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Measurement of Stiffness Index by Digital Volume Pulse Analysis Technique: Clinical Utility in Cardiovascular Disease Risk StratificationAshan Gunarathne1, Jeetesh V. Patel1, Elizabeth A. Hughes1 and Gregory Y.H. Lip1 CVD risk factors (diabetes mellitus: 33%, hypertension: 77.8%, Indices of arterial stiffness are accepted as independent markers of hypercholesteremia: 61%). On univariate analysis, sI was strongly cardiovascular disease (CVD), having both positive prognostic and associated with CVD risk (the European society of Cardiology diagnostic implications. the utility of stiffness index (sI) derived (EsC) based Heartscore) (Pearson correlation coefficient (R): 0.56, from digital volume pulse (DVP) analysis in CVD risk screening is not P ≤ 0.001) and increased in an ordinal fashion from "low risk" to "medium risk" to "high risk" to "very high risk" (pseudo R2 = 0.30; P < 0.001). In receiver operator characteristic curve analysis, sI was the best discriminator between low to medium risk and high-risk categories using a representative sample of individuals from local communities (area under curve (AuC): 0.76 (95% CI 0.64–0.88), P < 0.001) when (West Midlands, uK), we determined the performance of sI in the compared to total cholesterol, plasma glucose, systolic blood discrimination of increasing CVD risk. Arterial stiffness was measured pressure, and waist-to-hip ratio and had the utility to discriminate by DVP photoplethysmography (PCA 2; Micro Medical) using a direct, the individuals with known CVD risk factors such as diabetes standardized approach. CVD risk assessment was performed in and hypertension.
accordance with the Joint British society guidelines (JBs2).
Noninvasive measurements of arterial stiffness may aid the optimal Of our cohort of 247 individuals (51% male; mean age 55.2 (s.d. stratification of CVD risk in an apparently healthy population.
10.3) years), 187 were apparently healthy and 60 had established Am J Hypertens 2008; 21:866-872 2008 American Journal of Hypertension, Ltd.
Cardiovascular disease (CVD) is the commonest cause of Hence, there is a need for novel risk markers (or biomarkers) morbidity and premature mortality in the Western world1 and which are capable of directly examining the underlying has rapidly become an epidemic in the developing world over pathophysiological processes for refining risk stratification and recent years.2 Given the considerable health care burden con- the early identification of younger high-risk populations.6 To ferred by this disease, the timely identification of individuals be clinically useful in the prediction of CVD, novel techniques with an increased risk of CVD is an important consideration.
should be closely related to the existing prediction methods. In The assessment of CVD risk among individuals is usually addition, they should also provide an additional value to the performed by calculating "risk scores", such as the Framingham existing methods in risk assessment.
risk prediction score3 and, more recently, European Society Central to our current pathophysiological understand- of Cardiology (ESC) HeartScore.4 Risk score estimation uses ing of CVD is closely allied with accelerated atherosclerosis a combination of "established risk factors" including age, and age-related arteriosclerosis7,8 which are known to alter gender, systolic blood pressure, total cholesterol, and gly- vessel wall characteristics and increase arterial stiffness.9 cemic status. However, these scores are known to underesti- Measures of arterial stiffness indices are accepted as indepen- mate actual risk within high-risk populations, which has led dent markers of CVD having both prognostic and diagnostic to the quest for novel risk markers for finer and earlier risk implications.10–13 The majority of available methods for mea- suring arterial stiffness have proven to be both technically dif- ficult to perform and time consuming,14 specifically in terms 1university Department of Medicine, City Hospital, Birmingham, uK. of their use in risk assessment among large populations and in Correspondence: gregory Y.H. Lip community settings.
Received 12 December 2007; first decision 13 January 2008; accepted 29 April 2008; The stiffness index (SI) derived from the analysis of digital vol- advance online publication 12 June 2008. ume pulse (DVP) is a noninvasive indirect technique of measur- 2008 American Journal of Hypertension, Ltd.
ing arterial stiffness peripheral y.15 Arterial stiffness measured August 2008 VOLuME 21 NuMBER 8 866-872 AMERICAN JOURNAL OF HYPERTENSION
Clinical Utility of Stiffness Index in Clinical Practice
by the DVP analysis method has been proven to be a vali- 1 min intervals in the first instance and repeated in the arm dated and reproducible technique with minimal intraobserver with the higher blood pressure reading with the validated sem- variation.16,17 The SI has been demonstrated to have a compara- iautomatic Omron HEM-705CP (Omron Healthcare Europe, ble sensitivity and specificity to the pulse wave velocity method Mannheim, Germany) with appropriate cuff sizes after >5 min in the identification of patients with latent CVD.18 However, sitting.21 The mean of the last two blood pressure levels were its utility in cardiovascular risk assessment process among an used in the analysis. The heart rate was recorded from the last apparently healthy population has not been investigated.
