Value and Limitations of Existing Scores for the Assessment of Cardiovascular Risk. A Review for Clinicians

Cardiology Department, Adelaide Meath Hospital, Tallaght, Dublin, Ireland.
Journal of the American College of Cardiology (Impact Factor: 16.5). 09/2009; 54(14):1209-27. DOI: 10.1016/j.jacc.2009.07.020
Source: PubMed


Atherosclerotic cardiovascular diseases (CVDs) are the biggest causes of death worldwide. In most people, CVD is the product of a number of causal risk factors. Several seemingly modest risk factors may, in combination, result in a much higher risk than an impressively raised single factor. For this reason, risk estimation systems have been developed to assist clinicians to assess the effects of risk factor combinations in planning management strategies. In this article, the performances of the major risk estimation systems are reviewed. Most perform usably well in populations that are similar to the one used to derive the system, and in other populations if calibrated to allow for different CVD mortality rates and different risk factor distributions. The effect of adding "new" risk factors to age, sex, smoking, lipid status, and blood pressure is usually small, but may help to appropriately reclassify some of those patients who are close to a treatment threshold to a more correct "treat/do not treat" category. Risk estimation in the young and old needs more research. Quantification of the hoped-for benefits of the multiple risk estimation approach in terms of improved outcomes is still needed. But, it is likely that the widespread use of such an approach will help to address the issues of both undertreatment and overtreatment.

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Available from: Marie Therese Cooney, Mar 01, 2014
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    • "org/10.1016/j.dib.2016.01.002i As published scoring systems estimate 10-year risk, risk estimates were recalibrated for 7 years follow up to allow for comparison within the observed follow-up period [3] [4] [5] [6]. Recalibrated risk categories were as following: Low risk o5.25% and high-risk Z5.25%. "
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    ABSTRACT: The current guidelines recommend the new risk score, Atherosclerotic Cardiovascular Disease score (ASCVD), to assess an individual׳s risk of future cardiovascular disease (CVD) events. No data exist on the predictive utility of ASCVD score with the incremental value of coronary artery calcium scoring (CACS) across ethnicities and gender. Multi-Ethnic Study of Atherosclerosis (MESA) is a population based study (n=6814) of White (38%), Black (28%), Chinese (22%) and Hispanic (12%) subjects, aged 45–84 years, free from clinical cardiovascular disease. We performed a post-hoc analysis of 6742 participants (mean age 62, 53% female) from the MESA cohort. We evaluated the predictive accuracy for the ASCVD score for each participant in accord with the American College of Cardiology/American Heart Association guidelines using pooled cohort equations. Similar to the publication by Fudim et al. “The Metabolic Syndrome, Coronary Artery Calcium Score and Cardiovascular Risk Reclassification” [1] the analytic properties of models incorporating the ASCVD score with and without CACS were compared for cardiovascular disease CVD prediction. Here the analysis focused on ASCVD score (with and without CACS) performance across gender and ethnicities.
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    • "cigarette smoking status and other variables; see Cooney et al., 2009 for review). In the psychosis sample, among those who currently smoked tobacco, the number of cigarettes or cigar or pipe equivalents smoked daily during the previous four weeks was recorded. "
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    ABSTRACT: Antipsychotic drug treatment alters status on key risk factors for cardiovascular disease. The aim of this study was to test whether cardiovascular risk factor associations differ in adults with psychosis and adults from the general community. Data were analysed for those aged 25-64 years from a nationally representative psychosis sample (n = 1,457) and a national comparator sample (n = 8,866). The Pearson correlation coefficient was used to estimate the association among tobacco use, body mass index, waist circumference, diastolic and systolic blood pressure and fasting total-, LDL- and HDL-cholesterol, triglycerides and plasma glucose. The robust Levene test was used to test for sample differences in variance. Correlations among cardiovascular risk indicators and between cardiovascular risk indicators and age were often significantly weaker in those with psychosis than in those from the national comparator sample. This was not due to a reduction in variance within the psychosis sample. Risk prediction that synthesizes multivariate risk indicator data needs to be connected to verified cardiovascular morbidity and mortality in those with psychosis to determine if standard risk calculators adequately discriminate those at high, medium and low future risk of cardiovascular morbidity and mortality. Until then the clinical implications of low or absent correlations among cardiovascular risk indicators and their low or absent association with increasing age is unclear but may indicate that risk equations commonly used in the general population may not be applicable for those with treated psychosis. © The Royal Australian and New Zealand College of Psychiatrists 2015.
    Full-text · Article · Jan 2015 · Australian and New Zealand Journal of Psychiatry
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    • "The trends for the risk overestimation in low-risk populations and underestimation in high-risk groups have been successfully demonstrated by Cooney et al. [6]. It is known that an examination of 5% SCORE can equate to a 10–25% FRS risk, depending on which of the several FRS functions is selected [3]. "
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    ABSTRACT: The purpose of this study was the development of a clustering methodology to deal with arterial pressure waveform (APW) parameters to be used in the cardiovascular risk assessment. One hundred sixteen subjects were monitored and divided into two groups. The first one (23 hypertensive subjects) was analyzed using APW and biochemical parameters, while the remaining 93 healthy subjects were only evaluated through APW parameters. The expectation maximization (EM) and k-means algorithms were used in the cluster analysis, and the risk scores (the Framingham Risk Score (FRS), the Systematic COronary Risk Evaluation (SCORE) project, the Assessing cardiovascular risk using Scottish Intercollegiate Guidelines Network (ASSIGN) and the PROspective Cardiovascular Münster (PROCAM)), commonly used in clinical practice were selected to the cluster risk validation. The result from the clustering risk analysis showed a very significant correlation with ASSIGN (r = 0.582, p < 0.01) and a significant correlation with FRS (r = 0.458, p < 0.05). The results from the comparison of both groups also allowed to identify the cluster with higher cardiovascular risk in the healthy group. These results give new insights to explore this methodology in future scoring trials.
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