Dataset Information

Relationship Between Immunoinflammation and Coronary Physiology Evaluated by Quantitative Flow Ratio in Patients With Coronary Artery Disease

ABSTRACT: Background: The association between coronary physiology and immunoinflammation has not been investigated. We performed a retrospective study using quantitative flow ratio (QFR) to evaluate the interaction between immunoinflammatory biomarkers and coronary physiology. Methods: A total of 172 patients with CAD who underwent coronary arteriography (CAG) and QFR were continuously enrolled from May 2020 to February 2021. As a quantitative indicator of coronary physiology, QFR can reflect the functional severity of coronary artery stenosis. The target vessel measured by QFR was defined as that with the most severe lesions. Significant coronary anatomical stenosis was defined as 70% stenosis in the target vessel. Results: Compared with the QFR > 0.8 group, interleukin (IL)-6, IL-10, tumor necrosis factor (TNF)-α, and interferon (IFN)-γ were increased and CD3+ and CD4+ T lymphocyte counts were decreased in the QFR ≤ 0.8 group. In addition, patients with DS ≤ 70% had higher IL-6, IL-10, and TNF-α levels and decreased CD3+ and CD4+ T lymphocyte counts than those with DS > 70%. Logistic regression analysis indicated IL-6 to be an independent predictor of significant coronary functional and anatomic stenosis (odds ratio, 1.125; 95% CI, 1.059–1.196; P < 0.001). Receiver operating characteristic (ROC) analyses showed that IL-6 > 6.36 was predictive of QFR ≤ 0.8 of the target vessel. The combination of IL-6, IL-10 and CD4 improved the value for predicting QFR ≤ 0.8 of the target vessel (AUC, 0.737; 95% CI, 0.661–0.810). Conclusion: Among immunoinflammatory biomarkers, IL-6 was independently associated with a higher risk of QFR ≤ 0.8 of the target vessel. The combination of immunoinflammatory biomarkers was highly predictive of significant coronary functional and anatomic stenosis.

SUBMITTER: Liu C

PROVIDER: S-EPMC8511462 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundLipid and inflammatory molecules play a key role in the development of inflammation. Neutrophil counts are used as markers of inflammation duration, and HDL-C is used as an anti-atherosclerosis component. However, few studies have been found to integrate these two indicators to explore coronary stenosis. We suggested that neutrophil count as a marker of inflammation persistence and HDL-C as an anti-atherosclerotic component should be integrated into a single biomarker NHR to explore its correlation with CAD degree and predict the severity of coronary stenosis among CAD patients.MethodsWe examined 404 eligible patients who underwent coronary angiography. Based on the results of coronary angiography, patients in CAD+ group (n = 155) were defined as those having angiographic coronary stenosis of at least 50% lumen reduction in at least one major coronary artery (including left anterior descending artery, left circumflex artery, left main coronary artery, right coronary artery). Patients with luminal stenosis but no more than 50% were defined as CAD- group (n = 49), and patients without luminal stenosis (n = 200) were regarded as control group. The relationship between various serum markers and the severity of coronary stenosis was examined by Spearman correlation analysis. Logistic regression analysis was performed to identify the influencing factors of the severity of coronary artery disease.ResultsThe modified Gensini score was positively correlated with neutrophil HDL-C ratio and negatively correlated with albumin and HDL-C. Multiple regression analysis showed that neutrophil HDL-C ratio were significantly associated with CAD. Neutrophil HDL-C ratio is an independent predictor of CAD. The ROC analysis provided a cut-off value of 1.51 for neutrophil HDL-C ratio to predict CAD with 94.8% sensitivity and 0.024 Yoden index, and area under the ROC curve of 0.617 (95% CI 0.560-0.675, P < 0.001).ConclusionNeutrophil HDL-C ratio is not only closely related to coronary artery stenosis, but also an independent predictor of severe coronary stenosis.

Project description:ObjectivesThis study sought to assess the performance of cardiovascular magnetic resonance (CMR) myocardial perfusion mapping against invasive coronary physiology reference standards for detecting coronary artery disease (CAD, defined by fractional flow reserve [FFR] ≤0.80), microvascular dysfunction (MVD) (defined by index of microcirculatory resistance [IMR] ≥25) and the ability to differentiate between the two.BackgroundDifferentiation of epicardial (CAD) and MVD in patients with stable angina remains challenging. Automated in-line CMR perfusion mapping enables quantification of myocardial blood flow (MBF) to be performed rapidly within a clinical workflow.MethodsFifty patients with stable angina and 15 healthy volunteers underwent adenosine stress CMR at 1.5T with quantification of MBF and myocardial perfusion reserve (MPR). FFR and IMR were measured in 101 coronary arteries during subsequent angiography.ResultsTwenty-seven patients had obstructive CAD and 23 had nonobstructed arteries (7 normal IMR, 16 abnormal IMR). FFR positive (epicardial stenosis) areas had significantly lower stress MBF (1.47 ± 0.48 ml/g/min) and MPR (1.75 ± 0.60) than FFR-negative IMR-positive (MVD) areas (stress MBF: 2.10 ± 0.35 ml/g/min; MPR: 2.41 ± 0.79) and normal areas (stress MBF: 2.47 ± 0.50 ml/g/min; MPR: 2.94 ± 0.81). Stress MBF ≤1.94 ml/g/min accurately detected obstructive CAD on a regional basis (area under the curve: 0.90; p < 0.001). In patients without regional perfusion defects, global stress MBF <1.82 ml/g/min accurately discriminated between obstructive 3-vessel disease and MVD (area under the curve: 0.94; p < 0.001).ConclusionsThis novel automated pixel-wise perfusion mapping technique can be used to detect physiologically significant CAD defined by FFR, MVD defined by IMR, and to differentiate MVD from multivessel coronary disease. A CMR-based diagnostic algorithm using perfusion mapping for detection of epicardial disease and MVD warrants further clinical validation.

Project description:Coronary artery disease (CAD) remains the leading cause of death worldwide with approximately 1 in 30 patients with stable CAD experiencing death or acute myocardial infarction each year. The presence and extent of resultant myocardial ischaemia has been shown to confer an increased risk of adverse outcomes. Whilst, optimal medical therapy (OMT) forms the cornerstone of the management of patients with stable CAD, a significant number of patients present with ischaemia refractory to OMT. Historically coronary angiography alone has been used to determine coronary lesion severity in both stable and acute settings. It is increasingly clear that this approach fails to accurately identify the haemodynamic significance of lesions; especially those that are visually "intermediate" in severity. Revascularisation based upon angiographic appearances alone may not reduce coronary events above OMT. Technological advances have enabled the measurement of physiological indices including the fractional flow reserve, the index of microcirculatory resistance and the coronary flow reserve. The integration of these parameters into the routine management of patients presenting to the cardiac catheterization laboratory with CAD represents a critical adjunctive tool in the optimal management of these patients by identifying patients that would most benefit from revascularisation and importantly also highlighting patients that would not gain benefit and therefore reducing the likelihood of adverse outcomes associated with coronary revascularisation. Furthermore, these techniques are applicable to a broad range of patients including those with left main stem disease, proximal coronary disease, diabetes mellitus, previous percutaneous coronary intervention and with previous coronary artery bypass grafting. This review will discuss current concepts relevant to coronary physiology assessment, its role in the management of both stable and acute patients and future applications.

Dataset Information

Relationship Between Immunoinflammation and Coronary Physiology Evaluated by Quantitative Flow Ratio in Patients With Coronary Artery Disease

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets