reviewed by Professor Maja-Lisa Løchen

The past issue of the European Journal of Preventive Cardiology highlights an impressive number of efforts in expanding the applicability and scope of the existing guidelines-approved cardiovascular disease (CVD) risk-scores to multiple scenarios. These risk scores are commonly used in clinical practice, as the cornerstone of prevention and recent research has offered a rich and creative palette of options. Those include predictive algorithms in the young ages versus old ages beyond 75 years, extension of risk-time horizons from 10-years to 5-years or lifetime spans, inclusion of genetic information to commonly employed clinical dimensions, diversification of risk prediction by modifying risk factors such as a history of diabetes, and not least, the transferability of CVD-risk calculators from European to Asian, Latino-American and other populations.

The cardiology preventive community is clearly preoccupied with being able to detect CVD risk as early as possible, and intervene optimally by starting, intensifying or stopping prescribing, and ultimtaley bend the likelihood of having CVD events in the young ages, or address CVD needs best in the elderly. Various studies have suggested that additional information to classic and easily obtainable health variables, may somewhat improve risk-discrimination. For instance, adding information on Apo-B, Lp(a), CystatinC, HbA1c, repeat plaque visualisation, measures of valvular calcification, echocardiography of the heart, ethnicity, or orthostatic hypertension, just to name a few, seem to have additional informative value for improving the threshold for identification of low or high-risk individuals. However, such enhanced models need external validation, time and additional resources, not only for risk communication to patients in a manner that should otherwise be easily understood, but also implications for elaborate testing in primary care settings. As the PURE study highlighted in a multi-centric, multi-score comparable analysis of six tools, the INTERHEART non-laboratory CVD risk-prediction tools remains a good and reliable option in low-resource, remote or rural settings where advanced hospitals and laboratories are non-existent.

However, what appears common to all these efforts for refining CVD risk prediction, is that these emerging models largely classify the same group of individuals as high risk, but early detection with different timespans would result in a larger proportion of individuals meeting the commonly-agreed treatment criteria, due to systematically higher predicted CVD risk over different time-periods.

Note: The content of this article reflects the personal opinion of the author/s and is not necessarily the official position of the European Society of Cardiology.

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