versus 45.4%, P < 0.05) and antiplatelet drugs (29.2% versus 16.2%, P < 0.01). Higher SBP of ABPM was found for any period in MCI participants than in NCA.

Besides, PP was higher in MCI participants than NCA in ABPM at 24 hours (55.2 (10.6) versus 49.3 (10.4), P = 0 < 0.001), day (56.0 (10.3) versus 50.8 (10.8), P < 0.05), and night (52.7 (12.4) versus 47.1 (11.1), P < 0.05). We explored whether the relation between PP and MCI was linear or there were any J- or U-shape relationship and the last were not found. Therefore, PP was considered as a continuous variable afterwards.

In contrast to ABPM, none of the office measurements, neither PP nor cf-PWV were significantly different between groups. Results comparing cognitive status are shown in Table 2.

Table 2.

Univariate analysis of cognitive status with VRFs, arterial stiffness measurements, and cerebral small–vessel disease.

Characteristics	Normal cognitive aging (N = 628)	Mild cognitive impairment (N = 71)	P-value
Office characteristics
Age, years	62.7 (5.3)	63.2 (5.5)	0.35
Sex, female	309 (49.2%)	40 (56.3%)	0.25
Education, years	8 (7, 12)	8 (5, 8)	<0.05
Office SBP, mm Hg	142.3 (15.6)	143.5 (17.6)	0.73
Office DBP, mm Hg	77.5 (71.0, 84.0)	76.5 (67.0, 82.5)	0.10
Office PP, mm Hg	64.9 (13.2)	67.7 (14.4)	0.11
Poor compliance of BPLDs	276 (43.9)	33 (46.5)	0.68
Heart rate, bpm	69.4 (11.1)	66.1 (10.9)	0.27
Diabetes mellitus	140 (22.3%)	20 (28.2%)	0.26
Total cholesterol, mg/dL	218.0 (188.0, 245.0)	224.5 (185.0, 246.7)	0.39
Current smoker	92 (14.6%)	12 (16.9%)	0.61
Cf-PWV, m/s	10.7 (2.2)	10.5 (2.5)	0.64
Treatments
Dihydropyridine calcium–channel blocker	90 (14.9%)	14 (20.9%)	0.19
Thiazide	274 (45.4%)	42 (62.7%)	<0.05
β-Blocker	137 (22.7%)	14 (20.9%)	0.74
Angiotensin-converting enzyme inhibitor	291 (48.2%)	28 (41.8%)	0.32
Angiotensin receptor blocker	165 (27.3%)	24 (35.8%)	0.14
Statin	271 (41.3%)	34 (47.2%)	0.33
Antiplatelet	106 (16.2%)	21 (29.2%)	<0.01
Ambulatory blood pressure monitoring
24-hour SBP, mm Hg	125.9 (12.1)	130.6 (13.1)	0.02
24-hour DBP, mm Hg	76.5 (71.5, 81.1)	77.7 (70.3, 80.3)	0.37
24-hour PP, mm Hg	49.3 (10.4)	55.2 (10.6)	<0.01
Day SBP, mm Hg	131.8 (12.2)	135.6 (13.0)	0.06
Day DBP, mm Hg	81.1 (75.9, 86.2)	79.4 (72.8, 86.4)	0.18
Day PP, mm Hg	50.8 (10.8)	56.0 (10.3)	<0.05
Night SBP, mm Hg	116.6 (14.3)	121.9 (16.6)	0.04
Night DBP, mm Hg	69.2 (63.6, 74.6)	69.9 (62.7, 75.0)	0.49
Night PP, mm Hg	47.1 (11.1)	52.7 (12.4)	<0.05
Cerebral small–vessel disease
Number of lacunar infarcts			0.04
None	585 (93.2%)	63 (88.7%)
Single	34 (5.6%)	4 (5.9%)
Multiple	9 (1.4%)	4 (5.9%)
Deep WMH score (Fazekas scale)			0.01
Grade < 2	578 (92.0%)	61 (85.9%)
Grade ⩾2	50 (80%)	10 (14.1%)
Periventricular WMH score (Fazekas scale)			0.02
Grade < 2	604 (96.2%)	63 (88.7%)
Grade ⩾2	24 (3.8%)	8 (11.3%)

Abbreviations: BPLD, blood pressure–lowering drug; bpm, beats per minute; cf-PWV, carotid–femoral pulse wave velocity; DBP, diastolic blood pressure; PP, pulse pressure; SBP, systolic blood pressure; VRF, vascular risk factor; WMH, white matter hyperintensity.

