Background
Hypertension is one of the major risk factors for cardiovascular disease (CVD) and is a leading global burden [1, 2]. Because of ease of measurement in a practice setting, brachial blood pressure (BrBP) has been accepted as a gold standard and has been most widely used in the diagnosis, risk stratification and treatment monitoring of hypertensive patients [3, 4]. Robust evidence also suggests that baseline higher BrBP is strongly associated with future CVD outcomes [2]. Recently, the importance of central blood pressure (CBP) in the management of hypertension has been emphasized. It has been suggested that CBP is a more reliable indicator of target organ damage (TOD) and CVD risk than BrBP [5‐10]. The vital organs, including the heart, brain and kidney, are more closely exposed to CBP rather than to BrBP [11‐13]. Also, as blood pressure (BP) varies throughout the arterial tree, BrBP is a poor surrogate for CBP which is lower than the corresponding BrBP [14‐16]. The most reliable method to measure CBP is cardiac catheterization, which can directly measure the pressure of the aortic root using a pressure-sensing catheter [17]; however, it is invasive and costly for using in routine practice. Therefore, several methods of assessing CBP using non-invasive tools have been developed, and its reliability and usefulness have been verified in several studies [15, 18].
TOD is earlier structural and functional changes in vital organs in response to long-standing high BP, such as left ventricular hypertrophy (LVH), arterial stiffening, renal impairment, and retinopathy [3]. The presence of TOD is a marker of increased CVD risk [19, 20]. Thus, evaluation of TOD is important for cardiovascular risk assessment in both subjects with and without hypertension [21]. There have been many studies on the association between CBP and TOD [11, 12, 22‐26]. However, most studies focused on 1 or 2 TOD parameters, and data from systemic evaluation of the influence of CBP on various types of TOD in the same subjects have been scarce. In addition, little has been known about which measurements of CBP have a greater impact on TOD. Moreover, the role of CBP has not been well investigated in patients at high-risk. It has been suggested that TOD information is beneficial for risk stratification to determine proper treatment strategies in high-risk patients [27]. Thus, the present study was designed to investigate the relationship between CBP and TOD, using four measurements of CBP and 9 TOD parameters in patients with documented CVD or multiple risk factors.
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Methods
Study design and population
We prospectively enrolled the study patients aged between 20 and 85 years who had documented atherosclerotic cardiovascular disease (ASCVD), including coronary artery disease and ischemic stroke, or at least two of the traditional risk factors for ASCVD (hypertension, diabetes mellitus, smoking, and obesity) from March 2017 to July 2018. In order standardize the effects of other factors influencing the CBP as much as possible and to perform a more accurate analysis, patients with following conditions were excluded: (1) recently deteriorated chest pain, dyspnea or palpitation; (2) unstable or uncontrolled BP;; (3) left ventricular ejection fraction < 50 %;; (4) valvular regurgitation or stenosis of moderate degree or greater; (5) the presence of pericardial effusion; and (6) atrial fibrillation or other uncontrolled arrhythmia. The study protocol was approved by the Institutional Review Board (IRB) of Boramae Medical Center (Seoul, Korea) (IRB No: 26-2017-55) and written informed consent was obtained from each study patient.
