Cardiovascular risk assessment tools in Asia

Yuqing Zhang1, Huanhuan Miao1, Yook-Chin Chia2,3

  • 1Department of Cardiology, Fu Wai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Insights

Cardiovascular disease (CVD) risk assessment tools developed in Western countries need recalibration for Asian populations due to differing risk factors and CVD profiles. Developing new or adapting existing models with local data is crucial for accurate CVD risk prediction in Asia.

Area of Science:

  • Public Health
  • Epidemiology
  • Cardiology

Background:

  • Cardiovascular disease (CVD) poses a significant global health burden, particularly in Asia.
  • Existing CVD risk assessment tools are predominantly Western-based.
  • Asian populations exhibit distinct risk factor profiles and CVD patterns compared to Western populations.

Purpose of the Study:

  • To highlight the limitations of Western CVD risk assessment tools in Asian populations.
  • To emphasize the need for culturally specific or adapted risk models.
  • To guide the development and application of appropriate CVD risk assessment strategies in Asia.

Main Methods:

  • Review of existing literature on CVD risk assessment tools.
  • Analysis of epidemiological data comparing Western and Asian populations.
  • Discussion of the implications of differing risk factor prevalence and CVD profiles.

Main Results:

  • Western CVD risk assessment tools show limitations when applied to Asian populations due to differences in hypertension, cholesterol levels, metabolic disorders, and stroke-to-coronary heart disease ratios.
  • Existing Asian-specific models like China-PAR and JALS score are validated for national use.
  • Many Asian regions currently utilize non-recalibrated established models.

Conclusions:

  • Recalibration or development of new CVD risk assessment tools is essential for Asian populations.
  • Hypertension requires greater emphasis in Asian CVD risk assessment due to higher stroke incidence.
  • Adapting existing models with local epidemiological data is a viable alternative where resources are limited.

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