recorded blood pressure reading. Mean arterial blood pressure We hypothesized that SIs measured by DVP technique are was calculated by a formula: the mean pulse pressure added to strongly associated with ESC based cardiovascular risk scores one-third of the diastolic blood pressure.
in an apparently healthy population and that the SI is a good discriminator of stratification of CVD risk categories among Calculation of the SI using pulse wave form reflections. SI is a wider population that includes higher risk individuals. To test parameter derived from the analysis of the pulse wave forms this hypothesis, we measured the indices of arterial stiffness in which reflects the tone and arterial distensibility. Similar to other a representative population attending a CVD risk assessment noninvasive measurements such as augmentation index, this is clinic over a 1-year period.
an indirect method of determining arterial stiffness peripheral y. The digital pulse volume pulse waveform consists of a systolic peak and a second diastolic peak which is formed by the reflec- Using a representative sampling approach, volunteers who had tion of the pulse wave from the smal arteries in the lower body similar socioeconomic19 backgrounds based on the Townsend distal y. The time delay (peak-to-peak time (PPT), se deprivation index were recruited from the Sandwell and West between the systolic and diastolic peaks is related to the transit Birmingham Primary Health Care Trust (West Midlands, UK). time of pressure waves from the root of the subclavian artery to The total cohort (aged 30–75 years) comprised apparently the apparent site of reflection and back to the subclavian artery. healthy people without any known established risk factors and In addition to large vessel wall stiffness, the degree of pulse wave people with a past medical history of hypertension, diabetes, reflection also depends on the impedance of the microvascular and hyperlipidemia who were on treatment but had no history bed and the tone of the small to medium sized blood vessels. This of established cardiovascular events (e.g., myocardial infarc- path length can be assumed proportional to height (h). Therefore tion or stroke) according to careful clinical history, examina- index of large artery stiffness can be calculated from: SI = tion, and hospital medical records. All healthy subjects were h/PPT (ref).
free from documented CVD or risk factors (hypertension, diabetes mellitus, hyperlipidemia, ischemic heart disease, myo- Arterial stiffness measurement protocol. Arterial stiffness cardial infarction, and atrial fibrillation), peripheral artery dis- measurement was performed on the morning following an ease, or cerebrovascular disease (stroke or transient ischemic overnight fast (each subject was instructed to refrain from attack). None of the subjects was on any regularly prescribed caffeine-containing beverages, alcohol, and smoking in the cardiovascular medications at the time of the study. This was previous 12 h) after which the DVP was recorded in the per- established by the elicitation of a full medical history and the son's right index finger. Subjects were laid supine resting for completion of a comprehensive physical examination per- at least 20 min in a temperature controlled environment (24 ± formed by a qualified medical practitioner. Any person with 1 °C) before the measurements were taken. All the volunteers abnormal blood pressure measurements (>140/90 mm Hg), were advised to refrain from talking and sleeping while the fasting blood sugar level (>7 mmol/l), or a total cholesterol measurements were done. Patients with risk factors who were level (>5 mmol/l) was excluded from the study. Demographic on any antihypertensive or antianginal medications were asked data including details of smoking habit and alcohol consump- to miss their morning dose.
tion were collected.
Using the ESC HeartScore risk calculator, the absolute CVD risk (%) of developing nonfatal coronary heart disease, coronary death, or stroke over the next 10 years was estimated.20 This ESC HeartScore algorithm has been selected as the new stan- dard in European CVD risk prediction and management by the Third Joint European Societies Task Force on CVD Prevention in Clinical Practice4 and is based upon the risk factors, namely, age, gender, smoking status, systolic blood pressure, total cho- lesterol levels, and diabetes status. Each subject provided written and informed consent and the study was approved by the West Birmingham Local Research Ethics Committee.
Figure 1 Derivation of stiffness index from digital volume pulse analysis
Measurement of blood pressure. Systolic and diastolic brachial technique. X = forward wave/systolic peak; Y = reflected wave/diastolic peak; arterial blood pressure levels were measured in both arms at stiffness index = subject's height (m)/PPt. PPt, peak-to-peak time.
