Functional versus morphological assessment of vascular age in patients with coronary heart disease

Differences between SCORE, Framingham Risk Score, and Estimated Pulse Wave Velocity-Based Vascular Age Calculation Methods Based on Data from the Three Generations Health Program in Hungary

Early vascular ageing contributes to cardiovascular (CV) morbidity and mortality. There are different possibilities to calculate vascular age including methods based on CV risk scores, but different methods might identify different subjects with early vascular ageing. We aimed to compare SCORE and Framingham Risk Score (FRS)-based vascular age calculation methods on subjects that were involved in a national screening program in Hungary. We also aimed to compare the distribution of subjects identified with early vascular ageing based on estimated pulse wave velocity (ePWV). The Three Generations for Health program focuses on the development of primary health care in Hungary. One of the key elements of the program is the identification of risk factors of CV diseases. Vascular ages based on the SCORE and FRS were calculated based on previous publications and were compared with chronological age and with each other in the total population and in patients with hypertension or diabetes. ePWV was calculated based on a method published previously. Supernormal, normal, and early vascular ageing were defined as <10%, 10-90%, and >90% ePWV values for the participants. In total, 99,231 subjects were involved in the study, and among them, 49,191 patients had hypertension (HT) and 15,921 patients had diabetes (DM). The chronological age of the total population was 54.0 (48.0-60.0) years, while the SCORE and FRS vascular ages were 59.0 (51.0-66.0) and 64.0 (51-80) years, respectively. In the HT patients, the chronological, SCORE, and FRS vascular ages were 57.0 (51.0-62.0), 63.0 (56.0-68.0), and 79.0 (64.0-80.0) years, respectively. In the DM patients, the chronological, SCORE, and FRS vascular ages were 58.0 (52.0-62.0), 63.0 (56.0-68.0), and 80.0 (76.0-80.0) years, respectively. Based on ePWV, the FRS identified patients with an elevated vascular age with high sensitivity (97.3%), while in the case of the SCORE, the sensitivity was much lower (13.3%). In conclusion, different vascular age calculation methods can provide different vascular age results in a population-based cohort. The importance of this finding for the implementation in CV preventive strategies requires further studies.

Comparison of Functional and Morphological Estimates of Vascular Age

BACKGROUND/AIM

Vascular age (VA) is an emerging metric in preventive cardiovascular (CV) medicine. VA can be derived from morphological parameters such as carotid intima-media thickness (CIMT), or functional parameters such as pulse wave analysis (PWA), which celebrates its 100th birthday. This study aimed to investigate whether the results of both approaches are comparable.

PATIENTS AND METHODS

On the occasion of the double 100th anniversary of PWA and the Mannheim Clinic, 100 volunteers underwent a) bilateral CIMT assessment using high-resolution ultrasound and b) oscillometric PWA at the brachial forearm site. The respective VAs were calculated using previously published equations.

RESULTS

Median age of the participants was 53.6 years (range=39.8-62.6 years), and 56% were female. Median CIMT was 632.5 μm (range=548.8-730.0 μm). Median PWA-derived VA was 55.3 years (36.5-70.5 years). Different values were obtained for CIMT-derived VA, depending on the reference cohort used as calculation basis, ranging from median 43.7 (26.2-59.5 years) to median 64.0 years (43.5-82.1 years). In 46% of the participants divergent VAs were found, that is, the calculated age was higher according to one method and lower according to the other. Correlation analysis revealed a strong dependence of VA (both PWA- and CIMT-derived) and chronological age, as well as an increase in CV risk factors and the detection of plaques with age.

CONCLUSION

Different approaches for estimating VA are not comparable and often produce contradictory results. The current methods and their validity must be critically assessed if they are not standardized.

Vascular Age, Metabolic Panel, Cardiovascular Risk and Inflammaging in Patients With Rheumatoid Arthritis Compared With Patients With Osteoarthritis

Introduction

The risk of cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA) is 1.5–2 times higher than the general population. The fundamental risk factor for CVD is age, related to alterations at the arterial level. The aim of the study was to compare vascular age (VA) in RA patients under a strict treat-to-target (T2T) strategy with Osteoarthritis (OA) patients without strict follow up and to assess the influence of inflammaging (chronic, sterile, low-grade inflammation related to aging) and metabolic markers on VA.

Materials and Methods

This was an analytical cross-sectional study. Patients with RA (under a strict a T2T strategy) and OA patients without strict clinical follow-up were included. Patients with a history of uncontrolled hypertension, CVD, and/or current smoking were excluded. Sociodemographic, physical activity, and toxic exposure data were obtained. Waist-hip ratio and body mass index (BMI) were measured. DAS-28 (RA) and inflammatory markers, lipid profile, and glycaemia were analyzed. Pulse wave velocity (PWV) was measured (oscillometric method, Arteriograph-TensioMed®). VA was calculated based on PWV. Eleven components of inflammaging [six interleukins, three metalloproteinases (MMP), and two tissue inhibitors of metalloproteinases (TIMP)] were evaluated (Luminex® system). Univariate and bivariate analyzes (Mann Whitney U and chi-square) and correlations (Spearmans Rho) were done to compare the two groups.

Results

A total of 106 patients (74% women) were included, 52/RA and 54/OA. The mean age was 57 (Interquartile range - IQR 9 years). The BMI, waist circumference, and weight were higher in patients with OA (p &lt; 0.001). RA patients had low disease activity (DAS-28-CRP). There were no differences in VA, inflammaging nor in PWV between the two groups. VA had a positive, but weak correlation, with age and LDL. In group of RA, VA was higher in those who did not receive methotrexate (p = 0.013). LDL levels correlated with MMP1, TIMP1, and TIMP2.

Conclusions

When comparing RA patients with low levels of disease activity with OA patients with poor metabolic control, there are no differences in VA. Furthermore, methotrexate also influences VA in RA patients. This shows that implemented therapies may have an impact on not only the inflammatory state of the joint but also CVD risk.