Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation

Ferrario, Marco; Chiodini, Paolo; Chambless, Lloyd E.; Cesana, Giancarlo; Vanuzzo, Diego; Panico, Salvatore; Sega, Roberto; Pilotto, Lorenza; Palmieri, Luigi; Giampaoli, Simona

doi:10.1093/ije/dyh405

Cited by 194 publications

(162 citation statements)

References 34 publications

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“…Although these prediction models stratify patients according to different hard clinical end-points (events in the CUORE model and mortality in the SCORE model), they are assumed to be largely concordant and are both currently recommended for CV risk stratification by national [24] and [25] and European [13] guidelines. Therefore, given persistent uncertainties on reliability of risk classification based on conventional risk factors alone [2] and [3], routine ABI measurement appears to be an easy and reliable tool for identification of high risk subjects irrespective of conventional risk models.…”

Section: Discussionmentioning

confidence: 99%

Implications of routinely measuring Ankle-Brachial Index (ABI) among patients attending at a Lipid Clinic

Sona

Comba

Brescianini

et al. 2009

European Journal of Internal Medicine

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The definitive versionisavailableat:La versione definitiva è disponibile alla URL: [http://www.sciencedirect.com/science/article/pii/S0953620508002677?via=ihub] Implications of routinely measuring Ankle-Brachial Index (ABI) among patients attending at a Lipid Clinic Alessandro Sona, Monica Comba, Alessia Brescianini, Laura Corsinovi, Mauro Zanocchi, Gianfranco Fonte, Mario BoCorresponding author contact information, E-mail the corresponding author Abstract BackgroundLow (≤ 0.90) Ankle Brachial Index (ABI) values identify patients at high risk for cardiovascular (CV) disease and mortality. Implications for CV risk classification from routinely measuring ABI in the context of a Lipid Clinic have not been fully investigated. We aimed to evaluate whether and to what extent routine ABI determination on top of conventional risk prediction models may modify CV risk classification. MethodsConsecutive asymptomatic non-diabetic individuals free from previous CV events attending for a first visit at a Lipid Clinic underwent routine ABI determination and conventional CV risk classification according either to national CUORE model (including age, gender, smoking, total and high density lipoprotein cholesterol, systolic blood pressure and current use of blood pressure lowering drugs) and SCORE model for low risk countries. ResultsIn the overall sample (320 subjects, mean age 64.8 years) 77 subjects (24.1%) were found to have low ABI value. Forty-two of 250 subjects (16.8%) and 47 of 215 individuals (21.3%) at low or moderate risk according to the CUORE and SCORE models, respectively, were found to have low ABI values, and should be reclassified at high risk. ConclusionIn a series of consecutive asymptomatic individuals in a Lipid Clinic, we observed a high prevalence of low ABI values among subjects deemed at low or moderate risk on conventional prediction models, leading to CV high-risk reclassification of roughly one fifth of patients. These findings reinforce recommendations for routine determination of ABI at least within referral primary prevention settings.

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Section: Discussionmentioning

confidence: 99%

Implications of routinely measuring Ankle-Brachial Index (ABI) among patients attending at a Lipid Clinic

Sona

Comba

Brescianini

et al. 2009

European Journal of Internal Medicine

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“…Global individual CVD risk was calculated applying the risk equations of the CUORE project (13,14). Subjects older than 69 years or with previous cardiovascular events were excluded from this analysis.…”

Section: Definition Of Risk Factorsmentioning

confidence: 99%

“…Population-based reports in older populations (1, 2) suggested that T-wave deviation could be an indicator of increased risk of coronary heart disease and total mortality, independently on other cardiovascular risk factors; however such data were not confirmed in middle age subjects (22,23). We used the predicted risk of CVD in the Italian population, as a markers of ischemic cardiovascular risk, by applying the individual CUORE risk score (14,15), which provides an estimate of the probability of the first coronary or cerebrovascular event in the next ten years, based on a risk function derived from several Italian cohorts (24). Estimated risk for CVD has been already used as a surrogate for CVD to evaluate the association with novel risk factors (25,26).…”

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confidence: 99%

T-wave axis deviation, metabolic syndrome and estimated cardiovascular risk – In men and women of the MOLI-SANI study

et al. 2013

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Title: T-wave axis deviation, metabolic syndrome and estimated cardiovascular risk in men and women of the MOLI-SANI Study Methods: 11,143 women (54±11 years) and 9,742 men (55±11 years) were analysed from the Molisani cohort, randomly recruited from the general population. MetS was defined using the ATPIII criteria. T-wave axis deviation was measured from the standard 12-lead resting electrocardiogram.CVD risk in ten years was estimated by the CUORE score.Results: 29% of men and 27% of women with MetS showed borderline or abnormal T-wave as compared to 24% and 17% without MetS (p<0.0001 for both genders).Among components of MetS, elevated waist and blood pressure were strongly associated with Twave axis deviation, whereas glucose, HDL and triglycerides were only marginally. The odds of having borderline or abnormal T-wave axis deviation in multivariable regression analysis, was 1.38 (95% CI:1.25-1.53) in MetS men and 1.68 (95% CI:1.51-1.87) in MetS women compared to those without. Further adjustment for MetS components completely abolished the associations. Abnormal T-wave axis deviation was associated with an increased risk of CVD in 10 years in men (OR=4.4; 95% CI:1.10-17.9). Conclusion:T-wave axis deviation is strongly associated with components of the MetS, in particular high waist circumference and blood pressure and with an increased CVD risk, particularly in men.ECG monitoring to identify T-wave axis deviation in obese, hypertensive or MetS subjects can be an early indicator of vascular disease and help in reducing cardiac events.Word count: 250

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“…[7][8][9] Smoking acts synergistically with other major risk factors of CVD such as age, sex, high blood pressure, dyslipidemia and diabetes. 10 This has led to the development and validation of a number of multivariable risk models which can be used by primary care physicians to assess the risk in individual patients of developing all atherosclerotic CVD [11][12][13][14][15][16][17][18][19][20] or specific types of CVD, namely, coronary heart disease, 10,[20][21][22][23][24][25] stroke, 26 peripheral vascular disease, 27 or heart failure. 28 Multivariable assessment has been advocated to estimate absolute CVD risk and guide treatment of risk factors, 2,29 and the Framingham CVD risk assessment tool and other similar risk assessment tools have been validated 22,23,25 and also re-calibrated in other ethnically diverse populations.…”

Section: Introductionmentioning

confidence: 99%

“…10 This has led to the development and validation of a number of multivariable risk models which can be used by primary care physicians to assess the risk in individual patients of developing all atherosclerotic CVD [11][12][13][14][15][16][17][18][19][20] or specific types of CVD, namely, coronary heart disease, 10,[20][21][22][23][24][25] stroke, 26 peripheral vascular disease, 27 or heart failure. 28 Multivariable assessment has been advocated to estimate absolute CVD risk and guide treatment of risk factors, 2,29 and the Framingham CVD risk assessment tool and other similar risk assessment tools have been validated 22,23,25 and also re-calibrated in other ethnically diverse populations. 10,17,20,[26][27][28][29] This study seeks to examine the role of cigarette smoking as a risk factor in risk models in greater detail than the simple dichotomous yes/no variable [1][2][3] that has been incorporated in all the existing risk prediction models.…”

Section: Introductionmentioning

confidence: 99%

Framingham Risk Prediction Equations for Incidence of Cardiovascular Disease Using Detailed Measures for Smoking

Mannan

Stevenson

Peeters

et al. 2010

Heart, Lung and Circulation

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Current prediction models for risk of cardiovascular disease (CVD) incidence incorporate smoking as a dichotomous yes/no measure. However, the risk of CVD associated with smoking also varies with the intensity and duration of smoking and there is a strong association between time since quitting and the risk of disease onset. This study aims to develop improved risk prediction equations for CVD incidence incorporating intensity and duration of smoking and time since quitting.The risk of developing a first CVD event was evaluated using a Cox's model for participants in the Framingham offspring cohort who attended the fourth examination between the ages of 30 and 74 years and were free of CVD (n=3751). The full models based on the smoking variables and other risk factors, and reduced models based on the smoking variables and non-laboratory risk factors demonstrated good discrimination, calibration and global fit. The incorporation of both time since quitting among past smokers and packyears among current smokers resulted in better predictive performance as compared to a dichotomous current/non-smoker measure and a current/quitter/never smoker measure. Compared to never smokers, the risk of CVD incidence increased with pack-years. Risk among those quitting more than five years prior to the baseline exam and within five years prior to the baseline exam were similar and twice as high as that of never smokers. A CVD risk equation incorporating the effects of pack-years and time since quitting provides an improved tool to quantify risk and guide preventive care.

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Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation

Abstract: The CUORE Project predictive equation showed better accuracy of the FHS and PROCAM equations, overcoming frequently reported risk overestimates. The CUORE equation may be adopted to identify men with high coronary risk in Italy.

Cited by 194 publications

References 34 publications

Implications of routinely measuring Ankle-Brachial Index (ABI) among patients attending at a Lipid Clinic

Implications of routinely measuring Ankle-Brachial Index (ABI) among patients attending at a Lipid Clinic

T-wave axis deviation, metabolic syndrome and estimated cardiovascular risk – In men and women of the MOLI-SANI study

Framingham Risk Prediction Equations for Incidence of Cardiovascular Disease Using Detailed Measures for Smoking

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