Atrial High-Rate Episode Duration Thresholds and Thromboembolic Risk: A Systematic Review and Meta-Analysis

BACKGROUND: Available evidence supports an association between atrial high‐rate episode (AHRE) burden and thromboembolic risk, but the necessary extent and duration of AHREs to increase the thromboembolic risk remain to be defined. The aim of this systematic review and meta‐analysis was to identify the thromboembolic risk associated with various AHRE thresholds. METHODS AND RESULTS: We searched PubMed and Scopus until January 9, 2020, for literature reporting AHRE duration and thromboembolic risk in patients with implantable electronic devices. The outcome assessed was stroke or systemic embolism. Risk estimates were reported as hazard ratio (HR) or relative risk alongside 95% CIs. We used the Paule‐Mandel estimator, and heterogeneity was calculated with I(2) index. Among 27 studies including 61 919 patients, 23 studies reported rates according to the duration of the longest AHRE and 4 studies reported rates according to the cumulative day‐level AHRE duration. In patients with cardiac implantable devices, AHREs lasting ≥30 seconds significantly increased the risk of stroke or systemic embolism (HR, 4.41; 95% CI, 2.32–8.39; I(2), 5.5%), which remained consistent for the thresholds of 5 minutes and 6 and 24 hours. Patients with previous stroke or transient ischemic attack and AHREs lasting ≥2 minutes had a marginally increased risk of recurrent stroke or transient ischemic attack. The risk of stroke or systemic embolism was higher in patients with cumulative AHRE ≥24 hours compared with those of shorter duration or no AHRE (HR, 1.25; 95% CI, 1.04–1.52; I(2), 0%). CONCLUSIONS: This systematic review and meta‐analysis suggests that single AHRE episodes ≥30 seconds and cumulative AHRE duration ≥24 hours are associated with increased risk of stroke or systemic embolism

Cathepsin S Levels and Survival Among Patients With Non-ST-Segment Elevation Acute Coronary Syndromes

Patients with non-ST-segment elevation acute coronary syndromes (NSTE-ACS) are at high residual risk for long-term cardiovascular (CV) mortality. Cathepsin S (CTSS) is a lysosomal cysteine protease with elastolytic and collagenolytic activity that has been involved in atherosclerotic plaque rupture.; The purpose of this study was to determine the following: 1) the prognostic value of circulating CTSS measured at patient admission for long-term mortality in NSTE-ACS; and 2) its additive value over the GRACE (Global Registry of Acute Coronary Events) risk score.; This was a single-center cohort study, consecutively recruiting patients with adjudicated NSTE-ACS (n = 1,112) from the emergency department of an academic hospital. CTSS was measured in serum using enzyme-linked immunosorbent assay. All-cause mortality at 8 years was the primary endpoint. CV death was the secondary endpoint.; In total, 367 (33.0%) deaths were recorded. CTSS was associated with increased risk of all-cause mortality (HR for highest vs lowest quarter of CTSS: 1.89; 95% CI: 1.34-2.66; P < 0.001) and CV death (HR: 2.58; 95% CI: 1.15-5.77; P = 0.021) after adjusting for traditional CV risk factors, high-sensitivity C-reactive protein, left ventricular ejection fraction, high-sensitivity troponin-T, revascularization and index diagnosis (unstable angina/ non-ST-segment elevation myocardial infarction). When CTSS was added to the GRACE score, it conferred significant discrimination and reclassification value for all-cause mortality (Delta Harrell's C: 0.03; 95% CI: 0.012-0.047; P = 0.001; and net reclassification improvement = 0.202; P = 0.003) and CV death (AUC: 0.056; 95% CI: 0.017-0.095; P = 0.005; and net reclassification improvement = 0.390; P = 0.001) even after additionally considering high-sensitivity troponin-T and left ventricular ejection fraction.; Circulating CTSS is a predictor of long-term mortality and improves risk stratification of patients with NSTE-ACS over the GRACE score

Estimated pulse wave velocity improves risk stratification for all-cause mortality in patients with COVID-19

Accurate risk stratification in COVID-19 patients consists a major clinical need to guide therapeutic strategies. We sought to evaluate the prognostic role of estimated pulse wave velocity (ePWV), a marker of arterial stiffness which reflects overall arterial integrity and aging, in risk stratification of hospitalized patients with COVID-19. This retrospective, longitudinal cohort study, analyzed a total population of 1671 subjects consisting of 737 hospitalized COVID-19 patients consecutively recruited from two tertiary centers (Newcastle cohort: n = 471 and Pisa cohort: n = 266) and a non-COVID control cohort (n = 934). Arterial stiffness was calculated using validated formulae for ePWV. ePWV progressively increased across the control group, COVID-19 survivors and deceased patients (adjusted mean increase per group 1.89 m/s, P &lt; 0.001). Using a machine learning approach, ePWV provided incremental prognostic value and improved reclassification for mortality over the core model including age, sex and comorbidities [AUC (core model + ePWV vs. core model) = 0.864 vs. 0.755]. ePWV provided similar prognostic value when pulse pressure or hs-Troponin were added to the core model or over its components including age and mean blood pressure (p &lt; 0.05 for all). The optimal prognostic ePWV value was 13.0 m/s. ePWV conferred additive discrimination (AUC: 0.817 versus 0.779, P &lt; 0.001) and reclassification value (NRI = 0.381, P &lt; 0.001) over the 4C Mortality score, a validated score for predicting mortality in COVID-19 and the Charlson comorbidity index. We suggest that calculation of ePWV, a readily applicable estimation of arterial stiffness, may serve as an additional clinical tool to refine risk stratification of hospitalized patients with COVID-19 beyond established risk factors and scores

