A Population-Based Scoring System to Assess the Impact of Individual Risk Factors on Vascular Health

Abstract

Arterial stiffness is an indicator of vascular health, influenced by both pathological conditions and physiological determinants, noticeably age. Augmentation index (AI) and pulse wave velocity (PWV) are used among others to assess arterial stiffness. Several risk factors may contribute to pathologically increase arterial stiffness and produce early vascular aging. Our study aims to assess the impact of individual risk factors on vascular health, evaluating the distribution of PWV and AI values in a cohort of adult people without modifiable cardiovascular risk factors while analyzing their role in accelerating vascular ageing. We performed a secondary analysis of a Swiss population-based research project, which took place in 2017 and 2018. Of the 1202 participants originally enrolled, 1097 were included in the final sample. The population was divided into without (n=388) and with risk factors (n=709), based on the presence of the following: smoking, diabetes, previous cardiovascular disease (CVD), chronic kidney disease stage 3 or more, LDL cholesterol ≥ 4.11 or treatment with hypolipidemic drugs, hypertension or treatment with antihypertensive drugs, and metabolic syndrome. Tonometric and oscillometric devices were employed to assess PWV, and the 75th percentiles of PWV and AI in the population without risk factors were calculated to identify cut-offs for the logistic regression analysis. We developed nomograms by assigning a numerical score to each independent prognostic factor; the total score estimating the probability of PWVs and AIs being over the defined cut-offs. Patients with hypertension, diabetes, and obesity showed higher PWV values (p < 0.001). In the univariate logistic regression, factors predictive for higher PWV values were diabetes, CVDs, hypercholesterolemia, and hypertension, while CVDs, antihyperlipidemic treatment, hypertension, and increased BMI were predictive in the multivariate logistic regression. Smoking did not significantly influence arterial stiffness parameters. The present study provides reference values for PWV and AI in subjects without modifiable cardiovascular risk factors and, through nomograms, a risk score stratification to assess the impact of individual risk factors on vascular health.

Figure 1.

Flowchart showing the selection procedure of the participants.

Figure 2.

Graphical distribution of cf-PWV (A), br-PWV (B), and AI (C) according to age.

Figure 3.

Nomograms assign numerical scores to each independent prognostic factor. A higher total score is associated with a higher probability (prob) of having cf-PWVs (A), br-PWVs (B) or AIs (C) above the 75^th percentile.