1.3 PREDICTION OF CARDIOVASCULAR MORTALITY AND MORBIDITY IN THE MALMö DIET-CANCER COHORT FOR THE IDENTIFICATION OF HEALTHY VASCULAR AGEING, USING MARKERS OF VASCULAR STATUS

• Main Authors: Benjamin Nilsson Wadström, Peter Nilsson, Abd Al-Hakim Fatehali, Gunnar Engstrom
• Format: Article
• Language: English
• Published: Atlantis Press 2018-12-01
• Series: Artery Research
• Online Access: https://www.atlantis-press.com/article/125929977/view

Background: This study aims to translate two arterial measurements, aortic Pulse Wave Velocity (aPWV) and carotid Intima-Media Thickness (cIMT), into a combined Vascular Ageing Index (VAI), to evaluate the predictive power of VAI and utilize it to identify a sub-group with Healthy Vascular Ageing (HVA). Methods: In all, 2718 subjects were included from the CV arm of the Malmö Diet Cancer study (median age 72 years, 62.2% females). Median follow-up for CV events (N = 269) was 6.5 years. VAI was created by a function that combined aPWV and cIMT. Cox regressions for aPWV, cIMT and VAI, adjusted for conventional CV risk factors, were carried out. aPWV and cIMT were mutually adjusted for while VAI was analyzed separately. Model improvements for a model of conventional CV risk factors were assessed using Harrell’s c-statistic and continuous Net Reclassification Index (NRI). Results: Cox regression Results: (fully adjusted model): 1 SD of log-(aPWV), HR: 1.22 (95% CI: 1.03–1.42, P = 0.010), 1 SD of log (cIMT), HR: 1.29 (95% CI: 1.13–1.47, P < 0.001), 1 SD of log-VAI, HR: 1.43 (95% CI: 1.22–1.68, P < 0.001) (Figure 1). C-statistics: 0.715 (conventional risk factor model), 0.721 (+aPWV), 0.734 (+aPWV and cIMT) and 0.732 (+VAI). NRI showed a significant (P < 0.001) improvement for classification of event-free subjects when adding aPWV and cIMT or VAI. Conclusion: VAI added marginally to prediction of CV events. However, the classification of subjects who remained free from CV events was significantly improved.