The association of subclinical atherosclerosis with prediabetes is stronger in people with dyslipidaemia than in those with normoglycaemia: A cross-sectional study in Chinese adults

Metabolic health phenotype better predicts subclinical atherosclerosis than body mass index-based obesity phenotype in the non-alcoholic fatty liver disease population

Background

Non-alcoholic fatty liver disease (NAFLD), especially lean NAFLD is associated with an increased risk of atherosclerotic cardiovascular disease (CVD). It is not currently known which clinical phenotypes of NAFLD contribute most to individual subclinical atherosclerosis risk. We examined the relationship between body mass index (BMI), the metabolically healthy status, and subclinical atherosclerosis in the NAFLD population.

Methods

Data from asymptomatic NAFLD subjects who participated in a routine health check-up examination were collected. Participants were stratified by BMI (cutoff values: 24.0-27.9 kg/m2 for overweight and ≥28.0 kg/m2 for obesity) and metabolic status, which was defined by Adult Treatment Panel III criteria. Subclinical atherosclerosis was evaluated by brachial-ankle pulse wave velocity (baPWV) in 27,738 participants and by carotid plaque in 14,323 participants.

Results

Within each BMI strata, metabolically unhealthy subjects had a significantly higher prevalence of subclinical atherosclerosis than metabolically healthy subjects, whereas fewer differences were observed across subjects within the same metabolic category. When BMI and metabolic status were assessed together, a metabolically unhealthy status was the main contributor to the association of clinical phenotypes with the subclinical atherosclerosis burden (all p < 0.001). When BMI and metabolic abnormalities were assessed separately, the incidence of subclinical disease did not increase across BMI categories; however, it increased with an increase in the number of metabolic abnormalities (0, 1, 2 and ≥3).

Conclusion

A metabolically healthy status in NAFLD patients was closely correlated with subclinical atherosclerosis, beyond that of the BMI-based obesity phenotype. The application of metabolic phenotyping strategies could enable more precise classification in evaluating cardiovascular risk in NAFLD.

The relation between atherogenic index of plasma and cardiovascular outcomes in prediabetic individuals with unstable angina pectoris

BACKGROUND

The atherogenic index of plasma (AIP) is a novel biomarker associated with atherosclerosis, and an important risk factor for atherosclerosis, but its relation with cardiovascular prognosis in prediabetic patients with unstable angina pectoris (UAP) is still uncertain.

METHODS

This study included 1096 prediabetic patients with UAP who were subjected to follow-up for a maximum of 30 months, with cardiac death, refractory angina, and non-fatal myocardial infarction (MI) being the primary cardiovascular endpoints.

RESULTS

A significantly increased AIP was observed for the group with primary cardiovascular endpoints. Kaplan-Meier curves corresponding to these endpoints revealed pronounced differences between these two AIP groups (Log-rank P < 0.001). Multivariate Cox proportional hazards analyses highlighted AIP as being independent related to this primary endpoint (HR 1.308, 95% CI: 1.213-1.412, P < 0.001). AIP addition to the baseline risk model improved the prediction of the primary endpoint (AUC: baseline model, 0.622, vs. baseline model + AIP, 0.739, P < 0.001).

CONCLUSIONS

AIP could be used to predict cardiovascular events in prediabetic individuals with UAP.

Phenotyping the Prediabetic Population-A Closer Look at Intermediate Glucose Status and Cardiovascular Disease

Even though the new thresholds for defining prediabetes have been around for more than ten years, there is still controversy surrounding the precise characterization of this intermediate glucose metabolism status. The risk of developing diabetes and macro and microvascular disease linked to prediabetes is well known. Still, the prediabetic population is far from being homogenous, and phenotyping it into less heterogeneous groups might prove useful for long-term risk assessment, follow-up, and primary prevention. Unfortunately, the current definition of prediabetes is quite rigid and disregards the underlying pathophysiologic mechanisms and their potential metabolic progression towards overt disease. In addition, prediabetes is commonly associated with a cluster of risk factors that worsen the prognosis. These risk factors all revolve around a common denominator: inflammation. This review focuses on identifying the population that needs to be screened for prediabetes and the already declared prediabetic patients who are at a higher risk of cardiovascular disease and require closer monitoring.