Influence of chronic kidney disease on coronary plaque components in coronary artery disease patients with both diabetes mellitus and hypertension

Dynamic natural components and morphological changes in nonculprit subclinical atherosclerosis in patients with acute coronary syndrome and mild chronic kidney disease at the 1-year follow-up and clinical significance at the 5-year follow-up

INTRODUCTION

The natural outcome of coronary plaque in acute coronary syndrome (ACS) patients with chronic kidney disease (CKD) is unique, which can be analyzed quantitatively by optical flow ratio (OFR) software.

METHODS

A total of 184 ACS patients with at least one nonculprit subclinical atherosclerosis (NSA) detected by optical coherence tomography (OCT) at baseline and 1-year follow-up were divided into non-CKD group (n = 106, estimated glomerular filtration rate (eGFR)> 90 mL/(min×1.73 m2)) and mild CKD group (n = 78, 60≤eGFR<90 mL/(min×1.73 m2)). Changes of normalized total atheroma volume (TAVn) of NSA was the primary endpoint at the 1-year follow-up.

RESULTS

Patients with mild CKD showed more TAVn progression of NSA than non-CKD (p = 0.019) from baseline to the 1-year follow-up, which was mainly due to an increase in calcium TAVn (p<0.001). The morphological change in the maximal calcification thickness (p = 0.026) was higher and the change in the distance from the calcified surface to the contralateral coronary media membrane (ΔC-to-M) at the maximal cross-sectional calcium area was lower (p<0.001) in mild CKD group than in non-CKD group. Mild CKD had more NSA related MACEs at the 5-year follow-up than non-CKD (30.8% vs. 5.8%, p = 0.045).

CONCLUSIONS

Mild CKD patients had more plaque progression of NSA which showed the increase of calcium component with more protrusion into the lumen morphologically at the 1-year follow-up and a higher corresponding incidence of NSA-related MACEs at the 5-year follow-up.

TRIAL REGISTRATION

Clinical Trial registration ClinicalTrials.gov. NCT02140801. https://classic.clinicaltrials.gov/ct2/show/NCT02140801.

[Renal insufficiency and cardiovascular risk]

Patients with chronic renal insufficiency often show symptoms that are atypical for cardiovascular problems. The correct interpretation of the symptoms is crucial in order to correctly assess the risk of a heart-related emergency and to take preventive measures and initiate the right therapy. Biomarkers such as NT-proBNP, troponin T or hsCRP (highly sensitive CRP) are independent predictors of mortality, but do not replace instrument-based diagnostics. Patients with renal insufficiency often have stiff vessels which, due to the premature reflection of the pulse wave, can lead to left ventricular dysfunction and ultimately to heart failure.

Unsupervised machine learning based on clinical factors for the detection of coronary artery atherosclerosis in type 2 diabetes mellitus

BACKGROUND

Coronary atherosclerosis can lead to serious cardiovascular events. In type 2 diabetes (T2DM) patients, the effects of clinical factors on coronary atherosclerosis have not been fully elucidated. We used a clustering method to distinguish the population heterogeneity of T2DM and the differences in coronary atherosclerosis evaluated on coronary computed tomography angiography (CCTA) among groups and to facilitate clinical management.

METHODS

Clinical data from 1157 T2DM patients with coronary atherosclerosis who underwent CCTA in our hospital from January 2018 to September 2021 were retrospectively collected. The coronary artery segment plaque type and stenosis, the number of involved vessels, the segment involvement score (SIS) and the segment stenosis score (SSS) were evaluated and calculated. Unsupervised clustering analysis based on clinical information was used (cluster 1: n = 463; cluster 2: n = 341; cluster 3: n = 353). The association of coronary plaque characteristics with cluster groups was evaluated.