Data collection
Body mass index was calculated as weight in kilograms divided by the square of height in meters (kg/m2). Coronary artery disease (CAD) was defined according to (1) a history of myocardial infarction or coronary revascularization, including percutaneous coronary intervention or coronary artery bypass surgery; (2) documented luminal narrowing of epicardial coronary artery more than 50 % on invasive coronary angiography or coronary computed tomographic angiography; or (3) documentation of myocardial ischemia on exercise treadmill test or single-photon emission computed tomography. Ischemic stroke was defined as a previous diagnosis: a history of focal neurological deficit that continued for > 24 h, which was confirmed by brain imaging. Hypertension was defined as previous diagnosis, the use of antihypertensive medications or a resting BP of ≥ 140/90 mmHg. Diabetes mellitus was defined as a previous diagnosis, the use of oral hypoglycemic agents or insulin or fasting blood glucose ≥ 126 mg/dL. Patients were classified as smokers if they had smoked regularly during the previous 12 months. All subjects underwent laboratory tests by sampling venous blood in the morning after overnight fasting. Blood levels of following parameters were measured by an automated enzymatic procedure: white blood cell count, hemoglobin, total cholesterol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol, triglyceride, glucose, glycated hemoglobin, creatinine, C-reactive protein, and N-terminal pro-brain natriuretic peptide (NT-proBNP). Estimated glomerular filtration rate (eGFR) was calculated using 4-component Modification of Diet in Renal Disease (MDRD) study incorporating age, race, sex, and serum creatinine level [28]. Data were also collected on current medications for CVD, including antiplatelet agents (aspirin and clopidogrel), calcium channel blockers, renin-angiotensin system blockers, beta-blockers and statins.
Measurement of central blood pressure
Radial artery pressure waveforms and BrBP were recorded simultaneously using a fully automated device (HEM-9000AI; Omron Healthcare, Kyoto, Japan) to calculate late systolic pressure in the radial artery (SBP2) and to estimate central systolic BP (CSBP) [18]. The HEM-9000AI utilizes both oscillometer BP detection via a cuff wrap at the upper arm and tonometric measurement at the radial artery in the wrist. The device measures oscillometric signals for non-invasive BP measurement and processes the data through its computer and algorithm within the device. CBP was estimated using a regression equation with SBP2 as a major independent variable [29]. Four measurements of CBP analyzed in this study were CSBP, central diastolic BP (CDBP), central mean arterial pressure (CMAP), and central pulse pressure (CPP).
Target organ damage parameters
The following nine parameters of TOD were assessed: (1) obstructive CAD defined as > 50 % stenosis in the major epicardial coronary arteries on computed tomographic angiography or invasive coronary angiography; (2) LVH defined as left ventricular mass index (LVMI) > 115 g/m2 for man and > 95 g/m2 for woman [30]; (3) concentric remodeling of the left ventricle defined as relative wall thickness (RWT) > 0.42 [30]; (4) diastolic dysfunction defined as septal e′ <7 cm/Sec. [31]; (5) diastolic dysfunction defined as septal E/e′ >15 [31]; (6) chronic kidney disease defined as eGFR less than 60 mL/min/1.73 m2; (7) proteinuria defined as albumin-creatinine ratio (ACR) > 30 mg/g in spot urine; (8) increased arterial stiffness defined as brachial-ankle pulse wave velocity (baPWV) > 1,600 cm/Secs. [32, 33]; and (9) peripheral artery disease defined as ankle-brachial index (ABI) < 0.9. The tests for TOD, including blood test, urinalysis, ABI, baPWV and echocardiography were performed at the same day of CBP measurement. Computed tomographic angiography or invasive coronary angiography for the CAD evaluation was performed within 1 week of CBP measurement.
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Statistical analysis
Continuous variables are presented as means ± standard deviation, and categorical variables are presented as number (%). Pearson correlation analysis was performed to investigate the linear association between the two parameters of CBP measurements and TOD parameters. Scatter plots were used for the demonstration of linear correlations between the two parameters. Mean values of CBP measurements between patients with or without TOD were compared using Student t-tests. Analysis of variance was used to assess the association between mean values of CBP measurements and numbers of TOD parameters. Two-sided P-values < 0.05 were considered statistically significant for all tests. All statistical analyses were performed using IMB SPSS ver. 20.0 (IBM Corp., Armonk, NY, USA).
