Prediction of Cardiovascular Events by Pulse Waveform Parameters: Analysis of CARTaGENE

Louis-Charles Desbiens1, Catherine Fortier1,2, Annie-Claire Nadeau-Fredette1,3

  • 1Department of Medicine Université de Montréal Montreal Canada.

Insights

Aortic waveform parameters like augmentation index offer slight improvements in predicting major adverse cardiovascular events (MACE), particularly for individuals at low cardiovascular risk. Some parameters are independently associated with MACEs.

Area of Science:

  • Cardiovascular Physiology
  • Biomedical Engineering
  • Epidemiology

Background:

  • Aortic wave reflection parameters offer insights into cardiovascular health.
  • Their predictive value for cardiovascular events is not well established.
  • This study investigates their role in predicting major adverse atherosclerotic events (MACE).

Purpose of the Study:

  • To assess the association between aortic waveform parameters and MACE.
  • To evaluate the incremental predictive value of these parameters over the atherosclerotic cardiovascular disease (ASCVD) score.
  • To identify specific parameters that enhance cardiovascular risk prediction.

Main Methods:

  • Analysis of participants aged 40-69 from the CARTaGENE cohort.
  • Derivation of pulse wave analysis and wave separation analysis parameters from radial artery tonometry.
  • Cox models and reclassification metrics used to assess MACE prediction.

Main Results:

  • Central pulse pressure, forward pressure, and backward pressure were associated with MACE.
  • Augmentation index and reflection magnitude showed minimal but statistically significant improvement in MACE prediction when added to the ASCVD score.
  • Prediction enhancement was most notable in individuals with low baseline ASCVD scores.

Conclusions:

  • Certain aortic waveform parameters are independently linked to MACE in a population-based setting.
  • Augmentation index and reflection magnitude offer a slight enhancement to cardiovascular risk prediction, especially for low-risk individuals.
  • These findings suggest a potential role for advanced waveform analysis in refining cardiovascular risk stratification.

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