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      Cardiovascular Risk Assessed by Reynolds Risk Score in Relation to Waist Circumference in Apparently Healthy Middle-Aged Population in Montenegro

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          Abstract

          SUMMARY – Reynolds Risk Score (RRS) is regarded as a good screening tool for cardiovascular disease (CVD) risk. Since CVD is the leading cause of death in Montenegro, we aimed to assess the risk of CVD as assessed by RRS and to examine its association with cardiometabolic parameters in apparently healthy middle-aged population. In addition, we aimed to test whether obesity had an independent influence on RRS. A total of 132 participants (mean age 56.2±6.73 years, 69% females) were included. Body mass index (BMI), waist circumference (WC), blood pressure (BP) and biochemical parameters (fasting glucose, insulin, lipid parameters, creatinine and high sensitivity C-reactive protein) were determined. Insulin resistance (HOMA-IR) and glomerular filtration rate (eGFR) were calculated. Compared with females, a significantly higher number of males were in the high RRS subgroup (χ 2=45.9, p<0.001). Furthermore, significantly higher fasting glucose (p=0.030), insulin, HOMA-IR, triglycerides (p<0.001 all), anthropometric parameters (e.g., BMI and WC; p=0.004 and p<0.001, respectively), and creatinine, but lower eGFR and HDL-c (p<0.001 both) were recorded in the high-risk subgroup compared with low and medium risk subgroups. In all participants, in addition to LDL-c, diastolic BP and creatinine, WC was independently positively associated with RRS (β=0.194, p=0.006; β=0.286, p=0.001; β=0.267, p=0.001; and β=0.305, p=0.019, respectively), and 40% of variation in RRS could be explained with this model. In conclusion, middle-aged population with higher WC should be screened for RRS in order to estimate CVD risk.

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          Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score.

          Despite improved understanding of atherothrombosis, cardiovascular prediction algorithms for women have largely relied on traditional risk factors. To develop and validate cardiovascular risk algorithms for women based on a large panel of traditional and novel risk factors. Thirty-five factors were assessed among 24 558 initially healthy US women 45 years or older who were followed up for a median of 10.2 years (through March 2004) for incident cardiovascular events (an adjudicated composite of myocardial infarction, ischemic stroke, coronary revascularization, and cardiovascular death). We used data among a random two thirds (derivation cohort, n = 16 400) to develop new risk algorithms that were then tested to compare observed and predicted outcomes in the remaining one third of women (validation cohort, n = 8158). Minimization of the Bayes Information Criterion was used in the derivation cohort to develop the best-fitting parsimonious prediction models. In the validation cohort, we compared predicted vs actual 10-year cardiovascular event rates when the new algorithms were compared with models based on covariates included in the Adult Treatment Panel III risk score. In the derivation cohort, a best-fitting model (model A) and a clinically simplified model (model B, the Reynolds Risk Score) had lower Bayes Information Criterion scores than models based on covariates used in Adult Treatment Panel III. In the validation cohort, all measures of fit, discrimination, and calibration were improved when either model A or B was used. For example, among participants without diabetes with estimated 10-year risks according to the Adult Treatment Panel III of 5% to less than 10% (n = 603) or 10% to less than 20% (n = 156), model A reclassified 379 (50%) into higher- or lower-risk categories that in each instance more accurately matched actual event rates. Similar effects were achieved for clinically simplified model B limited to age, systolic blood pressure, hemoglobin A(1c) if diabetic, smoking, total and high-density lipoprotein cholesterol, high-sensitivity C-reactive protein, and parental history of myocardial infarction before age 60 years. Neither new algorithm provided substantive information about women at very low risk based on the published Adult Treatment Panel III score. We developed, validated, and demonstrated highly improved accuracy of 2 clinical algorithms for global cardiovascular risk prediction that reclassified 40% to 50% of women at intermediate risk into higher- or lower-risk categories.
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            Comparison of the Framingham and Reynolds Risk scores for global cardiovascular risk prediction in the multiethnic Women's Health Initiative.