RESULTS

The clinical data among the three groups were different in several aspects: (1) Cluster 1 had the least male patients (41.7%), the lowest proportion of patients with smoking (0%) or alcohol history (0.9%), and the lowest level of serum creatinine (74.46 ± 22.18 µmol/L); (2) Cluster 2 had the shortest duration of diabetes (7.90 ± 8.20 years) and was less likely to be treated with diabetes (42.2%) or statins (17.6%) and (3) Cluster 3 was the youngest (65.89 ± 10.15 years old) and had the highest proportion of male patients (96.6%), the highest proportion of patients with smoking (91.2%) and alcohol (59.8%) history, the highest level of eGFR (83.81 ± 19.06 ml/min/1.73m²), and the lowest level of HDL-C (1.07 ± 0.28 mmol/L). The CCTA characteristics varied with different clusters: (1) Cluster 1 had the largest number of segments with calcified plaques (2.43 ± 2.46) and the least number of segments with mixed plaques (2.24 ± 2.59) and obstructive stenosis (0.98 ± 2.00); (2) Cluster 1 had the lowest proportion of patients with mixed plaques (68%) and obstructive stenosis (32.2%); (3) Cluster 3 had more segments with noncalcified plaques than cluster 1 (0.63 ± 1.02 vs 0.40 ± 0.78, P < 0.05) and the highest proportion of patients with noncalcified plaques (39.9%) and (4) There was no significant difference in the extent of coronary plaques among the three clusters.

CONCLUSIONS

The unsupervised clustering method could address T2DM patients with heterogeneous clinical indicators and identify groups with different types of coronary plaque and degrees of coronary stenosis. This method has the potential for patient stratification, which is essential for the clinical management of T2DM patients with coronary atherosclerosis.

Gene polymorphism associated with angiotensinogen (M235T), endothelial lipase (584C/T) and susceptibility to coronary artery disease: a meta-analysis

OBJECTIVE

To explore the association between the variant M235T locus of angiotensinogen (AGT) gene, 584C/T locus of Endothelial lipase (EL) gene, and coronary artery disease (CAD) by meta-analysis.

METHODS

The case-control studies on the association between AGT/EL gene polymorphism and CAD were collected through searching PubMed, Excerpta Medica Database (EMBASE), Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang databases up to 1 March 2020. Stata 15.0 software was used for analysis.

RESULTS

A total of 29 articles met the inclusion criteria. After analyzing, it was found that the M235T polymorphism of AGT gene was associated with the occurrence of CAD. In the allele model (T vs. M), OR = 1.38 (P<v0.05). In other heredity, there was also statistical significance. Subgroup analysis indicated that except the heterozygous genetic model of the Chinese population, other genetic models of the Caucasian and Chinese population were also statistically significant. The 584C/T polymorphism of EL gene was associated with the occurrence of CAD, with OR = 0.83 (P<0.05) in the allele model (T vs. C) and OR = 0.80 (P<0.05) in the dominant gene model. Also, in the allele model of Caucasian subgroup, OR = 0.83 (P<0.05), while in Asian subgroup, there was no statistically significant genetic model.

CONCLUSION

AGT M235T and EL 584C/T polymorphisms are associated with CAD susceptibility. The genotype TT, TC or allele T of AGT M235T and genotype CC or allele C of EL 584C/T might be the genetic risk factors for the development of CAD.

Atherosclerotic Coronary Artery Disease in Patients With Cardiometabolic Syndrome

Major risk factors for cardiovascular disease (CVD) include aging, gender, smoking, family history and cardiometabolic syndrome. The relative residual risks for CVD after statin treatment for primary and secondary prevention have been reported by several large-scale randomized clinical trials. Statin treatment appears to prevent one-third of the onset and progression of CVD, but not the remaining two-thirds. There are three major problems regarding the residual risk of CVD: 1) Insufficient reduction of low-density lipoprotein cholesterol levels; 2) Low levels of high-density lipoprotein cholesterol and elevated triglyceride; and 3) Insufficient control of other risk factors (high blood pressure, obesity, metabolic syndrome, type 2 diabetes, etc.). Thus, a multifaceted preventive approach should be needed to prevent CVD after statin treatment.