AMERICAN JOURNAL OF HYPERTENSION VOLuME 21 NuMBER 8 August 2008
Clinical Utility of Stiffness Index in Clinical Practice
Recorded digital pulse wave forms using the photoplethys- Repeatability and reproducibility of SI measurements. SI was mography technique (PCA 2; Micro Medical) were used to measured in a total of three times in each arm at 5-min inter- generate indices of vessel reactivity and arterial stiffness as vals apart in 100 individuals at the same clinic visit. These per a standard validated protocol.20 Each person had at least measurements were repeated in a separate clinic visit in the three measurements (recorded for 30 s) taken 1 min apart and same temperature controlled environment in 6 weeks time. an average was calculated and used for the analysis. Volunteers Repeated measurements on the same visit (mean difference whose pulse wave recordings could not be adequately assessed (s.d.): 0.09 (0.66)) as well as in the separate visit (0.12 (0.93)) were excluded from the final analysis. In addition, volunteers demonstrated a good agreemen who had an SI variation of >15% within measurements were also excluded. All of the measurements were performed by the same operator. Intraobserver variation (coefficient of variation) of the repeated measurements of SI in the same subject on the same day and 6 weeks later was 5.4% and 7.4%, respectively.
Statistical analysis. Data were analyzed using SPSS version v14 (SPSS, Chicago, IL). After being tested for normality using the Kolmogorov–Smirnov test, all the indices measured demon- strated a normal distribution. Data are presented as the mean ± Mean stiffness index difference s.d. Student's t-test and one-way analysis of variance tests were used to determine differences between groups with continuous Mean stiffness index (m/s) variables, and the χ2-test was used to compare the categorical variables. In univariate analysis, Pearson's correlation was used to observe the relationship between arterial stiffness and other cardiovascular risk indices. Linear regression models were used for multivariate analysis. For the correlation analysis of ordi- nal variables, Polytomous Universal Model ordinal regression analysis was used where the Cox and Snell pseudo R2 values are reported to estimate the proportion of the total variation of an ordinal response that is explained by variables included in Mean stiffness index difference the model. Receiver operator characteristic curves were used to evaluate the performance of SI depicted by the mean area under Mean stiffness index (m/s) the curve with 95% confidence interval. A two-tailed P value Figure 2 Bland–Altman test demonstrating the agreement between
<0.05 was considered statistical y significant for all compari- repeated measurements of stiffness index (a) during a single-visit and (b) in
sons. Data are reported to three significant figures.
follow-up visits.
table 1 healthy volunteers vs. people with established cardiovascular risk indices
Cardiovascular risk factors
Mean (s.d.)
Body mass index (kg/m2) Waist-to-hip ratio Mean systolic BP (mm Hg) Mean diastolic BP (mm Hg) Mean arterial BP (mm Hg) serum Cholesterol (mg/dl) Fasting plasma glucose (mg/dl) EsC CVD risk score (%) stiffness index (m/s) BP, blood pressure; CVD, cardiovascular disease; ESC, European Society of Cardiology.
aP value comparing healthy vs. risk controls; significance at 0.05 level.
August 2008 VOLuME 21 NuMBER 8 AMERICAN JOURNAL OF HYPERTENSION
Clinical Utility of Stiffness Index in Clinical Practice
with a higher body mass index (P = 0.49). Subjects within the A total of 187 healthy volunteers and 60 people with risk fac- upper tertile of mean arterial pressure also had a higher SI com- tors were recruited for the study Fifty-one percent pared to those in the lower tertile (P < 0.001).
