Beyond the Definition of Metabolic Syndrome: Uric Acid, High Sensitivity C Reactive Protein and Global Cardiovascular Risk

ORIGINAL RESEARCH

 

Beyond the Definition of Metabolic Syndrome: Uric Acid, High Sensitivity C Reactive Protein and Global Cardiovascular Risk

 

Más allá de la definición de síndrome metabólico: ácido úrico, proteína c reactiva de alta sensibilidad y riesgo cardiovascular global

 

 

Jorge Vega Abascal 1,  Mayra Rosa Guimara Mosqueda 2, Luis Vega Abascal 3

1. Master degree in Medical Urgencies. Specialist in Internal Medicine. Associate Professor. Jose Avila Serrano  Teaching Polyclinic.  Velasco. Holguin, Cuba.
2. Master degree in Medical Urgencies. Specialist in Community Medicine and Second degree Specialist in Cardiology. Associate Professor. Jose Avila Serrano Teaching Polyclinic.  Velasco. Holguin, Cuba.
3. Master degree in Medical Urgencies. Specialist in Surgery. Associate Professor.  Jose Avila Serrano Teaching Polyclinic.  Velasco. Holguin, Cuba.

 

 

ABSTRACT

Introduction: the metabolic syndrome is becoming one of the main problems in public health.
Objective: to evaluate the relation between metabolic syndrome and uric acid, high sensitivity c reactive protein, total cardiovascular risk and cardiovascular events.
Methods: a study of cases controls nested in a dynamic cohort was carried out in Velasco Teaching Polyclinic from 2010 to 2015, the cases were 67 patients that developed metabolic syndrome during the period and the control group  were 67 patients matched by sex and age ± 5 years. The participants underwent a physical examination, anthropometry, laboratory test; all the study participants were under continuous surveillance during 4.5 years for development of cardiovascular events.
Results: the waist circumference (p = 0.000), systolic (p= 0.0042) and diastolic blood pressure (p= 0.0298), high sensitivity c reactive protein (p= 0.0039) and uric acid (p= 0.0283)   were significantly associate in both groups. The body mass index  was higher than 30 kg/m2 (OR 7.54; CI95%:3.35-16.9), LDL cholesterol greater than 4.16 mmol/l (OR 3.49; CI 95%:1.58-7.70) and hs CRP higher than 1 mg/dl (OR 3.59; CI 95%:1.51-8.51) showed statistically significant differences according to groups of studies. Global cardiovascular risk greater 20%, it was 3.84 times higher in the group with metabolic syndrome (CI 95%:1.67-8.82), 13.4% of the patients with metabolic syndrome developed a cardiovascular event during the period in comparison with the 2.9% in the group without metabolic syndrome (OR= 5.04; CI 95%: 1.04-24.3).
Conclusions: metabolic syndrome was significantly associated with mean level of uric acid, high sensitivity c reactive protein, total cardiovascular risk and cardiovascular events.

Keywords: metabolic syndrome, high sensitivity c reactive protein, uric acid, total cardiovascular risk, primary health care

RESUMEN

Introducción: el síndrome metabólico se está convirtiendo en uno de los principales problemas de salud pública
Objetivo: evaluar la relación entre el síndrome metabólico y el ácido úrico, la proteína c reactiva de alta sensibilidad, el riesgo cardiovascular global y la incidencia de eventos cardiovasculares.
Métodos: se realizó un estudio de casos controles anidados en una cohorte dinámica en el Policlínico Docente de Velasco desde 2010 a 2015, los casos fueron 67 pacientes que desarrollaron síndrome metabólico en el periodo y 67 controles que fueron apareados por sexo y edad de ± 5 años en relación con los casos, los participantes fueron sometidos a  un examen físico, determinaciones antropométricas y de laboratorio, fueron sometidos a seguimiento durante 4,5 años para la aparición de eventos cardiovasculares.
Resultados: mostraron que la circunferencia abdominal (p 0,000), la presión arterial sistólica (p 0,0042) y diastólica (p 0,0298), la proteína c reactiva de alta sensibilidad (p 0,0039) y el ácido úrico (p 0,0283) mostraron asociación estadísticamente significativa en ambos grupos. El  índice de masa corporal mayor de  30 kg/m2 (OR 7,54;  IC 95%: 3,35-16,9), LDL colesterol  mayor de 4,16 mmol/l (OR 3,49; IC 95%:1,58-7,70)  y proteína c reactiva de alta sensibilidad mayor de  1 mg/dl (OR=3,59; IC 95%:1,51-8,51) mostraron asociación estadísticamente significativa de acuerdo con los grupos  de estudio. El riesgo cardiovascular global mayor de  20% fue  3,84 veces mayor en el grupo con síndrome metabólico (IC 95 %: 1,67-8,82), el  13,4%  de los pacientes con  síndrome metabólico desarrollaron un evento cardiovascular durante el periodo de seguimiento en comparación con el  2,9% en el grupo sin síndrome metabólico (OR= 5,04; IC 95%: 1,04-24,3).
Conclusiones: el síndrome metabólico se asoció significativamente con la concentración media de ácido úrico, con la proteína c reactiva de alta sensibilidad, el riesgo cardiovascular global y el desarrollo de eventos cardiovasculares.

