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Cardiovascular Risk Calculators and their Applicability to South Asians
Manish Bansal1, Shraddha Ranjan2, Ravi R Kasliwal1
1Clinical and Preventive Cardiology, Medanta- The Medicity, Gurgaon, Haryana, India.
Insights
Developing accurate cardiovascular disease (CVD) risk scores for South Asians is crucial due to their higher risk. Current scores show inconsistencies, highlighting the need for tailored risk assessment tools.
Area of Science:
- Cardiology
- Public Health
- Epidemiology
Background:
- Cardiovascular disease (CVD) primary prevention relies on accurate risk estimation.
- South Asians exhibit significantly higher CVD risk compared to Western populations.
- Existing CVD risk scores are not validated for South Asian populations.
Purpose of the Study:
- To review available cardiovascular disease (CVD) risk scores.
- To assess their applicability and accuracy in South Asian populations.
- To discuss challenges and potential solutions for CVD risk assessment in South Asians.
Main Methods:
- A narrative review was conducted.
- Literature search performed using PubMed and Google search engines.
Main Results:
- Currently available CVD risk scores have limitations and inconsistent accuracy in South Asians.
- British risk scores (e.g., QRISK) may offer better accuracy due to the inclusion of South Asians in their development.
- Lack of prospective studies prevents definitive conclusions on risk score performance.
Conclusions:
- There is a critical need for large, prospective databases of South Asians to develop validated CVD risk scores.
- Such databases will facilitate the development of personalized CVD risk assessment and management strategies.
- Machine-learning approaches can enhance CVD risk prediction and personalized solutions for South Asian populations.
Background:
Estimation of absolute cardiovascular disease (CVD) risk and tailoring therapies according to the estimated risk is a fundamental concept in the primary prevention of CVD is assessed in this study. Numerous CVD risk scores are currently available for use in various populations but unfortunately, none exist for South Asians who have much higher CVD risk as compared to their western counterparts.
Methods:
A literature search was done using PubMed and Google search engines to prepare a narrative review on this topic.
Results:
Various currently available CVD risk scores and their pros and cons are summarized. The studies performed in native as well as migrant South Asians evaluating the accuracy of these risk scores for estimation of CVD risk are also summarized. The findings of these studies have generally been inconsistent, but it appears that the British risk scores (e.g. QRISK versions) may be more accurate because of inclusion of migrant South Asians in the derivation of these risk scores. However, the lack of any prospective study precludes our ability to draw any firm conclusions. Finally, the potential solution to these challenges, including the role of recalibration and subclinical atherosclerosis imaging, is also discussed.
Conclusion:
This review highlights the need to develop large, representative, prospectively followed databases of South Asians providing information on various CVD risk factors and their contribution to incident CVD. Such databases will not only allow the development of validated CVD risk scores for South Asians but will also enable application of machine-learning approaches to provide personalized solutions to CVD risk assessment and management in these populations.
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