Comparison of coronary heart disease risk among four diagnostic definitions of metabolic syndrome

Plasma metabolic fingerprints for large-scale screening and personalized risk stratification of metabolic syndrome

Direct diagnosis and accurate assessment of metabolic syndrome (MetS) allow for prompt clinical interventions. However, traditional diagnostic strategies overlook the complex heterogeneity of MetS. Here, we perform metabolomic analysis in 13,554 participants from the natural cohort and identify 26 hub plasma metabolic fingerprints (PMFs) associated with MetS and its early identification (pre-MetS). By leveraging machine-learning algorithms, we develop robust diagnostic models for pre-MetS and MetS with convincing performance through independent validation. We utilize these PMFs to assess the relative contributions of the four major MetS risk factors in the general population, ranked as follows: hyperglycemia, hypertension, dyslipidemia, and obesity. Furthermore, we devise a personalized three-dimensional plasma metabolic risk (PMR) stratification, revealing three distinct risk patterns. In summary, our study offers effective screening tools for identifying pre-MetS and MetS patients in the general community, while defining the heterogeneous risk stratification of metabolic phenotypes in real-world settings.

Potential of four definitions of metabolic syndrome to discriminate individuals with different 10-year cardiovascular disease risk scores: a cross-sectional analysis of an Iranian cohort

OBJECTIVE

We aimed to reveal the potential of four different metabolic syndrome (Mets) definitions to differentiate subjects according to 10-year risk of cardiovascular disease.

DESIGN

A cross-sectional analysis of a prospective cohort.

SETTING

This study used baseline data from the Shiraz Heart Study, a prospective cohort study in Shiraz, Iran. Participants were screened against Mets definitions including modified WHO, National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), American Heart Association (AHA) and International Diabetes Federation (IDF). Also, Framingham risk score (FRS) and atherosclerotic cardiovascular disease (ASCVD) risk score were determined for each participant.

PARTICIPANTS

A total number of 7225 participants of both genders entered the study. They were selected through defined family physician centres in different geographical areas. Urban residents with no migration plan were included. Those who were far from study centres or with disabilities that made them incapable to cooperate were excluded.

RESULTS

Participants were 47.68% (N=3445) male with the mean age of 52.13±8.00 years. The number of subjects with Mets identified by WHO was the lowest (N=1676), while the percentage of subjects with high risk score was the highest, 17.1% (N=282) in FRS and 9.8% (N=162) in ASCVD risk score. There were statistically significant differences in the mean risk scores between participants with and without Mets according to AHA, WHO and NCEP ATP III definitions (p<0.001). In IDF definition, the risk scores of subjects with Mets were not statistically different compared with peers without Mets, neither based on FRS (p=0.247) nor ASCVD risk score (p=0.193).

CONCLUSIONS

IDF was not the appropriate definition for discrimination of subjects with Mets and/or those at high risk of future cardiovascular events. AHA, WHO and NCEP ATP III definitions were effective to discriminate subjects with Mets from peers without Mets.

Effect of metabolic syndrome on coronary heart disease in rural minorities of Xinjiang: a retrospective cohort study

Background

Metabolic syndrome is diagnosed by a cluster of risk factors that associated with an increased risk of coronary heart disease (CHD). We aimed to explore the impact of and interactions between individual metabolic syndrome components on the risk of CHD in Xinjiang.

Methods

The baseline population included 7635 participants. The degree to which the components increase the risk of CHD and the multiplicative interactions between them were assessed using hazard ratios (HRs) and 95% confidence intervals (CIs). Additive interactions were appraised by the relative excess risk due to interaction, synergy index (SI), and attributable proportion of interaction.

Results

A total of 304 CHD patients were enrolled from rural residents of Xinjiang. Elevated blood pressure (HR 1.81; 95% CI 1.35–2.44) and elevated fasting blood glucose (FBG) (HR 1.82; 95% CI 1.38–2.38) increased the risk of CHD after adjustment for confounding factors. We found a positive additive interaction (SI 1.14; 95% CI 0.51–2.51) between elevated blood pressure and elevated FBG, but none were significant. As the number of components increased, the risk of CHD increased. The combinations of [high triglycerides (TG) + low high-density lipoprotein cholesterol (HDL-C) + elevated FBG + large waistline] (HR 4.26; 95% CI 1.43–12.73) and [elevated blood pressure + elevated FBG + low HDL-C + large waistline] (HR 1.82; 95% CI 1.38–2.38) increased the risk of CHD.

Conclusions

We provide evidence that elevated blood pressure and elevated FBG are independent risk factors for CHD and it might be necessary to maintain the normal waistline for preventing CHD.

Comparison of coronary heart disease risk assessments among individuals with metabolic syndrome using three diagnostic definitions: a cross-sectional study from China

OBJECTIVE

Metabolic syndrome (MetS) is a notable risk factor of coronary heart disease (CHD). However, there are differences in the methods used to define MetS. The purpose of this study was to determine which MetS definition most fully reflects the 10-year probability of CHD based on the Framingham risk algorithm.

