Trends in major lower limb amputations related to peripheral arterial disease in Hungary : A nationwide study (2004-2012)

ObjectivesTo assess the trends of peripheral arterial disease associated major lower limb amputation in Hungary over a 9 year period (2004–2012) in the whole Hungarian population.MethodsThis was a retrospective cohort study employing administrative health care data. Major amputations were identified in the entire Hungarian population during a 9 year period (2004–2012) using the health care administrative data. Direct standardization was used to eliminate the potential bias induced by the different age and sex structure of the compared populations. For external direct standardization, the ESP 2013 was chosen as reference.Results76,798 lower limb amputations were performed. The number of major amputations was 38,200; these procedures affected 32,084 patients. According to case detection, 50.4% of the amputees were diabetic. The overall primary amputation rate was 71.5%. The annual crude and age adjusted major amputation rates exhibited no significant long-term pattern over the observation period. The major lower limb amputation incidence for the overall period was 42.3/105 in the total population and 317.9/105 in diabetic population.ConclusionAccording to this whole population based study from Hungary, the incidence of lower limb major amputation is high with no change over the past 9 years. An explanation for this remains to be determined, as the traditional risk factors in Hungary do not account for it. The characteristics of major amputation (the rate of primary amputation, the ratio of below to above knee amputation and the age of the affected population) underline the importance of screening, early detection, improved vascular care and an optimal revascularization policy. Standardization and validation of amputation detection methods and reporting is essential

Practical Recommendations for Optimal Thromboprophylaxis in Patients with COVID-19: A Consensus Statement Based on Available Clinical Trials.

Coronavirus disease 2019 (COVID-19) has been shown to be strongly associated with increased risk for venous thromboembolism events (VTE) mainly in the inpatient but also in the outpatient setting. Pharmacologic thromboprophylaxis has been shown to offer significant benefits in terms of reducing not only VTE events but also mortality, especially in acutely ill patients with COVID-19. Although the main source of evidence is derived from observational studies with several limitations, thromboprophylaxis is currently recommended for all hospitalized patients with acceptable bleeding risk by all national and international guidelines. Recently, high quality data from randomized controlled trials (RCTs) further support the role of thromboprophylaxis and provide insights into the optimal thromboprophylaxis strategy. The aim of this statement is to systematically review all the available evidence derived from RCTs regarding thromboprophylaxis strategies in patients with COVID-19 in different settings (either inpatient or outpatient) and provide evidence-based guidance to practical questions in everyday clinical practice. Clinical questions accompanied by practical recommendations are provided based on data derived from 20 RCTs that were identified and included in the present study. Overall, the main conclusions are: (i) thromboprophylaxis should be administered in all hospitalized patients with COVID-19, (ii) an optimal dose of inpatient thromboprophylaxis is dependent upon the severity of COVID-19, (iii) thromboprophylaxis should be administered on an individualized basis in post-discharge patients with COVID-19 with high thrombotic risk, and (iv) thromboprophylaxis should not be routinely administered in outpatients. Changes regarding the dominant SARS-CoV-2 variants, the wide immunization status (increasing rates of vaccination and reinfections), and the availability of antiviral therapies and monoclonal antibodies might affect the characteristics of patients with COVID-19; thus, future studies will inform us about the thrombotic risk and the optimal therapeutic strategies for these patients

Illuminating the life of GPCRs

The investigation of biological systems highly depends on the possibilities that allow scientists to visualize and quantify biomolecules and their related activities in real-time and non-invasively. G-protein coupled receptors represent a family of very dynamic and highly regulated transmembrane proteins that are involved in various important physiological processes. Since their localization is not confined to the cell surface they have been a very attractive "moving target" and the understanding of their intracellular pathways as well as the identified protein-protein-interactions has had implications for therapeutic interventions. Recent and ongoing advances in both the establishment of a variety of labeling methods and the improvement of measuring and analyzing instrumentation, have made fluorescence techniques to an indispensable tool for GPCR imaging. The illumination of their complex life cycle, which includes receptor biosynthesis, membrane targeting, ligand binding, signaling, internalization, recycling and degradation, will provide new insights into the relationship between spatial receptor distribution and function. This review covers the existing technologies to track GPCRs in living cells. Fluorescent ligands, antibodies, auto-fluorescent proteins as well as the evolving technologies for chemical labeling with peptide- and protein-tags are described and their major applications concerning the GPCR life cycle are presented

A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography

Background: Coronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation Index (FAI) in standard coronary CT angiography (CCTA). However, inflammation is not the only process involved in atherogenesis and we hypothesized that additional radiomic signatures of adverse fibrotic and microvascular PVAT remodelling, may further improve cardiac risk prediction. Methods and results: We present a new artificial intelligence-powered method to predict cardiac risk by analysing the radiomic profile of coronary PVAT, developed and validated in patient cohorts acquired in three different studies. In Study 1, adipose tissue biopsies were obtained from 167 patients undergoing cardiac surgery, and the expression of genes representing inflammation, fibrosis and vascularity was linked with the radiomic features extracted from tissue CT images. Adipose tissue wavelet-transformed mean attenuation (captured by FAI) was the most sensitive radiomic feature in describing tissue inflammation (TNFA expression), while features of radiomic texture were related to adipose tissue fibrosis (COL1A1 expression) and vascularity (CD31 expression). In Study 2, we analysed 1391 coronary PVAT radiomic features in 101 patients who experienced major adverse cardiac events (MACE) within 5 years of having a CCTA and 101 matched controls, training and validating a machine learning (random forest) algorithm (fat radiomic profile, FRP) to discriminate cases from controls (C-statistic 0.77 [95%CI: 0.62–0.93] in the external validation set). The coronary FRP signature was then tested in 1575 consecutive eligible participants in the SCOT-HEART trial, where it significantly improved MACE prediction beyond traditional risk stratification that included risk factors, coronary calcium score, coronary stenosis, and high-risk plaque features on CCTA (Δ[C-statistic] = 0.126, P  Conclusion: The CCTA-based radiomic profiling of coronary artery PVAT detects perivascular structural remodelling associated with coronary artery disease, beyond inflammation. A new artificial intelligence (AI)-powered imaging biomarker (FRP) leads to a striking improvement of cardiac risk prediction over and above the current state-of-the-art. </p