For continuous variables mean (s.d.) or median (interquartile range) and for categorical variables count (%) are given. Significant values are shown in italics.

Multivariate analyses considering cognitive status as the outcome measure were performed. For time periods, only nocturnal PP remained independently associated with MCI, (OR per s.d. increase in nocturnal PP = 2.254, 95% CI 1.029, 4.939) together with education after adjustment by covariates of model 1 (age, sex, education, thiazide and antiplatelet use, SBP of the corresponding period, and the other VRFs). Additional correction for the presence of cSVD lesions yielded similar results in night PP per s.d. increase (OR = 2.552, 95% CI 1.137, 5.728). In this last model also years of education (OR = 0.860, 95% CI 0.759, 0.976) and deep WMHs (OR = 1.903, 95% CI 1.096, 3.306) were associated with MCI. Systolic BP was not independently associated with MCI in any period. Results for other time periods are shown in Table 3.

Table 3.

Associations between cognitive status and arterial stiffness.

	Model 1 OR for MCI (95% CI)	Model 2 OR for MCI (95% CI)
Office PP per s.d.	1.429 (0.825, 2.478)	1.485 (0.857, 2.575)
24-hour PP per s.d.	1.642 (0.834, 3.231)	1.969 (0.966, 4.102)
Day PP per s.d.	1.564 (0.785, 3.116)	1.842 (0.895, 3.791)
Night PP per s.d.	2.254 (1.029, 4.939)	2.552 (1.137, 5.728)
Cf-PWV per s.d.	1.143 (0.816, 1.602)	1.102 (0.775, 1.567)

Abbreviations: Cf-PWV, carotid–femoral pulse wave velocity; CI, confidence interval; MCI, mild cognitive impairment; OR, odds ratio; PP, pulse pressure.

Model 1: Adjusted by age, sex, education, diabetes mellitus, total cholesterol, smoking, heart rate, thiazides, antiplatelets, and systolic blood pressure of the analyzed period.

Model 2: Additionally adjusted by the number of lacunar infarcts and deep white matter hyperintensities.

Significant values are shown in italics.

Moreover, ABPM-related PP measurements were also increased in subjects with cSVD (all P < 0.05, data not shown).

We explored the relation of cognitive status jointly with the presence of cSVD lesions and AS. Figure 2 represents levels of daytime and nighttime PP according to cognitive diagnosis and presence or absence of cSVD.

Figure 2.

Relation between cognitive status and cSVD with day and night PP. No cSVD: participants without lacunar infarct and grade <2 in deep WMHs. cSVD: participants who had either a lacunar infarct, deep WMH grade ⩾2 or both. cSVD, cerebral small–vessel disease; MCI, mild cognitive impairment; NCA, normal cognitive aging; PP, pulse pressure; WMHs, white matter hyperintensities. *P-value < 0.05; •, Outlayer case.

Discussion

This observational study in middle- and old-aged hypertensive participants showed that daytime and nighttime PP (as measures of AS) obtained with 24-hour ABPM were associated with attention function and with MCI, respectively. These findings were independent of demographic factors, BP levels, treatments, and other VRFs and, were not attenuated considering the presence of cSVD.