of the subjects were between 30 and 41 years of age and 57.7% Measurements of SI was also significantly higher in people were male. As expected, patients with established CVD risk with established risk CVD factors without any gender variation factors were older, had higher systolic blood pressure and CVD (P < 0.01). Subjects with higher SI (upper tertile) compared to risk scores (P < Of the patients with established lower tertile were older (P < 0.001), were smokers (P = 0.04), CVD risk factors, 33% had diabetes mellitus, 77.8% had a diag- and had significantly higher mean systolic (P < 0.001) and nosis of hypertension, and 61% had hypercholesteremia. Of diastolic (P < 0.006) blood pressure as well as CVD risk scores these patients, 38.9% were on regular antihypertensive medi- (P < 0.001) cations, 11.1% were on antidiabetes medications, 11.2% were on anticholesterol treatment, and 14.4% were on antiplatelet relationship to esc based cVd risk stratification
On univariate analysis, there was a positive association SI was significantly higher in males (P = 0.01), as wel as in between SI and CVD risk (Pearson correlation coefficient (R): people in the upper age tertile vs. lower tertile (P < 0.001), smok- 0.56, P ≤ 0.001). On linear regression analysis, SI was associ- ers (P = 0.006), those with a history of hypertension (P = 0.007), ated with CVD risk scores (β (s.d.): 0.58 (1.3–2.0); P < 0.001). diabetes (P = 0.02), hypercholesteremia (P = 0.002), and those SI increased in an ordinal fashion across from low risk (<5%), with a high waist-to-hip ratio (P = 0.001) but not with those medium (5–10%), high (11–19%), and highest risk (>20%) (Pseudo R2 = 0.30; P < 0.001) Of the total population, 48.7% had lower-medium CVD table 2 indices of arterial stiffness (sis) for the total cohort
risk (<15%) and correspondingly lower SI values (mean ± s.d.: % of all Mean arterial
patients stiffness m/s
7.9 (1.5) m/s compared to those at high risk (P < (n = 247)
0.001). In addition, male subjects had a higher CVD risk score (P < 0.001) and correspondingly higher SI compared to the females (P = 0.01). There was a significant difference in the mean risk score levels (P < 0.001) and SI between healthy vol- unteers and risk factor controls in both males (P = 0.008) and females (P = 0.015) Waist-to-hip ratio correlations and multivariate regression
On univariate analysis (excluding people with established risk factors and medications), there was a significant positive asso- ciation (R) between SI and age (R = 0.41; P < 0.001) mean sys- tolic (R = 0.24; P < 0.001), diastolic blood pressure (R = 0.29; P = 0.001), pulse pressure (R = 0.17; P = 0.03), and mean arte- rial pressure (R = 0.34; P = 0.003). There was no significant association between SI and mean heart rate, body mass index, waist-to-hip ratio, fasting plasma glucose, and serum choles- terol. In multivariate regression analysis, β (95% CI) age (0.11 (0.04–0.17); P < 0.002), waist-to-hip ratio (0.33 (0.25–0.41); P = 0.05), and mean arterial pressure (0.06 (0.01–0.11); P = 0.01) independently associated with SI but not with serum cholesterol, fasting plasma glucose levels, or heart rate.
receiver operator characteristic curve analysis
Receiver operator characteristic curve analysis of baseline characteristics to discriminate subjects with higher CVD risk found SI to be the most useful variable in this population (area under curve (AUC): 0.76 (s.e. 0.06), P < 0.001) compared to total cholesterol (AUC: 0.58 (0.07), P = 0.17), plasma glucose (AUC: 0.62 (0.07), P = 0.07), mean blood pressure (AUC: 0.60 (0.06), P = 0.15), and waist-to-hip ratio (AUC: 0.45 (0.04), P = 0.35). In addition, SI had the discriminatory utility to iden- tify the patients with known diabetes (AUC: 0.68 (s.e. 0.04), P < aP value using one-way analysis of variance across all groups and independent t-test; significance at 0.05 level. bP value using χ2.
0.001), hypercholesteremia (AUC: 0.66 (s.e. 0.03), P < 0.001), hypertension (AUC: 0.66 (s.e. 0.03), P < 0.001), and higher AMERICAN JOURNAL OF HYPERTENSION VOLuME 21 NuMBER 8 August 2008
Clinical Utility of Stiffness Index in Clinical Practice
table 3 cardiovascular risk profile according to stiffness index tertiles for the total population
Mean stiffness index tertiles
Risk factors
Mean stiffness index Mean systolic BP (mm Hg) Mean diastolic BP (mm Hg) Mean arterial BP (mm Hg) Body mass index (kg/m2) Waist-to-hip ratio Fasting plasma glucose (mg/dl) serum Cholesterol (mg/dl) Risk factor (%) smoking status (%) Data are mean (s.d.).
BP, blood pressure; CVD, cardiovascular disease; ESC, European Society of Cardiology.
aP value using one-way analysis of variance across all groups; significance at <0.05 level. bP value using χ2.
Pseudo R2 = 0.30 P < 0.001 Stiffness index (m/s) ESC cardiovascular risk groups Figure 3 Ordinal association between mean stiffness index and European
society of Cardiology (EsC) risk score groups in healthy volunteers and in patients with cardiovascular risk factors. EsC Heartscore–based cardiovascular disease (CVD) risk groups (%): group I (<5%), group II (6–15%), group III (16–19%), group IV (>20%). Line shows the mean CVD risk score.
CVD risk tertiles waist- to-hip ratio (AUC: 0.69 (s.e. 0.05), P = 0.001) but not with higher body mass index (AUC: 0.50 (s.e. 0.06), P = 0.92).
