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Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

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Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
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Visceral Adiposity Thresholds for Cardiovascular Risk Stratification: A Simplified Biomarker-Driven Model.

Tangmeng Guo1,2,3, Ping He1,2, Weilin Lu1,2

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This summary is machine-generated.

Visceral adipose tissue (VAT) volume thresholds for cardiovascular disease (CVD) risk vary by sex and ethnicity. A simple biomarker model accurately predicts VAT volume, aiding in cardiometabolic risk assessment.

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Area of Science:

  • Cardiology
  • Metabolic Health
  • Body Composition Analysis

Background:

  • Visceral adipose tissue (VAT) volume is a key indicator of cardiometabolic risk.
  • Population-specific VAT thresholds and predictive tools for risk stratification are currently lacking.
  • Accurate assessment of VAT is crucial for identifying individuals at higher risk.

Purpose of the Study:

  • To establish sex- and ethnicity-specific VAT volume thresholds for cardiovascular disease (CVD) risk stratification.
  • To develop and validate a simplified, accessible predictive model for VAT volume.
  • To investigate the relationship between VAT volume, metabolic dysregulation, and CVD prevalence.

Main Methods:

  • Analysis of dual-energy x-ray absorptiometry (DXA)-derived VAT volume from US National Health and Nutrition Examination Survey (NHANES) data.
  • Utilized multivariable regression for threshold effect and sex/ethnicity interaction analysis.
  • Employed LASSO regularization and ROC analyses to develop a predictive model.

Main Results:

  • A VAT volume threshold of 327.0 cm³ was identified for CVD risk stratification.
  • Significant sex differences in risk thresholds were observed (males: 387.5 cm³, females: 312.0 cm³).
  • Ethnicity-specific thresholds were identified, with risk escalating differently across racial/ethnic groups.
  • A tri-biomarker model (waist circumference, triglycerides, apolipoprotein B) demonstrated comparable accuracy to DXA-based VAT quantification (AUC = 0.821 vs. 0.819).

Conclusions:

  • The study provides the first sex- and ethnicity-specific VAT volume thresholds for CVD risk stratification.
  • A cost-effective, clinically actionable tri-biomarker model offers a practical alternative for visceral adiposity screening.
  • These findings enhance the ability to identify and manage cardiometabolic risk associated with visceral adiposity.