Palabras clave: síndrome metabólico, proteína c reactiva de alta sensibilidad, ácido úrico, riesgo cardiovascular total, atención primaria de salud.

 

 

INTRODUCTION

Metabolic syndrome (MetS) is a combination of medical disorders that, including obesity, insulin resistance, impaired glucose metabolism, dyslipidemia of high triglycerides, low level of high density lipoprotein cholesterol (HDLc) and elevated blood pressure, when occurring together, increase the risk of developing cardiovascular disease and diabetes. It has become a major public health challenge worldwide 1, 2.

Since the first official definition of the MetS by a World Health Organization Working Group in 1999, a number of alternative definitions have been proposed. The most widely accepted of these have been produced by the European Group for the Study of Insulin Resistance (EGIR), International Diabetes Federation (IDF) and the National Cholesterol Education Program Adult Treatment Panel III (ATP III) 3.

Although a consensus criterion has not been reached for diagnosing MetS, it is recommended that screening should consider central obesity, insulin resistance; dyslipidemia (elevated triglycerides and low density lipoprotein cholesterol (LDLc)) and decreased high density lipoprotein cholesterol (HDLc), and high blood pressure. Other factors such as proinflammatory and prothrombotic states have also been associated with MetS 4.

These various definitions differed not only in the proposed components but also in the cut-off points used for each component, leading to considerable confusion, the confusion relates not only to the usefulness in the clinical setting but also was apparent in attempts to compare the burden of the MetS in different populations 3, 5.

There is an abundance of widely varying data comparing prevalence using different criteria and this only served to reinforce the need for a standardized definition internationally.  There is an urgent need to rationalize the variety of definitions that had been developed for the MetS. This need should be extended from clinical practice through to research 5.

The construct of the MetS diagnostic criteria has inherent limitations which impact on  its clinical usefulness, it does not include other important risk factors for predicting diabetes or cardiovascular disease (CVD), such as age, sex, family history socioeconomic status, ethnicity, current treatment, previous CVD events and LDLc, C reactive protein, uric acid or important behavioral variables such as smoking and physical activity 5, 6.

The MetS has proposed as a means to identify people with increased risk of cardiovascular disease and type 2 diabetes mellitus (T2DM) and to guide the clinical decisions and it has shown its utility to predict the morbidity and mortality for cardiovascular diseases and diabetes.

Cardiovascular disease often occurs in people with considered acceptable or average risk factors values, this suggests that there are other risk factors that must be the cause of this disease. If these factors were considered to the present set of CVD risk factors, it would improve risk estimation. A number of risk factors, some of them new and often called novel risk factors, have been proposed:  inflammatory markers such as C-reactive protein, coronary calcium, lipoprotein (a), interleukin-6, fibrinogen, homocysteine, insulin resistance, MetS, platelet function, and genetic scores 7.

The aim of this study was to evaluate the relation between MetS and uric acid, high sensitivity c reactive protein, global cardiovascular risk and cardiovascular events.

 

METHODS

A nested case control study in a dynamic cohort of 309 patients was carried out, the sample were  134 patients, with age between 35 to 74 years, without cardiovascular disease at baseline, of the Jose Avila Serrano Teaching Polyclinic, from Velasco, Holguin, during January 2010 to December 2015.

The cases were 67 patients that developed MetS during the period, according to definition of the ATP III proposed in 2005 by American Heart Association y and the  National Heart, Lung, and Blood Institute3 and the controls were 67 patients matched by sex and age ± 5 years, MetS was  considered if the patients have three of  the five criteria: abdominal obesity (waist circumference ≥ 102 cm  in male and  ≥ 88 cm in female), elevated triglycerides ≥ 1.70 mmol/l, decreased high-density lipoprotein cholesterol < 0.9 mmol/l in male  y   < 1.1 mmol/l in female, elevated blood pressure ≥ 130 mmHg for systolic or  ≥ 85 mmHg for diastolic blood pressure or blood pressure treatment,  and fasting glucose level ≥  5.55 mmol/l (100  mg/dl) or T2DM previously diagnosed3.