Figure 4 Distribution of stiffness index (sI) and cardiovascular disease (CVD)
risk groups according to tertiles for the healthy population. European society
of Cardiology Heartscore–based CVD risk tertiles (%): tertile I = (<5%),
tertile I = (6–15%), tertile I I = (>16%). sI tertiles (m/s): tertile 1 = sI <7.7; In this study, we demonstrate the clinical utility of a marker of tertile 2 = sI 7.8–9.7; tertile 3 = sI >9.8.
arterial stiffness to stratify CVD risk in individuals using the digital pulse wave form analysis technique. This study dem- Screening of the population with ESC HeartScore and onstrates a close association between SI and CVD risk score Framingham-based risk score methods continue to be recom- estimation using the ESC HeartScore model. More impor- mended in many current guidelines.22 However, the absolute tantly, the discriminatory properties of the SI in identifying levels of cardiovascular risk factors are mathematical y com- higher risk groups were significantly better than those of con- bined as a holistic approach during risk prediction with limited ventional cardiovascular risk indices such as total cholesterol direct relationships to underlying pathophysiological changes. level and fasting blood sugar measurements.
In this study, 16% of the people in the higher SI tertile stil August 2008 VOLuME 21 NuMBER 8 AMERICAN JOURNAL OF HYPERTENSION
Clinical Utility of Stiffness Index in Clinical Practice
had lower-medium CVD risk scores . This suggests was based on a European risk score engine (ESC based Heart that a significant proportion of the higher risk subjects may be Score), which does not use high-density lipoprotein cholesterol missed in a traditional risk assessment process and highlights for risk estimation compared with the Framingham (United the importance of using potential new risk markers to aid more States)-based risk calculation which allows finer risk stratifica- conventional cardiovascular risk stratification schemes.
tion of higher CVD risk individuals with lower high-density The novel DVP technique used to asses the arterial distensi- lipoprotein values. In addition, the DVP method used to mea- bility of volunteers in this study is an easily performable, non- sure arterial stiffness in this study did not provide information invasive technique with low intraobserver and interobserver on individual contributions that both large and small arter- variation. This method allows the indirect examination of ies make toward wave reflection and overall arterial stiffness. the structural integrity of both large and small arteries simul- Furthermore, calculation of SI is based on the assumption that taneously allowing the identification of apparently healthy subject's height is proportional to the path length of the wave individuals with subclinical atherogenesis and premature arte- reflection. In addition, this study may not have the power to riosclerosis. Measurements of SI may therefore be more useful discriminate or compare the established risk factors such as in the early identification of high-risk subjects without estab- smoking status between healthy and risk factor control groups. lished risk indices such as high blood pressure or cholesterol Moreover, this study doesn't provide the facility to determine levels. Such people are usually omitted in traditional CVD risk the discriminatory utility of SI in different age categories. Using a larger prospective study design that used CVD out- As expected, subjects with established risk factors in our comes with combined methods of measurement (pulse wave study also demonstrate higher SI when compared to healthy velocity and DVP, for example) would possibly have provided controls. Moreover, the SI was a better discriminator in iden- more comprehensive details thereby giving greater explanatory tifying people with established CVD risk factors (such as power to this study. However, the logistics for such a study are hypertension, diabetes, and hypercholesteremia) where indi- also limited by the need-to-treat individuals recognized to be vidual point measurements of theses risk indices are less use- at increased CVD risk.
ful, for example, where they are taking medications. While this In conclusion, SIs measured using the DVP technique is study highlights the clinical utility and acceptability of DVP strongly associated with the ESC "HeartScore" cardiovascular measurements in a wide spectrum of individuals with and risk score and demonstrates the discriminatory utility of the SI without established risk factors, further studies are warranted in identifying high-risk populations. Thus, noninvasive mea- to asses the utility of SI in clinical practice and to monitor surement of arterial stiffness may aid the identification of indi- treatment efficacy as well as disease progression.
viduals with high cardiovascular risk. However, there is a need In our study, the principal factors contributing to increased for future external validity studies of SI to demonstrate the SI include age and mean arterial pressure but not body mass ability to prospectively predict the clinical outcomes over and index. This is in keeping with the other published studies in above those predicted by existing CVD risk score estimations.
which the pulse wave technique was used.23–25 The indepen- dent association between waist-to-hip ratio with increased Acknowledgment: this research project was funded by the Research & Development department of City & sandwel West Birmingham Hospitals SI merits careful consideration. Indeed, several studies have NHs trust.
reported an association between waist-to-hip ratio and cardio- vascular risk factors such as hypertension and lipid and glu- Disclosure: the authors declared no conflict of interest.
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