Cardiovascular Disease Risk Prediction - Integration into Clinical Practice

Thura, T.; Blaha, Michael J.; Blumenthal, Roger S.; Joshi, Parag H.

doi:10.1007/s12170-013-0332-y

Cited by 2 publications

(2 citation statements)

References 45 publications

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“…The diabetes risk prediction models all account for BMI and in some instances the combination of both BMI and waist circumferences; therefore, these differences explain the observations in the diabetes prediction models. Age is generally regarded as the most dominant variable in CVD prediction models 22,23 and is an included risk variable in each of the diabetes risk assessments examined in this study. Therefore, the clinical relevance of cardiorespiratory fitness is demonstrated in the negative relationships between relative cardiorespiratory fitness values, thus allowing for age in all of the risk prediction scores (Figures 1 and 2).…”

Section: Discussionmentioning

confidence: 99%

Cardiorespiratory fitness is a stronger indicator of cardiometabolic risk factors and risk prediction than self-reported physical activity levels

Gray

Stephens

Williams

et al. 2015

Diabetes and Vascular Disease Research

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This study investigated the relationships of self-reported physical activity levels and cardiorespiratory fitness in 81 males to assess which measurement is the greatest indicator of cardiometabolic risk. Physical activity levels were determined by the General Practice Physical Activity Questionnaire tool and cardiorespiratory fitness assessed using the Chester Step Test. Cardiovascular disease risk was estimated using the QRISK2, Framingham Lipids, Framingham body mass index and Joint British Societies' Guidelines-2 equations, and type 2 diabetes mellitus risk calculated using QDiabetes, Leicester Risk Assessment, Finnish Diabetes Risk Score and Cambridge Risk Score models. Categorising employees by cardiorespiratory fitness categories ('Excellent/Good' vs 'Average/Below Average') identified more differences in cardiometabolic risk factor (body mass index, waist circumference, total cholesterol, total cholesterol:high-density lipoprotein ratio, high-density lipoprotein cholesterol, triglycerides, HbA 1c ) scores than physical activity (waist circumference only). Cardiorespiratory fitness levels also demonstrated differences in all four type 2 diabetes mellitus risk prediction models and both the QRISK2 and Joint British Societies' Guidelines-2 cardiovascular disease equations. Furthermore, significant negative correlations (p < 0.001) were observed between individual cardiorespiratory fitness values and estimated risk in all prediction models. In conclusion, from this preliminary observational study, cardiorespiratory fitness levels reveal a greater number of associations with markers of cardiovascular disease or type 2 diabetes mellitus compared to physical activity determined by the General Practice Physical Activity Questionnaire tool.

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Section: Discussionmentioning

confidence: 99%

Cardiorespiratory fitness is a stronger indicator of cardiometabolic risk factors and risk prediction than self-reported physical activity levels

Gray

Stephens

Williams

et al. 2015

Diabetes and Vascular Disease Research

View full text Add to dashboard Cite

show abstract

“…In both these scenarios there is a financial implication, be it by an increase in emergency admissions for individuals who believed they were at 'low' or 'intermediate' risk, or through statin treatments that are not required. One of the disadvantages of CVD risk prediction models is that the most heavily weighted variable in their algorithms is age, 6,19 which explains how an increase in predicted CVD risk concomitant with age was observed with all the risk algorithms despite very small differences between the prevalence of isolated risk factors.…”

Section: Implications For Research and Practicementioning

confidence: 99%

Predicted 10-year risk of cardiovascular disease is influenced by the risk equation adopted: a cross-sectional analysis

Gray¹,

Bracken

Turner

et al. 2014

Br J Gen Pract

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BackgroundValidated risk equations are currently recommended to assess individuals to determine those at 'high risk' of cardiovascular disease (CVD). However, there is no longer a risk 'equation of choice'. AimThis study examined the differences between four commonly-used CVD risk equations. Design and settingCross-sectional analysis of individuals who participated in a workplace-based risk assessment in Carmarthenshire, south Wales. MethodAnalysis of 790 individuals (474 females, 316 males) with no prior diagnosis of CVD or diabetes. Ten-year CVD risk was predicted by entering the relevant variables into the QRISK2, Framingham Lipids, Framingham BMI, and JBS2 risk equations. ResultsThe Framingham BMI and JBS2 risk equations predicted a higher absolute risk than the QRISK2 and Framingham Lipids equations, and CVD risk increased concomitantly with age irrespective of which risk equation was adopted. Only a small proportion of females (0-2.1%) were predicted to be at high risk of developing CVD using any of the risk algorithms. The proportion of males predicted at high risk ranged from 5.4% (QRISK2) to 20.3% (JBS2). After age stratification, few differences between isolated risk factors were observed in males, although a greater proportion of males aged ≥50 years were predicted to be at 'high risk' independent of risk equation used. ConclusionsDifferent risk equations can influence the predicted 10-year CVD risk of individuals. More males were predicted at 'high risk' using the JBS2 or Framingham BMI equations. Consideration should also be given to the number of isolated risk factors, especially in younger adults when evaluating CVD risk.

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Cardiovascular Disease Risk Prediction - Integration into Clinical Practice

Cited by 2 publications

References 45 publications

Cardiorespiratory fitness is a stronger indicator of cardiometabolic risk factors and risk prediction than self-reported physical activity levels

Cardiorespiratory fitness is a stronger indicator of cardiometabolic risk factors and risk prediction than self-reported physical activity levels

Predicted 10-year risk of cardiovascular disease is influenced by the risk equation adopted: a cross-sectional analysis

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