Impact of pericoronary adipose tissue inflammation on left ventricular hypertrophy and regional physiological indices in stable coronary artery disease patients with preserved systolic function

Impact of C-Reactive Protein on Long-Term Cardiac Events in Stable Coronary Artery Disease Patients with Chronic Kidney Disease

AIM

Chronic inflammation is associated with atherosclerosis development. Chronic kidney disease (CKD) is an independent risk factor for cardiovascular events and is associated with chronic inflammation. We aimed to investigate the influence of C-reactive protein (CRP), an important marker of inflammation, on the clinical outcomes of patients with CKD and stable coronary artery disease (CAD) undergoing percutaneous coronary intervention (PCI).

METHODS

Among patients with stable CAD and CKD who underwent PCI, 516 patients whose CRP levels were available before the PCI procedure were identified. The patients were divided into two groups according to the CRP levels: those with CRP ≥ 2.0 mg/L (high-CRP group) and those with CRP ＜2.0 mg/L (low-CRP group). The primary endpoint of this study was the occurrence of major adverse cardiac events (MACE), defined as a composite of cardiac death, myocardial infarction, and unplanned revascularization.

RESULTS

Overall, the mean age of the patients was 72.5±9.7 years, and 20.7% were female. The median CRP level was 1.43 mg/L (0.6-4.9 mg/L). The median follow-up period was 3.6 years. The occurrence of MACE was significantly higher in the high-CRP group than in the low-CRP group (log-rank p＜0.001). Notably, the incidence rate of cardiac death was significantly higher in the high-CRP group (log-rank p＜0.001). According to the multivariable analysis, CRP level ≥ 2.0 mg/L was found to be a significant predictor of MACE (hazard ratio [HR]: 1.54, 95% confidence interval [CI]: 1.04-2.28, p=0.003), as well as estimated glomerular filtration rate (HR: 0.98, 95% CI: 0.97-0.99, p＜0.01).

CONCLUSION

High-CRP levels adversely affect long-term cardiac events in patients with stable CAD and CKD.

Excess risk of cardiovascular events in patients in the United States vs. Japan with chronic kidney disease is mediated mainly by left ventricular structure and function

While patients receiving dialysis therapy in the United States are more likely to develop cardiovascular disease (CVD) than those in Japan, direct comparisons of patients with predialysis chronic kidney disease (CKD) are rare. To study this, we compared various outcomes in patients with predialysis CKD using data from the Chronic Renal Insufficiency Cohort (CRIC) and CKD Japan Cohort (CKD-JAC) studies and determined mediators of any differences. Candidate mediators included left ventricular (LV) indices assessed by echocardiography. Among 3125 CRIC and 1097 CKD-JAC participants, the mean LV mass index (LVMI) and ejection fraction (EF) were 55.7 and 46.6 g/m2 and 54% and 65%, respectively (both significant). The difference in body mass index (32 and 24 kg/m2, respectively) largely accounted for the differences in LVMI and C-reactive protein levels across cohorts. Low EF and high LVMI were significantly associated with subsequent CVD in both cohorts. During a median follow-up of five years, CRIC participants were at higher risk for CVD (adjusted hazard ratio [95% confidence interval]: 3.66 [2.74-4.89]) and death (4.69 [3.05-7.19]). A three-fold higher C-reactive protein concentration and higher phosphate levels in the United States cohort were moderately strong mediators of the differences in CVD. However, echocardiographic parameters were stronger mediators than these laboratory measures. LVMI, EF and their combination mediated the observed difference in CVD (27%, 50%, and 57%, respectively) and congestive heart failure (33%, 62%, and 70%, respectively). Thus, higher LV mass and lower EF, even in the normal range, were found to be predictive of CVD in CKD.

Evaluation of pericoronary adipose tissue attenuation on CT

Pericoronary adipose tissue (PCAT) is the fat deposit surrounding coronary arteries. Although PCAT is part of the larger epicardial adipose tissue (EAT) depot, it has different pathophysiological features and roles in the atherosclerosis process. While EAT evaluation has been studied for years, PCAT evaluation is a relatively new concept. PCAT, especially the mean attenuation derived from CT images may be used to evaluate the inflammatory status of coronary arteries non-invasively. The most commonly used measure, PCAT_MA, is the mean attenuation of adipose tissue of 3 mm thickness around the proximal right coronary artery with a length of 40 mm. PCAT_MA can be analyzed on a per-lesion, per-vessel or per-patient basis. Apart from PCAT_MA, other measures for PCAT have been studied, such as thickness, and volume. Studies have shown associations between PCAT_MA and anatomical and functional severity of coronary artery disease. PCAT_MA is associated with plaque components and high-risk plaque features, and can discriminate patients with flow obstructing stenosis and myocardial infarction. Whether PCAT_MA has value on an individual patient basis remains to be determined. Furthermore, CT imaging settings, such as kV levels and clinical factors such as age and sex affect PCAT_MA measurements, which complicate implementation in clinical practice. For PCAT_MA to be widely implemented, a standardized methodology is needed. This review gives an overview of reported PCAT methodologies used in current literature and the potential use cases in clinical practice.