Results
A total of 148 patients were enrolled and analyzed. The clinical characteristics of the study patients are shown in Table 1. Mean age was 67.1 ± 9.0 years, and 108 patients (73.0 %) were male. Ninety-eight patients (66.2 %) and 15 patients (10.1 %) had a history of CAD and ischemic stroke, respectively. The prevalence rates of hypertension, diabetes mellitus and current smoking in the study population were 74.3 %, 41.9 %, and 25.1 %, respectively. The results of most blood tests were within the normal range except mildly elevated blood level of NT-proBNP. Most patients were taking cardioprotective medications, such as antiplatelets (88.5 %), beta-blockers (71.3 %), renin-angiotensin system blockers (81.8 %), and statins (90.7 %). The results of BP profiles and TOD parameters are demonstrated in Table 2. Most patients had obstructive CAD (77.7 %). Table 3 shows the correlations between BP measurements and 8 TOD parameters. The presence of CAD is a binary variable and is excluded from this correlation analysis. Among eight TOD parameters, CSBP correlated with E/e′ and baPWV, CDBP with eGFR and baPWV, CMAP with baPWV, and CPP with septal e′, E/e′, eGFR, ACR, baPWV, and ABI. CPP was correlated with more TOD parameters than other CBP and BrBP measurements. LVMI and RWT were not associated with CBP measurement but associated with only brachial diastolic BP. Figure 1 shows the correlations between CPP and each value of TOD parameters. Table 4 showed the mean value of CBP measurements according to the presence of TOD. Obstructive CAD and LVH were associated with CDBP and CPP. Left ventricular (LV) diastolic dysfunction assessed by septal e′ velocity and E/e′ were associated with only CPP. LV concentric remodeling and chronic kidney disease (CKD) were not associated with either CBP measurement. Proteinuria was associated with CSBP and CPP. Increased arterial stiffness was associated with CSBP, CMAP, and CPP. Peripheral artery disease was associated with CDBP and CPP. In summary, CPP was associated with the largest number of TOD parameters. Also, CPP value increased as the number of TOD parameters increased (P = 0.010). Other CBP measurements did not show this association (P > 0.05 for each) (Fig. 2).
Table 1
Baseline characteristics of study population (n = 148)
Characteristic | Value |
|---|---|
Demographic finding
| |
Age (yr) | 67.1 ± 9.0 |
Male sex | 108 (73.0) |
Body mass index (kg/m2) | 25.9 ± 3.5 |
Comorbidity
| |
Coronary artery disease | 98 (66.2) |
Ischemic stroke | 15 (10.1) |
Hypertension | 110 (74.3) |
Diabetes mellitus | 62 (41.9) |
Current smoking | 38 (25.1) |
Laboratory finding
| |
White blood cell count (/µL) | 7,290 ± 5,240 |
Hemoglobin (g/dL) | 14.0 ± 1.5 |
Cholesterol (mg/dL) | 150 ± 30 |
Low-density lipoprotein cholesterol (mg/dL) | 78.3 ± 24.1 |
