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Abstract: SA-PO521

Cardiovascular Risk Prediction Improvement Using Algorithm- or Formula-Based Pulse Wave Velocity: Analysis of CARTaGENE

Session Information

Category: Hypertension and CVD

  • 1602 Hypertension and CVD: Clinical


  • Desbiens, Louis-Charles, Universite de Montreal, Montreal, Quebec, Canada
  • Nadeau-Fredette, Annie-Claire, Universite de Montreal, Montreal, Quebec, Canada
  • Hametner, Bernhard, Austrian Institute of Technology GmbH, Wien, Wien, Austria
  • Madore, Francois, Universite de Montreal, Montreal, Quebec, Canada
  • Agharazii, Mohsen, Centre Hospitalier Universitaire de Quebec-Universite Laval, Quebec, Quebec, Canada
  • Goupil, Remi, Universite de Montreal, Montreal, Quebec, Canada

Carotid-femoral pulse wave velocity (PWV) is the gold-standard measurement for aortic stiffness and a well-established surrogate marker for cardiovascular disease. Faster and less resource-intensive methods to estimate PWV (using either formulas or integrated pulse wave analysis algorithms) have been developed but their incremental predictive value for cardiovascular outcomes remains unclear.


We studied individuals aged between 40 and 69 from the population based CARTaGENE cohort (Quebec, Canada). Baseline PWV was assessed using a previously described estimation formula (formula- based PWV, or f-PWV; using age, sex, and systolic blood pressure) or estimated with the ARCSolver algorithm from central waveform characteristics obtained with the SphygmoCor device (algorithm-based PWV, or a-PWV). Major adverse cardiovascular events (MACE: cardiovascular mortality, non- fatal stroke, non-fatal myocardial infarction) during a 10-year follow-up were obtained from medico-administrative databases. Cox proportional hazards models were employed to obtain associations between PWV and MACE after adjustment for existing cardiovascular risk prediction scores (ASCVD [from revised pooled cohort equations], SCORE-2).


17,548 individuals were included and 2,263 experienced a MACE during follow-up. Mean PWV values at baseline were 8.4 ± 1.4 m/s (f-PWV) and 7.9 ± 1.3 m/s (a-PWV). Both f-PWV (HR= 1.52, 95% CI [1.47-1.58]) and a-PWV (HR=1.60 [1.54-1.66]) were predictive of MACE in unadjusted models. The association between a-PWV and MACE remained significant after adjustment for ASCVD (HR= 1.14 [1.08-1.20]) and but not after adjustment for SCORE-2 (HR= 1.06 [1.00-1.13]). In contrast, f-PWV was not associated with increased MACE after adjustment for either prediction score (HR= 1.02 [0.97-1.08] for ASCVD; HR= 0.95 [0.89-1.00] for SCORE-2). Similar trends were observed after stratification for tertiles of baseline cardiovascular risk.


Algorithm-based PWV, but not formula-based PWV, improves cardiovascular prediction beyond what is achievable with recognized prediction tools.