Relationship of body fat and left ventricular hypertrophy with the risk of all-cause death in patients with coronary artery disease

BACKGROUND

Left ventricular hypertrophy (LVH) is prevalent in obese individuals. Besides, both of LVH and obesity is associated with subclinical LV dysfunction. The study aims to investigate the interplay between body fat and LVH in relation to all-cause death in patients with coronary artery disease (CAD).

METHODS

In this retrospective cohort study, a total of 2243 patients with angiographically proven CAD were included. Body fat and LV mass were calculated using established formulas. Patients were grouped according to body fat percentage and presence or absence of LVH. Cox-proportional hazard models were used to observe the interaction effect of body fat and LVH on all-cause death.

RESULTS

Of 2243 patients enrolled, 560 (25%) had a higher body fat percentage, and 1045 (46.6%) had LVH. After a median follow-up of 2.2 years, the cumulative mortality rate was 8.2% in the group with higher body fat and LVH, 2.5% in those with lower body fat and no LVH, 5.4% in those with higher body fat and no LVH, and 7.8% in those with lower body fat and LVH (log-rank P < 0.001). There was a statistically significant interaction between body fat percentage and LVH ( P interaction was 0.003). After correcting for confounding factors, patients with higher body fat and LVH had the highest risk of all-cause death (HR = 3.49, 95% CI: 1.40-8.69, P = 0.007) compared with those with lower body fat and no LVH; in contrast, patients with higher body fat and no LVH had no statistically significant difference in risk of death compared with those with lower body fat and no LVH (HR = 2.03, 95% CI: 0.70-5.92, P = 0.195).

CONCLUSION

A higher body fat percentage was associated with a different risk of all-cause death in patients with CAD, stratified by coexistence of LVH or not. Higher body fat was significantly associated with a greater risk of mortality among patients with LVH but not among those without LVH.

Impact of the distribution of epicardial and visceral adipose tissue on left ventricular diastolic function

Although epicardial adipose tissue (EAT) and abdominal visceral adipose tissue (VAT) can contribute to left ventricular diastolic dysfunction (LVDD), the impact of these distribution has not been fully understood. A total of 235 patients who underwent cardiac computed tomography angiography and Doppler echocardiography was included in this study. We evaluated the association of indexed EAT volume and VAT area with septal and lateral early diastolic mitral annular velocity (e'). The VAT area index was significantly associated with septal and lateral e' velocity after adjusted for conventional cardiovascular risk factors and obstructive coronary artery disease (β-estimate; - 0.015 and - 0.019, both p = 0.01). The natural logarithmic EAT volume index (ln EAT volume index) also showed a significant association with septal and lateral e' (β-estimate; - 1.72 and - 0.99, both p < 0.01). The significant association of ln EAT volume index with septal and lateral e' was observed even after adjusting for VAT area index (β-estimate; - 0.79 and - 1.52, both p < 0.03). In the subgroup analysis, there were significant association of ln EAT volume index with both septal and lateral e' in the lower VAT group (β-estimate; - 1.40 and - 1.53, both p < 0.03) and with lateral e' in the higher VAT group (β-estimate - 1.64, p = 0.006). In contrast, ln EAT volume index was not associated with septal e' in the higher VAT group (p = 0.98). EAT accumulation was significantly associated with LVDD independently of obstructive coronary artery disease and abdominal VAT. The impact of EAT on LVDD may vary depending on the amount of abdominal VAT.

Prognostic value of pericoronary inflammation and unsupervised machine-learning-defined phenotypic clustering of CT angiographic findings

BACKGROUND

Pericoronary adipose tissue attenuation expressed by fat attenuation index (FAI) on coronary CT angiography (CCTA) reflects pericoronary inflammation and is associated with cardiac mortality.

OBJECTIVE

The aim of this study was to define the sub-phenotypes of coronary CCTA-defined plaque and whole vessel quantification by unsupervised machine learning (ML) and its prognostic impact when combined with pericoronary inflammation.

METHODS

A total of 220 left anterior descending arteries (LAD) with intermediate stenosis who underwent fractional flow reserve (FFR) measurement and CCTA were studied. After removal of outcome and FAI data, the phenotype heterogeneity of CCTA-defined plaque and whole vessel quantification was investigated by unsupervised hierarchical clustering analysis based on Ward's method. Detailed features of CCTA findings were assessed according to the clusters (CS1 and CS2). Major adverse cardiac events (MACE)-free survivals were assessed according to the stratifications by FAI and the clusters.

RESULTS

Compared with CS2 (n = 119), CS1 (n = 101) were characterized by greater vessel size, increased plaque volume, and high-risk plaque features. FAI was significantly higher in CS1. ROC analyses revealed that best cut-off value of FAI to predict MACE was -73.1. Kaplan-Meier analysis revealed that lesions with FAI ≥ -73.1 had a significantly higher risk of MACE. Multivariate Cox proportional hazards regression analysis revealed that age, FAI ≥ -73.1, and the clusters were independent predictors of MACE.

CONCLUSION

Unsupervised hierarchical clustering analysis revealed two distinct CCTA-defined subgroups and discriminated by high-risk plaque features and increased FAI. The risk of MACE differs significantly according to the increased FAI and ML-defined clusters.