The relation between large-artery stiffness with cognitive function, cognitive impairment, or dementia was reported by several⁶ (but not all)^7,8 clinical and community-based studies. Several of those studies used cf-PWV, to assess AS. When PP was used to assess AS a relation with cognitive outcomes were seen.^21,22 Poor global cognition or poor performance in selected cognitive functions, such as executive function and memory, were reported in those with higher PP in the general population.^21,23 Also a relation between cognitive impairment, especially vascular dementia including Alzheimer’s disease, and cognitive decline was observed in those with higher cf-PWV and PP.^11,24

In our case, inverse correlations were observed between cf-PWV and global and executive functions, although they were lost after correcting for VRFs and cSVD. Some remarkable differences exist between ours and previous studies. Most of the previous studies on cf-PWV and cognitive outcomes performed only univariate analysis or adjusted their analysis only by age, sex, and educational level as main confounders.⁶ Some others corrected also for VRFs^7,22 and one further adjusted by cSVD.²¹ In the latter, including the presence of cSVD in the analyses led to the loss of the associations between cf-PWV and cognitive function, as we found. In addition, our study characteristics may underlie these differences, as our participants were younger than in previous cohorts and most of them were treated with BPLDs.

In contrast to office cf-PWV and also office PP, here we provide evidences that serial PP determinations obtained by means of 24-hour ABPM are independently associated with cognitive status and function. Ambulatory blood pressure monitoring provides a more accurate and reproducible BP measurement than office BP assessment and it is a well-recognized tool to predict cardiovascular risk in hypertensive patients.²⁵ Besides, office measurements are greater influenced by environmental circumstances like white-coat effect that alters values of both cf-PWV and PP measurements.^12,25 The main advantage of ABPM as compared with cf-PWV assessment is its widespread use in the primary care setting, which is the first place where those with cognitive complaints are evaluated.

Previous studies investigated the role of ABPM-related PP measurements in relation to cognition and cognitive status. One of these studies diagnosed MCI participants after sequentially applying two screening tests in hypertensive patients at a cardiology clinic and found an association between MCI and higher 24-hour, day, and night PP measurements in the univariate analysis.⁹ Another one, also showed that in a memory clinic, ambulatory PP measurements were inversely associated with attention function after adjusting for age and education and showed a relation between higher PP and vascular dementia, but no association was found between MCI and 24-hours PP measurements.²⁶ Our results are therefore in agreement with those studies but some important differences should be noted among them. They had small sample size not only in MCI but also in control groups, one only used cognitive screening tools to diagnose cognitive impairment, the other one did not separate the results for the different ABPM periods and none of them corrected their analysis for VRFs and MRI lesions.

Regarding the relevance of the timing of PP assessment, it is well known that PP is defined by structural (stroke volume, velocity of ventricular ejection, and arterial compliance) and functional components and indeed these components might differ between day and night, after a circadian rhythm. During daytime, neurohumoral systems like the renin–angiotensin–aldosterone system are activated and sympathetic activity (that causes vasoconstriction) predominates. In contrast, while we sleep parasympathetic activity increases while a decrease in sympathetic and renin–angiotensin–aldosterone system activity is observed. Thus, the sleeping period is less dependent on the effect of neurohumoral factors like renin–angiotensin–aldosterone system and other environmental stimulus and might be more suitable to predict outcomes. Our results show a cross-sectional association of nocturnal PP with MCI patients, which is independent of nocturnal BP values. This might be surprising given the increasing evidence suggesting a role for nocturnal hypertension predicting cardiovascular risk.²⁷ But, in the case of cognitive function and status, only a few case–control studies have linked higher night SBP with lower cognitive performance with Mini-Mental State Examination or mainly with neurodegenerative dementia (Alzheimer’s disease).^28,29

Recently, 24-hours brachial PWV–recording devices have appeared and showed good and reproducible measurements.³⁰ Future studies should investigate whether 24-hours, daytime, or nighttime PWV provide useful predictive information on cognitive function and dementia, as we have shown for PP.

