Objective: The prognosis of patients with peripheral arterial disease (PAD) is characterized by an exceptionally high risk for myocardial infarction, ischemic stroke, and death; however, studies in search of new prognostic biomarkers in PAD are scarce. Even though low levels of high-density lipoprotein cholesterol (HDL-C) have been associated with higher risk of cardiovascular (CV) complications and death in different atherosclerotic diseases, recent epidemiologic studies have challenged its prognostic utility. The aim of this study was to test the predictive value of HDL-C as a risk factor for ischemic events or death in symptomatic PAD patients.
Methods: Clinical and demographic parameters of 254 symptomatic PAD patients were recorded. Amputation, ischemic coronary disease, cerebrovascular disease, and all-cause mortality were recorded during a mean follow-up of 2.7 years.
Results: Multivariate analyses showed that disease severity (critical limb ischemia) was significantly reduced in patients with normal HDL-C levels compared with the group with low HDL-C levels (multivariate analysis odds ratio, 0.09; 95% confidence interval [CI], 0.03-0.24). A decreased risk for mortality (hazard ratio, 0.46; 95% CI, 0.21-0.99) and major adverse CV events (hazard ratio, 0.38; 95% CI, 0.16-0.86) was also found in patients with normal vs reduced levels of HDL-C in both Cox proportional hazards models and Kaplan-Meier estimates, after adjustment for confounding factors.
Conclusions: Reduced HDL-C levels were significantly associated with higher risk for development of CV complications as well as with mortality in PAD patients. These findings highlight the usefulness of this simple test for early identification of PAD patients at high risk for development of major CV events.
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http://dx.doi.org/10.1016/j.jvs.2017.04.056 | DOI Listing |
Background: Cachexia is defined by chronic loss of fat and muscle, is a frequent complication of pancreatic ductal adenocarcinoma (PDAC), and negatively impacts patient outcomes. Nutritional supplementation cannot fully reverse tissue wasting, and the mechanisms underlying this phenotype are unclear. This work aims to define the relative contributions of catabolism and anabolism to adipose wasting in PDAC-bearing mice.
View Article and Find Full Text PDFFront Nephrol
December 2024
Department of Nephrology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Chronic kidney disease (CKD) patients often suffer from complications such as anemia as the kidney function declines. More than 25% of CKD hemodialysis patients in China are complicated with renal anemia due to renal and hepatic impairment in the production of erythropoietin (EPO). In recent years, prolyl hydroxylase domain (PHD) inhibitors have been approved in China and Japan for the treatment of CKD patients complicated with anemia.
View Article and Find Full Text PDFJ Vasc Surg Cases Innov Tech
February 2025
Department of Health and Kinesiology, Purdue University, West Lafayette, IN.
Objective: This study aimed to assess the effect of home-based exercise interventions on walking performance in patients with peripheral artery disease (PAD) and intermittent claudication (IC).
Design: Systematic review and meta-analysis.
Data Sources: We searched the Medline, Web of Science, Embase, Scopus and Cochrane Library databases to identify randomised controlled trials of patients with PAD and IC published in English up to August 2024.
Vascular
January 2025
Department of Vascular Surgery, University Hospital Leipzig, Leipzig, Germany.
Background: Peripheral artery disease (PAD) outcomes often rely on the expertise of individual vascular units, introducing potential subjectivity into disease staging. This retrospective, multicenter cohort study aimed to demonstrate the ability of artificial intelligence (AI) to provide disease staging based on inter-institutional expertise by predicting limb outcomes in post-interventional pedal angiograms of PAD patients, specifically in comparison to the inframalleolar modifier in the Global Limb Anatomic Staging System (IM GLASS).
Methods: We used computer vision (CV) based on the MobileNetV2 model, implemented via TensorFlow.
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