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A Population-Based Scoring System to Assess the Impact of Individual Risk Factors on Vascular Health
Vanessa Gagliano1, David Gehrig2, Rosaria Del Giorno2,3
1Department of Internal Medicine, Clinical Research Unit, Regional Hospital of Bellinzona and Valli, Ente Ospedaliero Cantonale, Bellinzona, Switzerland.
Insights
Arterial stiffness, measured by pulse wave velocity (PWV) and augmentation index (AI), is impacted by cardiovascular risk factors. This study provides reference values and a risk score to assess their effect on vascular aging.
Area of Science:
- Cardiovascular Health
- Vascular Aging
- Biomarkers of Arterial Stiffness
Background:
- Arterial stiffness is a key indicator of vascular health, influenced by aging and cardiovascular risk factors.
- Pulse wave velocity (PWV) and augmentation index (AI) are established measures for assessing arterial stiffness.
- Understanding the impact of individual risk factors on vascular aging is crucial for preventative strategies.
Purpose of the Study:
- To assess the impact of individual cardiovascular risk factors on vascular health.
- To evaluate the distribution of PWV and AI in adults without modifiable cardiovascular risk factors.
- To analyze the role of risk factors in accelerating vascular aging using nomograms and risk scores.
Main Methods:
- Secondary analysis of a Swiss population-based study (2017-2018) with 1097 participants.
- Categorization into groups with and without specific cardiovascular risk factors (smoking, diabetes, CVD, CKD, hypercholesterolemia, hypertension, metabolic syndrome).
- Assessment of PWV and AI using tonometric and oscillometric devices; logistic regression and nomogram development for risk stratification.
Main Results:
- Hypertension, diabetes, and obesity were associated with significantly higher PWV values (p < 0.001).
- Univariate analysis identified diabetes, CVDs, hypercholesterolemia, and hypertension as predictors of higher PWV.
- Multivariate analysis highlighted CVDs, antihyperlipidemic treatment, hypertension, and increased BMI as significant predictors of arterial stiffness.
Conclusions:
- The study establishes reference values for PWV and AI in individuals without major cardiovascular risk factors.
- Developed nomograms provide a risk score for stratifying the impact of individual risk factors on vascular health.
- Hypertension and diabetes are significant contributors to increased arterial stiffness and potentially accelerated vascular aging.
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.
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