The participants underwent a physical examination, anthropometry, blood pressure determination, blood pressure measurements were made on the right arm of the seated participants with a aneroid sphygmomanometer and an appropriately sized cuff; the average of two physician-obtained measures constituted the examination blood pressure; waist circumference was measured (cm) at level of the navel; cigarette smoking status was ascertained if the patients smokes or had smokes  in the last six months, past history of diabetes and hypertension was ascertained by the physician; serum total cholesterol and HDLc, LDLc, calculated according to Friedewald formula.  Uric acid, glycaemia, high sensitivity c reactive protein (hs CRP) levels were determined with standardized enzymatic methods; hs CRP were determined in two times with an interval of 15 days, being used the value average of both measurements.

The global cardiovascular risk to the ten years was stratified using Framingham - D´Agostino (2008) 8 risk table, that it use for the calculation of the risk: age, sex, smoking, diabetes mellitus, treated or untreated systolic blood pressure, total cholesterol and HDLc, classifying the patients as low risk (< 10%), among 10-20% as intermediate risk and > 20% as high risk.

All the study participants were under continuous surveillance during 4.5 years; for development of cardiovascular events or death. Study defines hard cardiovascular events if the patients developed a myocardial infarction, ischemic stroke, hemorrhagic stroke mortal or no, and coronary death, and it was considered all cardiovascular events if the patient developed hard events plus coronary angina, transitory ischemic attack and peripheral arterial disease.

The means, standard deviation and percentages were calculated. Student t test was used to compare mean of the independent samples with significant value of p< 0.05 and Odd Ratio (OR) with 95% confidence intervals, the data was coded and processed using the Statistical Package for Social Sciences (SPSS, version 15) and Med Calc software (version 4.16g).

All participants provided written informed consent, and the study protocol was approved by the Institutional Review Ethics Committee at the Jose Avila Serrano Teaching Polyclinic.

 

RESULTS

In the cases and controls groups there were 49 women (73.1%) and 18 men (26.9%). The results showed that in the studied population the waist circumference, systolic and diastolic blood pressure, level of high sensitivity c reactive protein and mean uric acid levels were significantly associated in both groups (table I)

Table I. Characteristic of the study population.

Variable

Metabolic
Syndrome

n

Means

Standart
Deviation

Difference
Between
means

95%
Confidence
Interval

P
value

Age
(years)

Yes

67

56.2

± 11.8

1,8

-2.15-5.75

0.3688

No

67

54.4

±11.3

Waist Circumference (cm)

Yes

67

104.3

±11.7

15.1

11.44-18.76

0.0000

No

67

89.2

±9.6

Systolic Blood Pressure  (mmHg)

Yes

67

142

±23.2

10.8

3.48-18.12

0.0042

No

67

131.2

±19.5

Diastolic Blood
Pressure  (mmHg)

Yes

67

86.9

±12.3

4.5

0.45-8.55

0.0298

No

67

82.4

11.4

Total Cholesterol
(mmol/l)

Yes

67

5.54

±1.31

0.38

-0.06-0,82

0.0968

No

67

5.16

±1.32

LDL cholesterol
(mmol/l)

Yes

67

3.22

±1.39

0.23

-0.23-0.69

0.3261

No

67

2.99

±1.31

Uric Acid ( μmol/l)

Yes

67

348.6

±166.3

59.7

6.47-112.9

0.0283

No

67

288.9

±144.5

Hs CRP
(mg/dl)

Yes

67

3.8

±2.8

1.3

0.42-2.18

0.0039

No

67

2.5

±2.3

LDLc: Low density lipoprotein cholesterol
Hs CRP: High sensitivity c reactive protein

The proposed components   of MetS according to the ATPIII definition (table II) showed statistically significant differences between both groups.

Table II. Factors considered as identifying abnormalities of metabolic syndrome
according to ATP III definition.

Factors

Metabolic Syndrome* n=67 n (%)

No Metabolic Syndrome n=67 n (%)

OR

 95 % CI

Waist Circumference

48(71.6)

15(22.4)

7.54

3.35-16.9

Increase BP or Past history HBP

50(74.6)

27(40.3)

4.35

2.08-9.09

Increase fasting glucose or Diabetes Mellitus

26(38.8)

4(5.9)

9.98

3.24-30.7

Triglycerides

54(70.1)

28(41.8)

5.78

2.66-12.57

HDL cholesterol

37(55.2)

14(20.9)

4.67

2.18-9.99

Met S: Metabolic Syndrome
HBP: High Blood Pressure
HDLc: High- density lipoprotein cholesterol

* Diagnosis of metabolic syndrome according to ATP III, 2005 (Adult Treatment Panel III) 3

  • Elevated waist circumference: ≥ 102 cm in men  and  ≥ 88 cm in women

  • Elevated blood pressure: 130 mm Hg systolic BP or 85 mm Hg diastolic BP or, drug treatment for hypertension.