Other important findings in our study are that in middle-aged and older-treated hypersensitive individuals, PP was also related to the presence of cSVD and both were related to MCI. A previous observational study showed that ambulatory SBP at nighttime was associated with the presence and progression of WMHs and SBP at daytime was only related to WMH progression.³¹ Indeed, a crosstalk has been described between large and small brain arteries that might partly explain our findings. In normal conditions, cerebrovascular autoregulation maintains cerebral blood flow constant despite the changes in BP in large vessels such as carotid and vertebral arteries thereby protecting the brain from changes in perfusion pressure. However, an increase in PP has a greater effect on brain cells than in peripheral organs, since they lack the protection of upstream-vasoconstricted vessels. So, small brain arteries depend on their own resilience to adapt to high-pressure fluctuations and the failure in this adaptation leads to microvasculature damage (hypertrophic remodeling of the vessel wall, lumen narrowing, and vessel rarefaction), which may not only serve to protect the microcirculation from pulsatile barotrauma in the presence of high PP, but also in return will cause an increased resistance to blood flow.³² Microvascular disease may produce hypoperfusion that could lead to cognitive impairment.³³ Also, microvascular disease may result in cerebral infarctions and takes part in the genesis of WMHs as seen in previous studies.³⁴ Then, both the number of silent brain infarcts and WMHs were related to cognitive impairment and dementia, in part because of disconnection of cortico-subcortical loops.³⁵ Our results also showed that daytime PP was associated with attention function, which is considered to be localized in frontal regions that have cortico-subcortical connections.³⁶

Our findings might have therapeutic implications. Lifestyle interventions like aerobic physical exercise have been shown to reduce AS³⁷ and also, a protective role for cognitive decline has been suggested.³⁸ Clinical trials with antihypertensive medication also shown to be effective to reduce AS.³⁹ However, inconsistent results were shown when analyzing if antihypertensive treatment was able to reduce the progression of cognitive decline and the clinical onset of dementia.⁴⁰ Although limitations of these trials have been noted (i.e., cognitive results were analyzed as secondary outcomes and with small sample sizes, short follow-up time, etc.), it remains to be determined if reducing AS has any added effect on reducing dementia and cognitive decline beyond what should be expected by BP reduction. In our case, differences were seen with different BPLDs both for cognitive status and cognitive function (although they were not independent of VRFs and AS), further research is therefore needed to clarify the differential effect of BPLDs in cognitive impairment.

The strengths of this study are the relatively large sample size of community-dwelling hypersensitive individuals without dementia and stroke. Besides, AS measurements were performed by different approaches with oscillometric devices, at different places (office and ambulatory) and as single and multiple (24 hours) assessments. Similarly, we used a standard MRI protocol for the whole cohort and adjusted our results also for VRFs and cSVD. We used a quite extensive cognitive screening test for the selection and diagnosis of the participants that provide more information than for instance Mini-Mental State Examination or other shorter tests. However, using a comprehensive cognitive battery for all the participants, and not in those who failed the DRS-2, just would have diminished the rate of misdiagnosis associated with screening tests. Also using volumetric assessment of white and gray matter would permit a more accurate quantification of cSVD.

Footnotes

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research has been funded with grants from the Fondo de Investigaciones Sanitarias (PI10/0705, CM10/00063, and CP09/136), the Catalonian Society of Hypertension, the Càtedra-UAB Novartis de Medicina de Familia, and IDIAP Jordi Gol. Neurovascular Research Laboratory takes part in the Spanish stroke research network INVICTUS (RD12/0014/0005).

Declaration of conflicting interests

The author(s) has declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Authors’ contributions

IR-L helped in study conception and design, acquisition of data, analysis and interpretation of data, drafted the manuscript, and approved the final version of the manuscript. CN helped in acquisition of data, interpretation of data, drafted the manuscript, and approved the final version of the manuscript. JF helped in acquisition of data, drafted the manuscript, and approved the final version of the manuscript. JLT, XM, and AV-B helped in interpretation of data, revised it critically for intellectual content, and approved the final version of the manuscript. EV helped in study design, interpretation of data, revised it critically for intellectual content, and approved the final version of the manuscript. CIJ helped in acquisition of data, revised it critically for intellectual content, and approved the final version of the manuscript. JM helped in study conception and design, interpretation of data, revised it critically for intellectual content, and approved the final version of the manuscript. PD is the corresponding author and helped in study conception and design, acquisition of data, analysis and interpretation of data, drafting the article and revising it for intellectual content, and approved the final version of the manuscript.

Supplementary material

Supplementary material for this paper can be found at

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