High-density lipoprotein cholesterol (mg/dL) | 47.6 ± 11.7 |
Triglyceride (mg/dL) | 135 ± 83 |
Fasting blood glucose (mg/dL) | 119 ± 33 |
Glycated hemoglobin (%) | 6.35 ± 1.09 |
C-reactive protein (mg/dL) | 0.96 ± 6.89 |
NT-proBNP (pg/mL) | 326 ± 515 |
Medication
| |
Antiplatelet agent | 131 (88.5) |
Calcium channel blocker | 73 (48.7) |
Renin-angiotensin system blocker | 121 (81.8) |
Beta-blocker | 107 (71.3) |
Statin | 136 (90.7) |
Table 2
BP profiles and TOD parameters (n = 148)
Characteristic | Value |
|---|---|
BP profile
| |
Right brachial systolic blood pressure (mmHg) | 135 ± 16 |
Right brachial diastolic blood pressure (mmHg) | 77 ± 10 |
Right brachial mean blood pressure (mmHg) | 96 ± 10 |
Right brachial pulse pressure (mmHg) | 58 ± 14 |
Central systolic blood pressure (mmHg) | 139 ± 19 |
Central diastolic blood pressure (mmHg) | 77 ± 10 |
Central mean blood pressure (mmHg) | 98 ± 11 |
Central pulse pressure (mmHg) | 69 ± 11 |
Central augmentation index (%) | 82 ± 14 |
Parameter of TOD
| |
Obstructive coronary artery disease | 115 (77.7) |
Left ventricular mass index (g/m2) | 97.2 ± 26.0 |
Relative wall thickness | 0.38 ± 0.06 |
Septal e’ velocity (cm/sec) | 5.9 ± 1.8 |
Septal E/e’ | 11.7 ± 4.4 |
Estimated glomerular filtration rate (mL/min/1.73 m2) | 82.0 ± 22.1 |
Microalbumin creatinine ratio (mg/g) | 127 ± 444 |
Brachial-ankle pulse wave velocity (cm/sec) | 1,578 ± 314 |
Ankle-brachial index | 1.08 ± 0.13 |
Table 3
The correlation coefficient (r) between BP measurements and TOD parameters
Variable | LVMI | RWT | Septal e′ | E/e′ | eGFR | ACR | baPWV | ABI |
|---|---|---|---|---|---|---|---|---|
CSBP | 0.014 | 0.077 | –0.148 | 0.271** | –0.126 | –0.041 | 0.416** | –0.142 |
CDBP | –0.125 | –0.011 | –0.011 | –0.011 | 0.192* | –0.096 | 0.247** | 0.149 |
CMAP | –0.067 | 0.038 | –0.007 | 0.149 | 0.045 | –0.091 | 0.379** | 0.007 |
CPP | 0.034 | 0.137 | –0.236** | 0.306** | –0.302** | –0.219* | 0.329** | –0.193* |
BrSBP | –0.011 | 0.065 | –0.096 | 0.267** | –0.090 | 0.032 | 0.398** | –0.151 |
BrDBP | –0.233** | –0.015* | 0.131 | –0.015 | 0.139 | –0.096 | 0.218* | 0.047 |
BrMAP | –0.155 | 0.022 | 0.032 | 0.128 | 0.043 | –0.048 | 0.350** | –0.043 |
BrPP | 0.148 | 0.083 | –0.197* | 0.308** | –0.196* | 0.099 | 0.291** | –0.203* |
Fig. 1
Correlations between central pulse pressure and various types of target organ damage: A left ventricular mass index, B Relative wall thickness, C Septal e’ velocity, D Septal E/e’, E eGFR, F microalbumin/creatinine ratio, G Pulse wave velocity, H Ankle brachial index. eGFR; estimated glomerular filtration rate
Table 4
Mean values of central blood pressure measurements according to the presence of TOD
Variable | TOD (+) | TOD (–) | P-value |
|---|---|---|---|
Obstructive CAD
| (+) (n = 104) | (–) (n = 30) | |
CSBP, mmHg | 139 ± 19 | 139 ± 18 | 0.881 |
