Arterial Stiffness and Cardiometabolic-Based Chronic Disease: The Kardiovize Study

Iuliia Pavlovska1, Jeffrey I Mechanick2, Geraldo A Maranhao Neto3

  • 1International Clinical Research Centre (ICRC), St Anne's University Hospital Brno (FNUSA), Czech Republic; Department of Public Health, Faculty of Medicine, Masaryk University, Brno, Czech Republic.

Insights

The adiposity-based chronic disease (ABCD) and dysglycemia-based chronic disease (DBCD) models better identify arterial stiffness (ArSt) than traditional methods. These models offer improved detection of cardiovascular risk factors like high arterial stiffness.

Area of Science:

  • Cardiology
  • Endocrinology
  • Public Health

Background:

  • Arterial stiffness (ArSt) is a key predictor of cardiovascular events.
  • A cardiometabolic disease model integrates adiposity-based chronic disease (ABCD) and dysglycemia-based chronic disease (DBCD).

Purpose of the Study:

  • To compare the effectiveness of ABCD and DBCD models versus traditional classifiers in detecting high ArSt using the cardio-ankle vascular index (CAVI).

Main Methods:

  • Evaluated 2070 adults (25-64 years) from a population-based sample, excluding type 1 diabetes.
  • Defined ABCD and DBCD criteria and stratified ArSt risk using American Association of Clinical Endocrinologists guidelines.

Main Results:

  • Highest high CAVI prevalence observed in stage 2 ABCD (18.5%) and stage 4 DBCD (31.8%).
  • Stage 2 ABCD and all DBCD stages significantly increased high CAVI risk in univariate analysis.
  • Obesity (BMI ≥30 kg/m²), while significant, explained only 0.3% of CAVI variability after adjustments.

Conclusions:

  • ABCD and DBCD models demonstrated superior performance in detecting ArSt compared to traditional classifiers.
  • The independent association of these models with ArSt was not significant after adjusting for age and gender.
  • The complex, multifactorial relationship of CAVI with ABCD and DBCD, potentially mediated by insulin resistance, warrants further investigation.
Abstract

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