DESIGN

Cross-sectional study.

SETTING

Data were obtained from the China Health and Nutrition Survey and the Influencing Factors of Chronic Diseases Survey conducted among residents of Nanshan District in Shenzhen, China.

PARTICIPANTS

In total, 1721 participants aged 20-80 years were included in this study.

METHODS

MetS was diagnosed according to the criteria of the National Cholesterol Education Program's Adult Treatment Panel (revised NCEP-ATP III), the International Diabetes Federation (IDF) and the Chinese Diabetes Society (CDS). The NCEP-ATP III algorithm was used to calculate the Framingham risk score, and the Framingham risk score was used to define the probability of developing CHD within 10 years either as low (<6%), moderate (6%-10%), moderately high (10%-20%) or high (>20%). Chi-square tests with or without the Bonferroni correction were used to compare the differences in the distribution of the 10-year estimated risk of developing CHD among the three definitions.

RESULTS

Compared with the other definitions, the revised NCEP-ATP III criteria identified more participants (30.96%, 95% CI 28.8% to 33.2%) as having MetS, while the CDS criteria showed the highest 10-year probability of developing CHD. The 10-year probability of developing CHD in the participants with MetS was significantly higher than that in the participants without MetS (CDS: χ²=157.65, revised ATP III: χ²=45.17, IDF: χ²=306.15, all p<0.001), and all definitions more fully reflect the CHD risk in men than in women (revised NCEP-ATP III: χ²=72.83; IDF: χ²=63.60; CDS: χ²=23.84; all p<0.001).

CONCLUSIONS

This study demonstrates the differences in the prevalence and distribution of the 10-year estimated risk of developing CHD based on the definition of MetS. A significant finding of this study is that the MetS definitions have better performance for men than for women. Further studies in China, especially longitudinal studies, are needed to determine which definition of MetS is best suited for predicting CHD risk.

Sex-specific clustering of metabolic risk factors and their association with incident cardiovascular diseases: A population-based prospective study

BACKGROUND AND AIMS

We identified distinct patterns of metabolic risk factors (MRF), and examined their association with subsequent cardiovascular disease (CVD) risk.

METHODS

The study sample included 8113 participants (45% men) aged ≥30 years. Self-organizing map (SOM) was applied to clustering of five dichotomized MRF in men and women. MRF were included: low estimated glomerular filtration rate (eGFR), high fasting plasma glucose (FPG), high total cholesterol (TC), high systolic blood pressure (SBP) and high body mass index (BMI). The association between clusters membership and age, education, smoking status, physical activity level and family history (FH) of premature CVD was estimated using multinomial logistic regression. Cox regression was used to estimate the relation of each cluster with CVD events.

RESULTS

SOM identified seven distinct clusters of MRF in both men and women. About 35 and 44% of men and women, respectively, had ≥3 MRF. Among men, MRF were clustered in those with older age, low physical activity, lower education and FH of premature CVD; while, among women, clustering was observed in past smoker, those with older age and positive FH of premature CVD. In the male population, a cluster with 100% high SBP and high FPG, had the highest risk for CVD events. However, among women, two clusters, each with 100% high FPG, yielded the highest and similar risk for CVD.

CONCLUSIONS

SOM identified multiple patterns of MRF in the Iranian population. The results may be useful for targeting efforts to promote strategies to reduce the risk of CVD in the Iranian population.

Cardiovascular Risk Stratification in Patients with Metabolic Syndrome Without Diabetes or Cardiovascular Disease: Usefulness of Metabolic Syndrome Severity Score

INTRODUCTION

The estimated cardiovascular risk determined by the different risk scores, could be heterogeneous in patients with metabolic syndrome without diabetes or vascular disease. This risk stratification could be improved by detecting subclinical carotid atheromatosis.

AIMS

To estimate the cardiovascular risk measured by different scores in patients with metabolic syndrome and analyze its association with the presence of carotid plaque.

METHODS

Non-diabetic patients with metabolic syndrome (Adult Treatment Panel III definition) without cardiovascular disease were enrolled. The Framingham score, the Reynolds score, the new score proposed by the 2013 ACC/AHA Guidelines and the Metabolic Syndrome Severity Calculator were calculated. Prevalence of carotid plaque was determined by ultrasound examination. A Receiver Operating Characteristic analysis was performed.

RESULTS

A total of 238 patients were enrolled. Most patients were stratified as "low risk" by Framingham score (64%) and Reynolds score (70.1%). Using the 2013 ACC/AHA score, 45.3% of the population had a risk ≥7.5%. A significant correlation was found between classic scores but the agreement (concordance) was moderate. The correlation between classical scores and the Metabolic Syndrome Severity Calculator was poor. Overall, the prevalence of carotid plaque was 28.2%. The continuous metabolic syndrome score used in our study showed a good predictive power to detect carotid plaque (area under the curve 0.752).

CONCLUSION

In this population, the calculated cardiovascular risk was heterogenic. The prevalence of carotid plaque was high. The Metabolic Syndrome Severity Calculator showed a good predictive power to detect carotid plaque.