CDBP, mmHg | 75.4 ± 9.7 | 81.1 ± 9.7 | 0.007 |
CMAP, mmHg | 96.8 ± 11.3 | 100.5 ± 11.3 | 0.115 |
CPP, mmHg | 64.1 ± 17.1 | 56.0 ± 14.3 | 0.036 |
LVMI
| > 115 g/m2 for male and > 95 g/m2 for female (n = 91) | ≤ 115 g/m2 for male and ≤ 95 g/m2 for female (n = 31) | |
CSBP, mmHg | 140 ± 20 | 138 ± 19 | 0.770 |
CDBP, mmHg | 72.8 ± 9.9 | 77.2 ± 9.8 | 0.031 |
CMAP, mmHg | 95.1 ± 10.7 | 97.7 ± 11.7 | 0.294 |
CPP, mmHg | 68.1 ± 20.0 | 61.3 ± 15.4 | 0.041 |
RWT
| > 0.42 (n = 24) | ≤ 0.42 (n = 98) | |
CSBP, mmHg | 142 ± 23 | 138 ± 18 | 0.311 |
CDBP, mmHg | 76.0 ± 10.8 | 76.1 ± 9.8 | 0.976 |
CMAP, mmHg | 98.2 ± 12.9 | 96.7 ± 11.1 | 0.565 |
CPP, mmHg | 66.7 ± 21.0 | 61.9 ± 15.6 | 0.307 |
e′ velocity
| < 7 cm/sec (n = 105) | ≥ 7 cm/sec (n = 17) | |
CSBP, mmHg | 140 ± 20 | 132 ± 14 | 0.113 |
CDBP, mmHg | 75.6 ± 10.1 | 78.9 ± 8.6 | 0.216 |
CMAP, mmHg | 97.1 ± 11.8 | 96.7 ± 9.7 | 0.888 |
CPP, mmHg | 64.4 ± 17.1 | 53.1 ± 10.6 | 0.010 |
E/e′
| > 15 (n = 25) | ≤ 15 (n = 97) | |
CSBP, mmHg | 143 ± 23 | 137 ± 18 | 0.173 |
CDBP, mmHg | 73.8 ± 11.9 | 76.7 ± 9.4 | 0.192 |
CMAP, mmHg | 97.1 ± 14.5 | 97.0 ± 10.6 | 0.967 |
CPP, mmHg | 70.1 ± 16.5 | 60.0 ± 16.5 | 0.015 |
eGFR
| < 60 mL/min/1.73 m2 (n = 27) | ≥ 60 mL/min/1.73 m2 (n = 107) | |
CSBP, mmHg | 143 ± 19 | 138 ± 19 | 0.330 |
CDBP, mmHg | 74.5 ± 8.6 | 77.3 ± 10.2 | 0.188 |
CMAP, mmHg | 97.1 ± 10.9 | 97.8 ± 11.5 | 0.791 |
CPP, mmHg | 67.8 ± 16.7 | 61.4 ± 16.5 | 0.085 |
ACR
| > 30 mg/g (n = 43) | ≤ 30 mg/g (n = 78) | |
CSBP, mmHg | 144 ± 19 | 136 ± 18 | 0.034 |
CDBP, mmHg | 76.2 ± 10.0 | 76.5 ± 9.7 | 0.877 |
CMAP, mmHg | 98.7 ± 11.2 | 96.6 ± 11.0 | 0.303 |
CPP, mmHg | 67.8 ± 18.5 | 60.1 ± 14.8 | 0.015 |
baPWV
| > 1,600 cm/sec (n = 57) | ≤ 1,600 cm/sec (n = 77) | |
CSBP, mmHg | 145 ± 19 | 135 ± 18 | 0.003 |
CDBP, mmHg | 77.3 ± 10.5 | 76.3 ± 9.6 | 0.578 |
CMAP, mmHg | 99.9 ± 11.9 | 95.9 ± 10.7 | 0.043 |
CPP, mmHg | 68.0 ± 16.6 | 58.8 ± 15.7 | 0.001 |
ABI
| < 0.9 (n = 9) | ≥ 0.9 (n = 125) | |
CSBP, mmHg | 145 ± 24 | 139 ± 19 | 0.353 |
CDBP, mmHg | 67.6 ± 11.4 | 77.4 ± 9.6 | 0.004 |
CMAP, mmHg | 93.6 ± 14.6 | 97.9 ± 11.1 | 0.277 |
CPP, mmHg | 77.8 ± 17.3 | 61.7 ± 16.2 | 0.005 |
Fig. 2
Association between central blood pressure and the number of TOD parameters. CSBP, central systolic blood pressure; CDBP, central diastolic blood pressure; CMAP, central mean arterial pressure; CPP, central pulse pressure; TOD, target organ damage
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Discussion
Our result, using four CBP measurements and nine TOD parameters, showed that each CBP measurement were related to different TOD parameters in patients with ASCVD or its multiple risk factors. Among four CBP measurements (CSBP, CDBP, CMAP, and CPP), CPP was the best correlate with TOD. It also revealed that the higher CPP was, the more target organs were damaged.
