Pulse Wave Velocity Assessment: A Useful Tool to Screen Asymptomatic Individuals at High Cardiovascular Risk?

The global burden of cardiovascular (CV) disease is very high worldwide, and it is expected to increase further due to the aging of the population. The estimated expected 20.5 million deaths in 2025 are projected to increase to 35.6 million by 2050 [1]. These alarming data necessitate urgent action to tackle such rising burden. Strengthening actions of screening, early detection and prevention of individuals at high CV risk at the global level is crucial. Healthcare systems, particularly in countries with high rates of CV deaths from atherosclerotic disease and relatively low financial resources, should implement effective and targeted interventions to address this growing challenge.

The atherosclerotic process, like its risk factors—including hyperglycemia, dyslipidemia, and hypertension—often progresses asymptomatically. This makes risk stratification for CV disease particularly challenging among general population and supports the need of developing screening strategies using simple, reliable, and cost-effective methods. Simple tools to perform CV risk stratification at the individual level include blood pressure (BP) measurement and blood tests for serum glucose and cholesterol. Automated BP monitors offer a simple and relatively inexpensive option for mass screening. In contrast, blood tests require additional costs, specialized personnel, and dedicated facilities, making them more suitable for selective screening of individuals after an initial selection.

Some novel BP monitors, such as the Tel-o-Graph, integrate brachial BP measurement with pressure waveform detection [2]. The subsequent analysis of the brachial waveform profile using proprietary algorithms enables the non-invasive measurement of pulse wave velocity (PWV), a measure of arterial stiffness. This parameter is a recognized marker of vascular aging, reflecting the progressive decline in arterial elasticity which may be accelerated by the cumulative CV risk factors and other determinants. Automated oscillometric cuff-based PWV measurement could therefore be promising to identify individuals at high CV risk where asymptomatic CV risk factors have already cumulatively accelerated arterial degeneration [3].

The results of the study presented by Celenk et al. in the current issue of the Journal [4] provide seminal evidence in support of the hypothesis that automated PWV assessment could be useful as a screening tool to identify individuals at high CV risk. The authors analyzed the characteristics of a selected population of 209 participants from a cohort of subjects aged 40–69 years who attended a Family medicine clinic in Turkey. These clinics usually serve as primary points of contact for medical care, offering comprehensive primary healthcare services for individuals and families.

All participants underwent the assessment of their 10-year absolute risk of fatal and non-fatal CV events using both the Framingham Risk Score (FRS) calculator [5] and the novel SCORE-2 [6] risk equation. Both tools employ a similar multivariable approach based on key CV risk factors such as age, sex, systolic BP values, smoking status total, and HDL-cholesterol values. A major difference is that the FRS directly incorporates diabetes risk, whereas the SCORE-2 approach uses a separate tool (SCORE-DM) for individuals with diabetes [7]. This distinction reflects the fact that CV risk in diabetes may be influenced by factors not included in SCORE-2, such as age of diagnosis, diabetes duration, and renal function. Another major difference is that the FRS classifies individuals into low—intermediate and high-risk categories based solely on absolute risk, whereas SCORE-2 also considers age categories in its approach.

The authors categorized the entire population into three age- and sex-matched groups based on different risk categories (low-intermediate-high) and examined the ability of PWV to discriminate between individuals in these risk categories. Overall, PWV proved effective in predicting individuals at high versus low risk. Notably, at a cut-off value of 8.5 m/s, PWV showed relatively good ability to discriminate individuals at high versus moderate risk according to SCORE-2 risk (AUC 0.77, specificity 71%). Similarly, at a cut-off value of 7.6, PWV discriminated well between low versus moderate risk individuals according to FRS (AUC 0.77, specificity 77%).

These results, particularly when compared to previous negative findings obtained in a different population (AUC 0.61 in the high CV risk stratification, 0.51 in the moderate CV risk stratification) [8], support the hypothesis that PWV assessment may aid in identifying subjects with a high likelihood of high CV risk. This, in turn, could help in guiding selection of candidates for further diagnostic tests, such as blood glucose and cholesterol measurement.

However, several factors limit the generalizability of these findings. Notably, the authors did not compare PWV's ability to discriminate between individuals at different CV risk levels with that of systolic or diastolic BP, leaving unanswered the question about which one of these two measures, BP or PWV, or their combination, provides the best CV risk discrimination. The study also does not assess whether PWV has additive prognostic value beyond traditional CV risk stratification, in predicting outcomes, as its observational design lacks a longitudinal component. Moreover, the number of diabetic patients is unreported, and it is not explicated if a different risk equation has been applied to this sub-population.

The Tel-o-Graph device calculates a single-point measure of PWV through a proprietary algorithm based on the characteristics of the pulse waveform measured by the cuff, BP values, and age. Recent findings indicate that PWV values provided by devices that use single-site brachial pressure waveforms are primarily influenced by age and BP rather than serving as a reliable incremental measure of arterial stiffness [9].

Turkey is classified as a nation at high CV risk. The age- and sex-standardized CV mortality is about 200 per 100 000 person/year [6]. Non-native risk prediction model taken from other populations with different CV risk factor prevalences could significantly underestimate the effective absolute CV risk. However, FRS demonstrated fair discrimination in CVD risk prediction either in Asian people [10] and in European Mediterranean areas [11], whereas the SCORE-2 allows calibration based on the absolute CV risk category for each European country, included Turkey.

During the last decade many nations, such as Turkey, made fundamental reforms in the health system to improve the treatment of risk factors to prevent CVD. In this context, the simple adoption of BP monitors integrated with automated PWV measurement in primary healthcare services such as the family medicine clinics, could help in contrasting the expected increase in CV events and aging of the population. It is however essential to exercise caution when interpreting the results derived from observational studies with relatively small sample sizes. Further research is needed to confirm, reinforce, and expand upon the seminal hypothesis proposed by the authors in this current study.