  • Elevated fasting glucose 100 mg/dl or drug treatment for elevated glucose

  • Elevated triglycerides:> 1.70 mmol/l

  • Reduced   HDL cholesterol: <0.9 mmol/l in men and <1.1 mmol/l in women

Other factors that increased the probability of MetS were body mass index more than 30 kg/m2, LDL cholesterol level more than 4.16 mmol/l   and level of hs CRP higher than 1 mg/dl showed statistically significant differences according to groups of study (table III).

Table III.  Factors that increased probability of the metabolic syndrome.

Factors

Metabolic Syndrome n=67 n (%)

No Metabolic Syndrome n=67 n (%)

OR

95 % CI

Smoking

Yes

19(28.4)

20(29.8)

0.93

0.44-1.96

No

48(71.6)

47(70.1)

1.07

0.51-2.26

Body Mass Index (kg/m2)

< 24.9

9(13.4)

32(47.8)

0.16

0.07-0.39

25-29.9

20(29.8)

24(35.8)

0.76

0.36-1.57

> 30

40(59.7)

11(16.4)

7.54

3.35-16.9

Total Cholesterol (mmol/l)

< 6

44(65.7)

52(77.6)

0.55

0.65-1.18

6-7.2

14(20.9)

9(13.4)

1.70

0.68-4.25

> 7.2

9(13.4)

6(8.9)

1.57

0.52-4.70

LDL Cholesterol (mmol/l)

< 3.37

25(37.3)

40(59.7)

0.40

0.20-0.80

3.38-4.13

13(19.4)

15(22.4)

0.83

0.36-1.92

> 4.16

29(43.3)

12(17.9)

3.49

1.58-7.70

Uric acid (μmol/l)

> 440(Male)
>350(Female)

27(40.3)

20(29.8)

1.58

0.77-3.24

Hs CRP (mg/dl)

< 1

9(13.4)

24(35.8)

0.27

0.12-0.66

> 1

58(86.6)

43(64.2)

3.59

1.51-8.51

LDLc: Low-density lipoprotein cholesterol
Hs CRP: High sensitivity c reactive protein

Total cardiovascular risk greater 20% was 3.84 times higher in the group with MetS (95 % CI: 1.67-8.82) and 13.4% of the patients with MetS developed a cardiovascular event during the period in comparison with 2.9% of patients in the group without MetS (OR= 5.4; 95% CI: 1.04-24.3) (table IV)

Table IV. Global cardiovascular risk and cardiovascular events according
to study groups.

Variable

Metabolic Syndrome n (%)

No Metabolic Syndrome n (%)

OR

 95 % CI

Global Cardiovascular Risk

< 10 %

19(28.4)

29(43.3)

0.51

0.25-1.06

10-20 %

21(31.3)

28(41.8)

0.63

0.31-1.29

> 20 %

27(40.3)

10(14.9)

3.84

1.67-8.82

Cardiovascular Events*

Hard

5(7.5)

1(1.5)

5.32

0.60-46.8

All

9(13.4)

2(2.9)

5.04

1.04-24.3

* Followed by 4.5 years

 

DISCUSSION

Among the contributing major cardiovascular risk factors, an increased waistline, elevated triglycerides, impaired fasting plasma glucose, high systolic blood pressure and low levels of HDL cholesterol are referred to as MetS 3, 9. Obesity is a growing burden worldwide; hence, forecasts predict an increase in prevalence from 35%, to  51% by 2030 in US Americans 9.

In this research the waist circumference (p 0.0000) was significantly associated in both groups (table I) and the BMI > 30 kg/m2 showed significantly statistical differences (OR 7.54; 95 % CI: 3.35-16.9) (table III).

In spite of the fact that high BMI values are associated with adverse risk profiles for morbidity and mortality, particularly in relation to T2DM and atherothrombotic cardiovascular disease, various sub-types of obesity have been described which complement the apparent dose-response relationship between BMI and its impact on health. The most classic sub-types are android obesity (abdominal) and gynoid obesity (gluteal obesity) 10.

Less well-known sub-types are, however, also of interest. For example, a phenotype corresponding to metabolically obese normal-weight (MONW) individuals has been reported, these individuals have a normal BMI together with some of the characteristics of obese individuals such as insulin resistance, central adiposity, low levels of HDL and high levels of triglycerides, and high blood pressure. At the same time, metabolically healthy obese (MHO) individuals have also been identified. These individuals have BMI>30, but none of the metabolic alterations which are typical of obese individuals 10.

