Literature DB >> 23563367

The impact of age & ethnicity in coronary artery disease risk assessment using Framingham Risk Scores & metabolic syndrome.

Dimitrios M Konstantinou1.   

Abstract

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Year:  2013        PMID: 23563367      PMCID: PMC3657847     

Source DB:  PubMed          Journal:  Indian J Med Res        ISSN: 0971-5916            Impact factor:   2.375


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Metabolic syndrome (MS) is a constellation of coronary artery disease (CAD) risk factors including abdominal obesity, non-traditional dyslipidaemia [i.e. low high density lipoprotein cholesterol (HDL-C), high triglycerides (TG) levels and the presence of small, dense low density lipoprotein cholesterol (LDL-C) particles], impaired fasting glucose and elevated blood pressure. These abnormalities tend to cluster in a frequency greater than chance expectation and it was hypothesized that the underlying pathophysiological disorder is insulin resistance1. Epidemiological data derived from large, community-based observational studies suggest that MS is associated with incident diabetes mellitus2 and increased cardiovascular (CV) morbidity3 and mortality4. However, these findings were questioned by others claiming that MS has no independent predictive ability for future CV events56 or that MS carries no additional prognostic information than that conferred by the sum of its parts7. On the other hand, Framingham Risk Score (FRS) is a widely accepted risk model estimating one's 10-year cardiovascular risk and stratifying individuals accordingly as low (<10%), intermediate (10-20%) and high risk (>20%)8. FRS takes into account age, smoking status, lipids, diabetes status and hypertension. Prospectively collected data support that FRS is superior to MS in future CV events prediction9 while others report a significant correlation between MS and prevalent CAD in subjects considered as low risk according to FRS10. In the present cross-sectional study by Khanna et al11, both MS status and FRS were assessed in a consecutive sample of 200 patients undergoing coronary angiography. Among study participants, 88 per cent had significant coronary artery lesions defined as luminal narrowing of >50 per cent in at least one of the three major epicardial coronary arteries. MS was significantly associated with CAD prevalence since only 6 per cent of MS patients had a normal coronary angiogram compared with 28 per cent of their non-MS counterparts (P<0.05). MS presence was also correlated with CAD severity with a reported prevalence of double or triple vessel disease of 61 per cent compared to 41 per cent among non-MS individuals (P<0.05). Despite this high overall CAD prevalence, as many as 35 and 41 per cent of patients respectively were classified as low- and intermediate-risk according to FRS. Mean FRS among MS patients, was significantly higher compared to those without MS (P<0.001) while MS prevalence increased progressively across FRS categories (from 61 over 87% to 92%). The present work provides two useful clinical implications. First, the authors underline the significant age dependence of FRS which limits its predictive ability when it is applied in younger individuals. Splitting the patients into four age groups further supported this argument; MS prevalence remained constantly high (>70%) in all age groups while less than 15 per cent of patients younger than 65 yr were considered as having a high 10-year CV risk according to FRS11. The great importance of applying the more relevant MS definition for a certain population is another point highlighted in this study. Various guidelines have been proposed over time (e.g. WHO, NCEP-ATP, IDF) and different cut-off points have been set for certain ethnic groups. Particularly in Asians, a lower threshold for waist circumference is applied reflecting the overall lower mean BMI in this population. Moreover, a significant proportion of Asian people are described as metabolically obese - having high triglycerides and low HDL-C levels - while being within the normal range of waist circumference and waist-to-hip ratio12. Different MS definitions result in quite variable estimates for MS prevalence. In the present study11, MS prevalence was 77 per cent according to the modified South Asian guidelines1213 and came down to 61 per cent when IDF definition14 was applied. This observation suggests that considering the increased waist circumference as an essential criterion (IDF definition) would underestimate the true prevalence of MS in study's population. According to the authors, 12 per cent of participants with a normal BMI (i.e. <23 kg/m2 were still classified as having MS. Probably this subgroup of patients represents the normal weight but metabolically obese Indians. The authors conclude that in a population where CAD develops earlier than it is reported in Western countries, FRS may underestimate true CV risk among younger individuals. On the contrary, MS prevalence remains constantly high across all age groups. Moreover, MS provides life-time prognostic information for incident CAD while FRS is valid only for a 10-year period which is a relatively short period when applied in young individuals. Based on the present study's findings, physicians should not rely solely to FRS to assess one's individual risk for future CV events rather evaluating additionally his/her MS status. Keeping in the same line, Khanna et al11 underscore the need for increased awareness among health practitioners in diagnosing MS since a non-negligible proportion of patients may still have MS despite being of normal weight. In modern times where MS and associated metabolic abnormalities are constantly rising, early MS identification and adaptation of a healthier lifestyle seem to be the key goal for CV primary prevention.
  13 in total

