Comparison of laboratory-based and non-laboratory-based WHO cardiovascular disease risk charts: a population-based

Fatemeh Rezaei1, Mozhgan Seif2, Abdullah Gandomkar3

  • 1Department of Social Medicine, Jahrom University of Medical Sciences, Jahrom, Iran.

Insights

A non-laboratory-based Cardiovascular Disease (CVD) risk chart is a viable alternative to laboratory testing, especially in resource-limited settings. This simple, inexpensive model shows substantial agreement with WHO laboratory-based charts for CVD risk prediction.

Area of Science:

  • Cardiology
  • Public Health
  • Epidemiology

Background:

  • Cardiovascular Disease (CVD) risk assessment is crucial for preventive interventions in high-risk populations.
  • Laboratory testing for CVD risk may be inaccessible in resource-limited countries.
  • This study compares WHO laboratory-based and non-laboratory-based CVD risk prediction models.

Purpose of the Study:

  • To compare the agreement between laboratory-based and non-laboratory-based WHO risk charts for Cardiovascular Disease (CVD).
  • To assess the feasibility of using non-laboratory-based models in resource-constrained environments.

Main Methods:

  • Utilized baseline data from 8138 participants in the Pars cohort study without prior CVD or stroke history.
  • Applied the updated 2019 WHO model to calculate 10-year fatal and non-fatal CVD risks.
  • Compared laboratory-based (age, sex, smoking, diabetes, SBP, total cholesterol) and non-laboratory-based (age, sex, smoking, SBP, BMI) models using kappa statistics and correlation coefficients.

Main Results:

  • Strong correlation coefficients (r=0.84-0.93) were observed between the models across different sex and age groups.
  • Risk classification agreement was substantial for males <60 and all individuals ≥60 years (kappa=0.65-0.79).
  • Moderate agreement was found for females <60 years (kappa=0.46), with similar overall risk distributions between models.

Conclusions:

  • The non-laboratory-based CVD risk prediction model is simple, inexpensive, and non-invasive.
  • It classifies individuals' CVD risk almost identically to the laboratory-based model.
  • These models can be used interchangeably in countries with limited resources for effective CVD risk assessment.
Abstract

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