The existence of these 2 "paradoxical" sub-types led to several studies over the last 2 decades which contributed to metabolically characterization and quantify visceral adipose tissue as opposed to subcutaneous adipose tissue. These studies showed that the quantity of visceral adipose tissue is directly correlated in both men and women with a seriously altered metabolic risk profile which leads the development of T2DM and cardiovascular disease. Therefore, although it is true that obesity increases the risk of chronic disease, it seems clear that patients with visceral obesity constitute a sub-group of individuals with the most serious metabolic alterations 10.

Indeed, adipose tissue is no longer regarded as a simple long-term storage organ for fatty acids but rather appreciated as an important role in the metabolism of lipids and glucose, since numerous hormones and proinflammatory cytokines are released from adipocytes themselves, macrophages, fibroblasts and endothelial cells, early, primary inflammatory changes in adipose tissue have consequently been identified to play a key role in systemic inflammation, atherosclerosis and cardiovascular death 9, 11.

It has been demonstrated that excess body fat, abdominal visceral fat, and larger waist circumference have been associated with accelerated arterial stiffening. Abdominal obesity has been associated with an adverse effect on blood vessels, independently of age, sex, blood pressure, fasting glucose and BMI. Combination of diabetes mellitus and abdominal obesity, but not overall obesity, has been associated with significant deterioration in terms of arterial stiffness parameters. Body fat distribution is one of the major determinants of metabolic health, and visceral adiposity has a stronger correlation with metabolic abnormalities and cardiovascular disease than subcutaneous adipose tissue 11.

The mean level of uric acid was significantly associated in both groups (table I) but the level more than 440 and 350 μmol/l in male and female respectively were not significantly associated in the groups with and without MetS (table III).

Serum uric acid (UA) is a strong predictor of stroke, coronary artery disease, and MetS, however, the definite role of uric acid in these diseases is still the subject of much discussion and debate because it is always accompanied with other risk factors such as diet, obesity, and dyslipidemia. Specifically, disputation exists about whether serum uric acid is a causative risk factor or only a coexisting marker of those pathologic processes 12.

However, few studies have investigated the predictive role of UA levels, and studies that investigate the relation between UA and MetS criteria in patients previously detected with cardiovascular risk are still scarce 13. Abreu da Silva, et al found   higher UA levels in subjects showing MetS when compared to those who did not 13 , previous epidemiologic studies have also shown increased serum UA levels in adults with MetS, as well as an association between increased UA levels and  oxidative stress, endothelial dysfunction, inflammation,  atherosclerosis, and increased risk of cardiovascular events 13-15.

BMI and total body fat, indicators of total adiposity; and waist circumference, indicator of central adiposity, showed an association with UA levels 13, therefore, the independence of the associations of hyperuricaemia with atherosclerosis and CVD has remained controversial 15, given that low-grade inflammation and insulin resistance are two important risks factors for MetS, uric acid may play a key role in the pathogenesis of MetS that is partially mediated by an inflammatory pathway, additionally,  uric acid might play a causal pathogenic role in the cause of MetS that could possibly be mediated by the inhibition of endothelial function 14, 15 .

Evidence from prospective and interventional studies of various populations suggests that gout and hyperuricaemia are independent risk factors for cardiovascular diseases, the mechanisms linking hyperuricaemia and gout with cardiovascular events are unclear but may include oxidative stress generated by xanthine oxidase (XO), the enzyme that catalyses the formation of urate, other explanations are a direct contribution to endothelial dysfunction and low-grade inflammation associated with increased urate levels and tophi 16.

During the recent years, an increasing number of publications have supported that allopurinol might have a benefit effect in a variety of cardiovascular diseases, and may provide a survival benefit among patients with hyperuricaemia. Indeed, allopurinol, a free radical scavenger, was found to improve both endothelial dysfunction and levels of some markers of oxidative stress 16.

The precise mechanism by which allopurinol exerts a beneficial effect on the cardiovascular system is poorly known, the drug is thought to act mainly through an increase in the bioavailability of endothelium derived nitric oxide, presumably by blocking the production of reactive oxygen species generated by the XO activity 16.

Recent data have also suggested that the cardiovascular benefit of allopurinol in patients with heart failure might be due to its urate lowering property, although this point is a matter of debate. Indeed, post hoc analyses of clinical trials have suggested that the reduced vascular risk afforded by therapeutics, such as atorvastatin and losartan which are not XOs, was due to their urate lowering property 16.