Classification Of Noisy Signals Using Fuzzy Artmap Neural Networks

This paper describes an approach to classification of noisy signals using a technique based on the Fuzzy ARTMAP neural network (FAM). A variation of the testing phase of Fuzzy ARTMAP is introduced, that exhibited superior generalization performance than the standard Fuzzy ARTMAP in the presence of noise. We present an application of our technique for textured grayscale images. We perform a large number of experiments to verify the superiority of the modified over the standard Fuzzy ARTMAP. More specifically, the modified and the standard FAM were evaluated on two different sets of features (fractal-based and energy-based), for three different types of noise (Gaussian, uniform, exponential) and for two different texture sets (Brodatz, aerial). Furthermore, the classification performance of the standard and modified Fuzzy ARTMAP was compared for different network sizes

Fuzzy Artmap Based Classification Technique Of Natural Textures

This paper describes an approach to classification of textured grayscale images using a technique based on image filtering and the fractal dimension (FD) and the Fuzzy ARTMAP neural network (FAMNN). Twelve FD features are computed based on twelve filtered versions of the original image using directional Gabor filters. Features are computed in a window and mapped to the central pixel of this window. We implemented a variation of the testing phase of Fuzzy ARTMAP that exhibited superior performance than the standard Fuzzy ARTMAP and the 1-nearest neighbor (1-NN) in the presence of noise. Training was performed using patterns that were extracted from twenty different textures. The performance of classification is also studied with respect to a testing set. Segmentation results are also presented to illustrate that the classification algorithm and its specified parameters are adequate so that more than one texture can be identified in the same image

Texture classification using ART-based neural networks and fractals

In this paper texture classification is studied based on the fractal dimension (FD) of filtered versions of the image and the Fuzzy ART Map neural network (FAMNN). FD is used because it has shown good tolerance to some image transformations. We implemented a variation of the testing phase of Fuzzy ARTMAP that exhibited superior performance than the standard Fuzzy ARTMAP and the 1-nearest neighbor (1-NN) in the presence of noise. The performance of the above techniques is tested with respect to segmentation of images that include more than one texture

Classification of noisy signals using fuzzy ARTMAP neural networks

This paper describes an approach to classification of noisy signals using a technique based on the Fuzzy ARTMAP neural network (FAM). A variation of the testing phase of Fuzzy ARTMAP is introduced, that exhibited superior generalization performance than the standard Fuzzy ARTMAP in the presence of noise. We present an application of our technique for textured grayscale images. We perform a large number of experiments to verify the superiority of the modified over the standard Fuzzy ARTMAP. More specifically, the modified and the standard FAM were evaluated on two different sets of features (fractal-based and energy-based), for three different types of noise (Gaussian, uniform, exponential) and for two different texture sets (Brodatz, aerial). Furthermore, the classification performance of the standard and modified Fuzzy ARTMAP was compared for different network sizes

Azilsartan as a Potent Antihypertensive Drug with Possible Pleiotropic Cardiometabolic Effects: A Review Study

BACKGROUND: Hypertension related cardiovascular (CV) complications could be amplified by the presence of metabolic co-morbidities. Azilsartan medoxomil (AZL-M) is the eighth approved member of angiotensin II receptor blockers (ARBs), a drug class of high priority in the management of hypertensive subjects with diabetes mellitus type II (DMII). METHODS: Under this prism, we performed a systematic review of the literature for all relevant articles in order to evaluate the efficacy, safety, and possible clinical role of AZL-M in hypertensive diabetic patients. RESULTS: AZL-M was found to be more effective in terms of reducing indices of blood pressure over alternative ARBs or angiotensin-converting enzyme (ACE) inhibitors with minimal side effects. Preclinical studies have established pleiotropic effects for AZL-M beyond its primary antihypertensive role through differential gene expression, up-regulation of membrane receptors and favorable effect on selective intracellular biochemical and pro-atherosclerotic pathways. CONCLUSION: Indirect but accumulating evidence from recent literature supports the efficacy and safety of AZL-M among diabetic patients. However, no clinical data exist to date that evince a beneficial role of AZL-M in patients with metabolic disorders on top of its antihypertensive effect. Further clinical studies are warranted to assess the pleiotropic cardiometabolic benefits of AZL-M that are derived from preclinical research