1.  Prevention Conference V: Beyond secondary prevention: identifying the high-risk patient for primary prevention: medical office assessment: Writing Group I.

Authors:  S M Grundy; T Bazzarre; J Cleeman; R B D'Agostino; M Hill; N Houston-Miller; W B Kannel; R Krauss; H M Krumholz; R M Lauer; I S Ockene; R C Pasternak; T Pearson; P M Ridker; D Wood
Journal:  Circulation       Date:  2000-01-04       Impact factor: 29.690

2.  The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men.

Authors:  Hanna-Maaria Lakka; David E Laaksonen; Timo A Lakka; Leo K Niskanen; Esko Kumpusalo; Jaakko Tuomilehto; Jukka T Salonen
Journal:  JAMA       Date:  2002-12-04       Impact factor: 56.272

3.  Defining the metabolic syndrome construct: Multi-Ethnic Study of Atherosclerosis (MESA) cross-sectional analysis.

Authors:  Dhananjay Vaidya; Moyses Szklo; Kiang Liu; Pamela J Schreiner; Alain G Bertoni; Pamela Ouyang
Journal:  Diabetes Care       Date:  2007-05-07       Impact factor: 19.112

4.  Metabolic syndrome vs Framingham Risk Score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus.

Authors:  S Goya Wannamethee; A Gerald Shaper; Lucy Lennon; Richard W Morris
Journal:  Arch Intern Med       Date:  2005 Dec 12-26

5.  Metabolic syndrome as a predictor of all-cause and cardiovascular mortality in type 2 diabetes: the Casale Monferrato Study.

Authors:  Graziella Bruno; Franco Merletti; Annibale Biggeri; Giuseppe Bargero; Stefania Ferrero; Cristina Runzo; Stefano Prina Cerai; Gianfranco Pagano; Paolo Cavallo-Perin
Journal:  Diabetes Care       Date:  2004-11       Impact factor: 19.112

6.  Metabolic syndrome and angiographic coronary artery disease prevalence in association with the Framingham risk score.

Authors:  Dimitris M Konstantinou; Yiannis S Chatzizisis; George E Louridas; George D Giannoglou
Journal:  Metab Syndr Relat Disord       Date:  2010-06       Impact factor: 1.894

7.  Diabetes, the metabolic syndrome, and angiographic progression of coronary arterial disease in postmenopausal women.

Authors:  Philip B Mellen; William T Cefalu; David M Herrington
Journal:  Arterioscler Thromb Vasc Biol       Date:  2005-10-20       Impact factor: 8.311

8.  Metabolic syndrome with and without C-reactive protein as a predictor of coronary heart disease and diabetes in the West of Scotland Coronary Prevention Study.

Authors:  Naveed Sattar; Allan Gaw; Olga Scherbakova; Ian Ford; Denis St J O'Reilly; Steven M Haffner; Chris Isles; Peter W Macfarlane; Chris J Packard; Stuart M Cobbe; James Shepherd
Journal:  Circulation       Date:  2003-07-14       Impact factor: 29.690

Review 9.  The metabolic syndrome and dyslipidemia among Asian Indians: a population with high rates of diabetes and premature coronary artery disease.

Authors:  Enas A Enas; Vishwanathan Mohan; Mohan Deepa; Syed Farooq; Suraj Pazhoor; Hancy Chennikkara
Journal:  J Cardiometab Syndr       Date:  2007

10.  Metabolic syndrome & Framingham Risk Score: observations from a coronary angiographic study in Indian patients.

Authors:  Roopali Khanna; Aditya Kapoor; Sudeep Kumar; Satyendra Tewari; Naveen Garg; Pravin K Goel
Journal:  Indian J Med Res       Date:  2013-02       Impact factor: 2.375

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