The pathophysiological mechanism by which the MetS increases cardiovascular risk remains under debate; earlier definitions by the World Health Organization and the EGIR emphasize the independent role of insulin resistance as the underlying component of the MetS. Insulin resistance progresses toward hyperinsulinemia and hyperglycemia, thus triggering peripheral vasoconstriction and sodium retention. Hepatic production of very low-density lipoprotein also increases, leading to hypertriglyceridemia, low HDL cholesterol, elevated apolipoprotein B, elevated small LDL cholesterol, and consequently, atherosclerosis, as a result of these lipid imbalances, individuals with the MetS typically exhibit a prothrombotic and proinflammatory state 17, 18.

Adipocytes secrete mediators including Tumor Necrotic Factor (TNF), leptin, adiponectin, and resistin, which lead to insulin resistance, it is postulated that central obesity causes systemic hypertension and dyslipidemia independently and through the induction of insulin resistance 18.

 At least half of the attributable risk in patients who end up with a thrombus or atherosclerosis is caused by this inflammatory response, major meta-analyses have shown that if you measure inflammation using the high-sensitivity C-reactive protein (hs-CRP) test, the magnitude of risk associated with hs-CRP is larger than the magnitude of risk of high blood pressure or high cholesterol 19, 20.

However, all of these parameters are associated with elevated levels of hs-CRP, an easily measured inflammatory biomarker that has proven to be a strong, independent predictor of both incident diabetes and incident cardiovascular disease, CRP levels also correlate with several other components such as fasting insulin, microalbuminuria, and impaired fibrinolysis that are not easily evaluated in usual clinical practice 19-21.

Rapidly evolving work now demonstrates that in addition to being a marker of innate immunity, CRP also has several direct effects at the level of the vessel wall, these observations, along with basic research into the inflammatory mechanisms of both diabetes and vascular dysfunction, provide strong evidence that insulin resistance and atherosclerosis share a common inflammatory basis, CRP, however, is also associated with several aspects of the MetS not easily ascertained in usual clinical practice, including fasting insulin, hypofibrinolysis, and microalbuminuria 19

MetS is associated with increased oxidative stress, furthermore, it appears that some component pathologies of the MetS contribute to a higher percentage of total oxidative stress than others; however, additional studies are needed to determine the exact contribution of individual components to total oxidative stress 4.

In this study no differences in the smoker in the groups were found, this can be explained by the prevalence of women in both groups, smoking and air pollution interact with the MetS which are not insufficiently assumed, but they clearly combined to deliver a cardiovascular risk factor which is greater than the sum of each of them.

Smokers and ex-smokers are more likely to have MetS than nonsmokers, both cigarette smoking and the MetS are strong independent risk factors for cardiovascular disease; however, smoking also potentiates the negative cardiovascular effects of the MetS. For example, MetS is associated with higher rates of cardiac events after acute myocardial infarction and smoking has an additive effect. These effects are largely mediated via Reactive Oxygen Species (ROS) generation 4.

There is an increasing interest in the development of novel biomarkers and imaging methods to refine CV risk prediction, The Emerging Risk Factors Collaboration has explored the benefit of including lipid-related markers [i.e. apolipoprotein B, apo-lipoprotein A-I, lipoprotein (a), or lipoprotein-associated phospholipase A2] in prognostic models for CV disease risk prediction 22-25.

MetS was commonly defined by the presence of obesity, diabetes, hypertension, and dyslipidemia, and these factors were involved in the mechanisms of insulin resistance, inflammation, and atherosclerosis, but does not  include other novel risk factor, the tools for prediction of cardiovascular risk include other different risk factors and both (MetS and scores for cardiovascular risk prediction) do not include other risk factors, with the improving of knowledge on  metabolic syndrome and the  prediction of cardiovascular risk the investigators have opportunities for the certain identification of novel biomarkers or risk factors that could be considered for  cardiovascular disease and the prevention of the cardiovascular diseases is based in the opportune identification in the primary health care with the biggest precision possible of the people with risk of developed cardiovascular disease 26-28.

Specific strengths of the present study were the use of nested case control study in a dynamic cohort design tended to results in estimated with lower bias and greater precision, controls matched to cases on classical matching factors (eg, age, sex); a limitation of this study was its small sample due to lack of laboratory reagents and suitable technology that did not allow to investigate more people.

 

CONCLUSIONS

In conclusion, this research showed relation statistically significant  between the MetS and the mean level of uric acid, the level of hs CRP higher than 1 mgl/dl, level of LDLc greater than 4.16 mmol/l, the global cardiovascular risk higher than 20% and the incidence of all cardiovascular events.

