Key result
A 1 standard deviation increment in the Vascular Aging Index was significantly associated with an increased risk of composite cardiovascular disease events (HR 1.45; 95% CI 1.26-1.68; P<.001).
Why the study?
Although arterial morphology and function can be measured directly using established methods, the predictive power of combining aortic pulse wave velocity and carotid intima-media thickness into a Vascular Aging Index remained to be evaluated.
Does a Vascular Aging Index combining aPWV and cIMT improve prediction of cardiovascular events and total mortality in an elderly urban population?
Cohort (n=2,718)
Does a Vascular Aging Index combining aPWV and cIMT improve prediction of cardiovascular events and total mortality in an elderly urban population?
Hazard Ratio: 1.45 (95% CI 1.26–1.68)
p-value: p=<.001
A combined Vascular Aging Index using aPWV and cIMT significantly improves the prediction of cardiovascular events beyond conventional risk factors, primarily by correctly down-adjusting risk for noncases.
VAI may refine CV risk stratification in elderly cohorts; leaves open its incremental utility beyond standard scores in prospective trials.
The morphology and function of the arteries can be directly measured using different established methods. This prospective cohort study aimed to translate 2 of these, aortic pulse wave velocity (aPWV) and carotid intima–media thickness (cIMT), into a combined Vascular Aging Index (VAI) and then evaluate the predictive power of aPWV, cIMT, and VAI. Patients (n = 2718) were included from the cardiovascular arm of the Malmö Diet and Cancer Study (median age 71.9 years, 62.2% females). Total follow-up time was 16 448 person-years and a composite cardiovascular disease (CVD) end point was used. Cox regressions yielded adjusted hazard ratios (95% confidence interval) per 1 standard deviation increment of log e aPWV, log e cIMT, and log e VAI of 1.25 (1.08-1.45, P = .003), 1.27 (1.13-1.44, P < .001), and 1.45 (1.26-1.68, P < .001), respectively. The C-statistics increased from 0.714 to 0.734 when adding aPWV and cIMT to a model of conventional risk factors. Net Reclassification Index also showed a significant ( P < .001) improvement for the classification of event-free patients and no change for patients with events. A VAI based on aPWV and cIMT had a good predictive performance. Used together, aPWV and cIMT incrementally and significantly improve the prediction of CVD events by correctly down-adjusting the predicted risk for noncases.
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Wadström et al. (2019) conducted a cohort in Cardiovascular disease (n=2,718). Vascular Aging Index (VAI) was evaluated on Composite cardiovascular disease (CVD) end point (HR 1.45, 95% CI 1.26-1.68, p=<.001). A 1 standard deviation increment in the Vascular Aging Index was significantly associated with an increased risk of composite cardiovascular disease events (HR 1.45; 95% CI 1.26-1.68; P<.001).
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