Vital organs, such as the heart, kidneys, and brain, are more directly exposed to CBP rather than to BrBP. In this study, CPP was correlated with the most indices of TOD (6/8), although both CBP and BrBP parameters could predict TOD well. There is a theoretical background that central aorta is closer to major organs, so CBP’s influence is greater than BrBP [34, 35]. CBP represents the true pressure load imposed on the heart, kidney and brain, and flow derived by CBP influences the local flow into these vital organs [13]. Therefore, CBP could be better correlated with cardiovascular prognosis and TOD than BrBP [9]. In the Strong Heart Study, CBP was more strongly associated with future cardiovascular events than BrBP in disease-free individuals [5]. Other studies have shown that CBP lowering may be responsible for LVH regression and the improvement in cardiovascular prognosis beyond BrBP lowering [8, 36]. These findings support the hypothesis that CBP-lowering drugs may be more effective than BrBP-targeting ones [8].
It is not well-known which CBP measurements are clinically relevant. A few studies have emphasized the importance of CPP, as it was associated with the risk of TOD and ASCVD. Jankowski et al. [37] showed that CPP and pulsatility of the central aorta were the most important factors related to CAD rather than BrBP, and Central Aortic Pressure and Clinical Outcomes (CAFÉ) study also revealed that CPP may be a main determinant of clinical outcomes [8]. Madhavan et al. [38] demonstrated that the wider pulse pressure (PP) was identified as a predictor of myocardial infarction. In line with these studies, our findings also showed that CPP was most important factor predicting TOD among CBP measurements.
Possible mechanisms explaining the association between CPP and TOD can be suggested. Elevation of PP is both a cause and a result of arterial damage and atherosclerosis. Degenerative changes in the aortic wall and arterial tree by aging increase stiffness of the aorta, and lead to an increase in PP [39]. With repeated exposure to increased CPP, the arteries are directly damaged and arteriosclerosis progresses [21]. Progressive aortic stiffness increases systolic BP and decreases diastolic BP, which makes CPP wider [40]. Therefore, CPP is an indicator of aortic stiffness. Patients with increased aortic stiffness share common cardiovascular risk factors of TOD, such as aging, high BP, hyperglycemia, and dyslipidemia [41]. In addition, increased systolic BP cause LVH, and low diastolic BP is associated with decreased coronary blood flow [42].
Risk stratification and early aggressive management for high-risk patients is important for preventing future cardiovascular events and for reducing morbidity and mortality. The present study revealed that CBP, especially CPP, is valuable in the prediction of TOD. Measurement of CBP using radial artery tonometry, which is non-invasive and well-validated, could be useful for the risk stratification of high-risk patients. This study could also be a hypothesis-generating trial for further investigations into the development of novel medications lowering CPP or using CPP as a monitoring tool.
Some limitations are present in this study. First, because cardiovascular outcomes, such as myocardial infarction or mortality, were not investigated, we could not conclude whether CPP was related to long-term prognoses of patients. However, as TOD is a well-known factor closely related to worse cardiovascular outcomes [19, 20], CPP might be a prognostic factor of future cardiovascular events. Longitudinal studies with a larger sample size are warranted. Secondly, due to the relatively small number of study patients, we were able to show only weak linear correlations between CBP and the parameters of TOD. There was also a possibility that associations between some other CBP measurements and TOD did not reach statistical significance. For similar reason, the superiority of CBP over BrBP could not be proved in this study, however, the purpose of our study is not to compare CBP and BrBP. Thirdly, the duration or risk factors of ASCVD could have had an effect on CBP measurements and TOD; however, our data did not provide information on this. Finally, as our data were collected from Korean patients at high coronary risk, it should be cautious in applying them to other ethnic groups of patients.
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Conclusions
CPP had a stronger correlation with TOD than other CBP measurements in patients with ASCVD or multiple risk factors. Non-invasive measurement of CPP may be a useful tool for risk stratification of high-risk patients.
Acknowledgements
Not applicable.
Declarations
Ethics approval and consent to participate
The study protocol was approved by the Institutional Review Board (IRB) of Boramae Medical Center (Seoul, Korea) (IRB number, 26-2017-55) and written informed consent was obtained from each study patient.
Consent for publication
Not applicable.
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Competing interests
The authors declare that they have no competing interests.
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