 

REFERENCES

1. Zhou H,  Guo Zr,  Hu Xs , Yu Lg,  Xu Bx , Wu M, et al. An exploratory analysis of dynamic change of metabolic syndrome in relation to the risk of developing cardiovascular disease in a chinese cohort. Iranian J Publ Health. 2012[cited 2013 Jan 14]; 41(4):26-34. Available in: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3481612/pdf/ijph-41-26.pdf

2. Zhu Z, Liu Y, Zhang C, Yuan Z, Zhang Q, Tang Fang, et al. Identification of cardiovascular risk components in urban chinese with metabolic syndrome and application to coronary heart disease prediction: A longitudinal study. PLoS ONE. 2013[cited 2014 Jul 10]; 8(12): 1-10. Available in: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3866125/pdf/pone.0084204.pdf

3. Zimmer P, George K, Alberti M, Serrano M. A new international diabetes federation worldwide definition of the metabolic syndrome: the rationale and the results. Rev Esp Cardiol. 2005[cited 6 Oct 2006]; 58(12):1371-1375. Available in:  http://www.revespcardiol.org/es/content/articulo/13082533/

4. Hutcheson R, Rocic P. The metabolic syndrome, oxidative stress, environment, and cardiovascular disease: The great exploration. Exp Diabetes Res. 2012[cited 27  Jun 2013];2012(2012):1-13. Available in: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3399393/

5. Simmons RK, Alberti KG, Gale EA, .Colagiuri S, Tuomilehto J, Qiao Q, et al. The metabolic syndrome: useful concept or clinical tool? Report of a WHO expert Consultation . Diabetologia. 2010. [cited 14 Jan 2011];53(4):600–605. Available in: http://link.springer.com/article/10.1007/s00125-009-1620-4

6. Pineda CA. Metabolic syndrome: definition, history, criterion. Colombia Med.2013[cited 14 Jan 2014];39(1):96-106.Available in: http://bibliotecadigital.univalle.edu.co/bitstream/10893/4753/1/Metabolic%20syndrome.pdf

7. D’Agostino RB, Pencina MJ,  Massaro, JM, Coady S. Cardiovascular disease risk assessment: Insights from Framingham. Glob Heart. 2013. [cited 2014 Oct 7]; 8(1): 11–23. Available in: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3673738/

8. D'Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM. General cardiovascular risk profile for use in primary care. The Framingham Heart Study. Circulation. 2008 [cited 15 Feb 2013]; 117(6):743-753.Available in: http://circ.ahajournals.org/cgi/content/full/117/6/743

9. Rohla M, Weiss TW. Adipose   tissue, inflammation and atherosclerosis. Clin Lipidology. 2014[cited 30 Jun 2014]; 9(1):71-81.Available in: http://www.futuremedicine.com/doi/pdf/10.2217/clp.13.80

10. Alegria Ezquerra E, Castellano Vázquez JM, Alegria Barrero A. Obesity, metabolic syndrome and diabetes: cardiovascular implications and therapy. Rev Esp Cardiol. 2008[cited 30 Mar   2012];61(7):752-764.Available in http://www.revespcardiol.org/es/obesity-metabolic-syndrome-and-diabetes/articulo/13123996/

11. Lukich A, Gavish D,  Shargorodsky M. Normal weight diabetic patients versus obese diabetics: Relation of overall and abdominal adiposity to vascular health. Cardiovasc Diabetol. 2014[cited  14 Dec  2014]; 13(141).Available in: http://www.medscape.com/viewarticle/835945_1

12. Peng TC, Wang CC, Wei Kao T, Hsin Chan J, Yang YH, Wen ChangY, et al. Relationship between hyperuricemia and lipid profile in US adults. Biomed Research International.2015 [cited 2015 Jul 10 ]:1-7.Available in: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299312/

13. Abreu da Silva H, Cardoso JC,  Bressan J,  Miranda H. Relation between uric acid and metabolic syndrome in subjects with cardiometabolic risk. Einstein. 2015 [cited 2015 May 19]13(2): 202-208. Available in: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1679-45082015005053194&lng=en&nrm=iso&tlng=en

14. Lee JK ,  Ryoo JH ,  Choi JM , Park SK. Serum uric acid level and the incidence of metabolic  syndrome in middle-aged Korean men: A 5-year follow up study. J Prev Med Public Health 2014 [cited 2015 Jan 14];47:317-326. Available in: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4263007/

15. Li LX, Dong XH, Li MF,  Zhan R, Li TT, ShenJ,et al. Serum uric acid levels are associated with hypertension and metabolic syndrome but not atherosclerosis in Chinese inpatients with type 2 diabetes. Journal of Hypertension 2015 [cited 2015 Jul 10]; 33(3): 482-490. Available in:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4309490/

