Angiology最新文献

To investigate the relationships between inflammatory parameters, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII), and quantitative flow ratio (QFR) in stable coronary artery disease (CAD) patients (n = 450) enrolled in this cross-sectional study. Logistic regression was performed to evaluate the associations of NLR, PLR, MLR, and SII evaluated as continuous and binary variables with QFR ≤0.80. When treated as continuous variables, lnNLR was associated with QFR ≤0.80 with borderline significance in univariable (odds ratio (OR) = 1.60, p = .05) and multivariable analysis (OR = 1.72, p = .05), while lnMLR was associated with QFR ≤0.80 significantly in univariable analysis (OR = 1.87, p = .03) and with borderline significance in multivariable analysis (OR = 1.91, p = .05). When treated as binary variables, high levels of MLR and SII were significantly associated with QFR ≤0.80 in univariable (MLR: OR = 1.91, p = .02; SII: OR = 2.42, p = .006) and multivariable analysis (MLR: OR = 1.83, p = .04; SII: OR = 2.19, p = .02). NLR, MLR, and SII, but not PLR, were significantly associated with the severity of coronary physiology in stable CAD patients.

Increased arterial stiffness is independently associated with cardiovascular risk. Obstructive sleep apnea (OSA) and sleep duration (SDUR) may contribute to increased arterial stiffness, but it is unclear whether this association is modulated by gender. We aimed to evaluate the potential impact of gender in modulating the association of OSA and SDUR with arterial stiffness. Participants from the ELSA-Brasil study performed sleep assessments with portable polygraph to define OSA severity and SDUR by 1-week wrist actigraphy. Pulse wave velocity (PWV) was measured using a standard technique without access to the sleep data. We studied 1863 participants (42.2% male, age: 49±8 years, respiratory disturbance index (RDI): 9.9 (4.5-19.4) events/h, SDUR: 6.5 (5.9-7.1) hours, mean PWV: 7.3 ± 1.2 m/s). We found that men had higher PWV, higher frequency of diabetes, and higher blood pressure when compared to women. The regression analysis showed an independent association between increased RDI and PWV in men (ß: 0.007; 95% CI: 0.001-0.012), but not in women. In contrast, an independent association between SDUR and increased arterial stiffness was observed only in women (ß: 0.068; 95% CI: 0.002-0.134). In conclusion, the association of sleep disorders with arterial stiffness showed a distinct gender pattern depending on the sleep variable studied.

The present study aimed to analyze common carotid artery strain properties in patients (n = 59) with severe aortic valve stenosis who underwent transcatheter aortic valve replacement (TAVR). Arterial compliance of the common carotid artery was assessed by ultrasound speckle-tracking before and after TAVR. For sub-analysis the study cohort was divided according to aortic valve area <.75 cm² (n = 30) vs ≥.75 cm² (n = 29). Comparison of pre- and post-procedural strain variables showed an improvement in median radial velocity (P < .0001), radial displacement (P = .007), circumferential strain (P = .004), radial strain rate (P = .023), and circumferential strain rate (P < .0001), while the increase of radial strain showed a trend (P = .082). Analysis of aortic valve area revealed an inverse correlation between aortic valve area and the differences (post-procedural-pre-procedural values) for radial strain rate, and circumferential strain. Moreover, sub-analysis revealed that the increase of carotid strain variables before and after TAVR were more pronounced in the sub-group of aortic valve area .75 vs ≥.75 cm². TAVR led to a reduction of arterial wall stiffness of the common carotid artery assessed by ultrasound speckle-tracking. The decrease of arterial wall stiffness after TAVR was more pronounced in more severe aortic valve stenosis.

Aortic aneurysm is a life-threatening condition and mechanisms underlying its formation and progression are still incompletely understood. Omics approach has brought new insights to identify a broad spectrum of biomarkers and better understand cellular and molecular pathways involved. Omics generate a large amount of data and several studies have highlighted that artificial intelligence (AI) and techniques such as machine learning (ML)/deep learning (DL) can be of use in analyzing such complex datasets. However, only a few studies have so far reported the use of ML/DL for omics analysis in aortic aneurysms. The aim of this study is to summarize recent advances on the use of ML/DL for omics analysis to decipher aortic aneurysm pathophysiology and develop patient-tailored risk prediction models. In the light of current knowledge, we discuss current limits and highlight future directions in the field.