            Framingham-based and Reynolds Risk scores for cardiovascular disease (CVD) prediction have not been directly compared in an independent validation cohort. We selected a case-cohort sample of the multiethnic Women's Health Initiative Observational Cohort, comprising 1722 cases of major CVD (752 myocardial infarctions, 754 ischemic strokes, and 216 other CVD deaths) and a random subcohort of 1994 women without prior CVD. We estimated risk using the Adult Treatment Panel III (ATP-III) score, the Reynolds Risk Score, and the Framingham CVD model, reweighting to reflect cohort frequencies. Predicted 10-year risk varied widely between models, with ≥10% risk in 6%, 10%, and 41% of women with the ATP-III, Reynolds, and Framingham CVD models, respectively. Calibration was adequate for the Reynolds model, but the ATP-III and Framingham CVD models overestimated risk for coronary heart disease and major CVD, respectively. After recalibration, the Reynolds model demonstrated improved discrimination over the ATP-III model through a higher c statistic (0.765 versus 0.757; P=0.03), positive net reclassification improvement (NRI; 4.9%; P=0.02), and positive integrated discrimination improvement (4.1%; P<0.0001) overall, excluding diabetics (NRI=4.2%; P=0.01), and in white (NRI=4.3%; P=0.04) and black (NRI=11.4%; P=0.13) women. The Reynolds (NRI=12.9%; P<0.0001) and ATP-III (NRI=5.9%; P=0.0001) models demonstrated better discrimination than the Framingham CVD model. The Reynolds Risk Score was better calibrated than the Framingham-based models in this large external validation cohort. The Reynolds score also showed improved discrimination overall and in black and white women. Large differences in risk estimates exist between models, with clinical implications for statin therapy.
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              Anthropometric measurements of general and central obesity and the prediction of cardiovascular disease risk in women: a cross-sectional study

              Objectives It is important to ascertain which anthropometric measurements of obesity, general or central, are better predictors of cardiovascular disease (CVD) risk in women. 10-year CVD risk was calculated from the Framingham risk score model, SCORE risk chart for high-risk regions, general CVD and simplified general CVD risk score models. Increase in CVD risk associated with 1 SD increment in each anthropometric measurement above the mean was calculated, and the diagnostic utility of obesity measures in identifying participants with increased likelihood of being above the treatment threshold was assessed. Design Cross-sectional data from the National Heart Foundation Risk Factor Prevalence Study. Setting Population-based survey in Australia. Participants 4487 women aged 20–69 years without heart disease, diabetes or stroke. Outcome measures Anthropometric obesity measures that demonstrated the greatest increase in CVD risk as a result of incremental change, 1 SD above the mean, and obesity measures that had the greatest diagnostic utility in identifying participants above the respective treatment thresholds of various risk score models. Results Waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-stature ratio had larger effects on increased CVD risk compared with body mass index (BMI). These central obesity measures also had higher sensitivity and specificity in identifying women above and below the 20% treatment threshold than BMI. Central obesity measures also recorded better correlations with CVD risk compared with general obesity measures. WC and WHR were found to be significant and independent predictors of CVD risk, as indicated by the high area under the receiver operating characteristic curves (>0.76), after controlling for BMI in the simplified general CVD risk score model. Conclusions Central obesity measures are better predictors of CVD risk compared with general obesity measures in women. It is equally important to maintain a healthy weight and to prevent central obesity concurrently.
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                Author and article information

                Journal
                Acta Clin Croat
                Acta Clin Croat
                ACC
                Acta Clinica Croatica
                Sestre Milosrdnice University Hospital and Institute of Clinical Medical Research, Vinogradska cesta c. 29 Zagreb
                0353-9466
                1333-9451
                March 2018
                March 2018
                : 57
                : 1
                : 22-30
                Affiliations
                Primary Health Care Center, Podgorica, Montenegro; University Department of Pediatrics, Faculty of Medicine, University of Niš, Niš, Serbia; Clinical Center of Montenegro, Podgorica, Montenegro; Department of Medical Biochemistry, University of Belgrade, Faculty of Pharmacy, Belgrade, Serbia; Department of Biology, Faculty of Natural Science and Mathematics, University of Montenegro, Podgorica, Montenegro
                Author notes
                Correspondence to: Aleksandra Klisić, MD, PhD, Primary Health Care Center, Trg Nikole Kovačevića 6, 81000 Podgorica, Montenegro
E-mail: aleksandranklisic@ 123456gmail.com 
Received March 8, 2017, accepted January 18, 2018
                Article
                acc-57-22
                10.20471/acc.2018.57.01.03
                6400353
                30256008
                b1d16012-3cef-4320-96c9-fb0e96acafd8
                Copyright @ 2018

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND) 4.0 License.

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                Categories
                Original Scientifi c Paper

                cardiovascular diseases,risk factors,body mass index,waist circumference,c-reactive protein,obesity,cause of death,montenegro

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