16. Grimaldi-Bensouda L, Alperovitch A, Aubrum E, Danchin N, Rossigni M, Abenhaim L, et al. Impact of allopurinol on risk of myocardial infarction. Ann Rheum Dis. 2015.[cited 2015 Jul 10]; 74(5): 836-842. Available in: http://www.medscape.com/viewarticle/844859?src=wnl_edit_tpal

17. Miguel-Soca P. Predictores de riesgo cardiometabolico. Revista Finlay. 2015 [cited 2015 Jul 3]; 5(2):80-82. Disponible en: http://www.revfinlay.sld.cu/index.php/finlay/article/view/357

18. Mottillo F. Filion K, Genest J, Joseph J,Pilote L, Poirier P, et al. The metabolic syndrome and cardiovascular risk. A systematic review and meta-analysis.JACC.2010 [cited 2011 Jun 27]; 56(14):1113-32.Available in: http://www.sciencedirect.com/science/article/pii/S0735109710026380

19. Ridker PM, Buring JE,  Cook N, Rifai N. C-reactive protein, the metabolic syndrome, and risk of incident cardiovascular events An 8-year follow-up of 14 719 initially healthy american women. Circulation. 2003[cited 2005 Sep 19]; 107:391-397.Available in:  http://circ.ahajournals.org/content/107/3/391.full.pdf+html

20. The Emerging Risk Factors Collaboration. C - reactive protein, fibrinogen, and cardiovascular disease prediction. N Engl J Med. 2012[cited 2013 Jan 14]; 367(14): 1310–1320. Available in: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3714101/pdf/nihms488711.pdf

21. Vega J, Guimara M, Garces Y, Garcia Y, Vega L. Proteina C reactiva de alta sensibilidad y riesgo de enfermedad cardiovascular. CCM. 2015[cited 2015 Jul 10]; 19(2):190-201. Disponible en: http://www.revcocmed.sld.cu/index.php/cocmed/article/view/978/621

22. Charakida M, Masi S, Deanfield JE. The Year in Cardiology 2012: focus on cardiovascular disease prevention. Eur Heart J. 2013 [cited 2014 Nov 21]; 34: 314–7. Available in http://eurheartj.oxfordjournals.org/content/ehj/early/2013/01/02/eurheartj.ehs429.full.pdf

23. Nordet P, Mendis M, Dueñas A, de la Noval R, Armas N. Total cardiovascular risk assessment and management using two prediction tools, with and without blood cholesterol. MEDICC Review.2013 [cited 2014 Nov 26]; 15(4). Available in: http://www.scielosp.org/scielo.php?pid=S1555-79602013000400009&script=sci_arttext

24. Aljutaili M, Becker C, Witt S, Holle R, Leidl L. Should health insurers target prevention of cardiovascular disease?: A cost-effectiveness analysis of an individualized programme in Germany based on routine data. BMC Health Services Research.2014 [cited  2014 Nov 26]; 14:263.Available in: http://www.biomedcentral.com/1472-6963/14/263

25. Vega J, Guimará M, Vega L. Riesgo cardiovascular, una herramienta útil para la prevención de las enfermedades cardiovasculares. Rev Cubana Med Gen Integr.2011 [cited 2013 Dec 12]; 27(1):91-97. Available in: http://scielo.sld.cu/pdf/mgi/v27n1/mgi10111.pdf

26. Vega J, Guimara M, Garces Y, Vega L, Rivas M. Predicción del riesgo coronario y cardiovascular global en atención primaria de salud. CCM. 2015 [cited 2015 Nov 27] 19(2):202-211. Available in: http://www.revcocmed.sld.cu/index.php/cocmed/article/download/979/622

27. Tarragó E, Miguel Soca PE, Cruz L, Santiesteban Y.  Factores de riesgo y prevención de la enfermedad isquémica. CCM. 2012 [cited 2014 Nov 20]; 16(2). Disponible en: http://www.revcocmed.sld.cu/index.php/cocmed/article/view/505

28. Rivas Vázquez D, Miguel Soca PE, Llorente Columbié Y, Marrero Ramírez GM. Comportamiento clínico y epidemiológico del síndrome metabólico en adultos. Rev Cubana Med Gen Integr. 2015  [citado  2016  Mar  09];  31(3). Available in: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S0864-21252015000300001&lng=es

 

 

Recibido: 15 de julio de 2015
Aprobado: 14 de marzo de 2016

 

 

Jorge Vega Abascal, MD, Msc. Jose Avila Serrano Teaching Polyclinic.  Velasco. Holguin, Cuba
Email: vegabascalhlg@infomed.sld.cu



Copyright (c) 2021 Jorge Vega Abascal, Mayra Rosa Guimara Mosqueda, Luis Vega Abascal

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Esta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial 4.0 Internacional.