55 research outputs found
A diabeteses láb ischaemiás eredete. Epidemiológia, a diagnózis nehézségei, prevenciós és revascularisatiós lehetőségek
"Diabetic foot" as definition covers a multifactorial clinical condition. According to the recent epidemiological data, the role of lower limb ischemia is getting more influential over other pathological causes, like neuropathy, infections and bone or soft tissue deformity. In diabetes, vascular disease leads to increased risk for leg ulcers and minor or major amputations. The traditional diagnostic tools for recognition of peripheral arterial disease have limited value because of diabetes specific clinical manifestations. Available vascular centers with special expertise and diagnostic tools are the prerequisite for efficient diagnosis supporting timely recognition of peripheral arterial disease. In course of treatment of diabetic foot with ischemic origin, beyond effective medical treatment revascularization (open vascular surgery or endovascular procedures) has paramount importance for prevention of limb loss. Vascular teams of vascular specialists, vascular surgeons and interventional radiologist in dedicated centers in multidisciplinary cooperation with other professions represent public health issue in effective prevention. Orv. Hetil., 2017, 158(6), 203-211
Modeling the pharmacodynamics of passive membrane permeability
Small molecule permeability through cellular membranes is critical to a better understanding of pharmacodynamics and the drug discovery endeavor. Such permeability may be estimated as a function of the free energy change of barrier crossing by invoking the barrier domain model, which posits that permeation is limited by passage through a single “barrier domain” and assumes diffusivity differences among compounds of similar structure are negligible. Inspired by the work of Rezai and co-workers (JACS 128:14073–14080, 2006), we estimate this free energy change as the difference in implicit solvation free energies in chloroform and water, but extend their model to include solute conformational affects. Using a set of eleven structurally diverse FDA approved compounds and a set of thirteen congeneric molecules, we show that the solvation free energies are dominated by the global minima, which allows solute conformational distributions to be effectively neglected. For the set of tested compounds, the best correlation with experiment is obtained when the implicit chloroform global minimum is used to evaluate the solvation free energy difference
Left atrial appendage size is a marker of atrial fibrillation recurrence after radiofrequency catheter ablation in patients with persistent atrial fibrillation
Introduction There are no consistently confirmed predictors of atrial fibrillation (AF) recurrence after catheter ablation. Therefore, we aimed to study whether left atrial appendage volume (LAAV) and function influence the long-term recurrence of AF after catheter ablation, depending on AF type. Methods AF patients who underwent point-by-point radiofrequency catheter ablation after cardiac computed tomography (CT) were included in this analysis. LAAV and LAA orifice area were measured by CT. Uni- and multivariable Cox proportional hazard regression models were performed to determine the predictors of AF recurrence. Results In total, 561 AF patients (61.9 +/- 10.2 years, 34.9% females) were included in the study. Recurrence of AF was detected in 40.8% of the cases (34.6% in patients with paroxysmal and 53.5% in those with persistent AF) with a median recurrence-free time of 22.7 (9.3-43.1) months. Patients with persistent AF had significantly higher body surface area-indexed LAV, LAAV, and LAA orifice area and lower LAA flow velocity, than those with paroxysmal AF. After adjustment left ventricular ejection fraction (LVEF) <50% (HR = 2.17; 95% CI = 1.38-3.43; p < .001) and LAAV (HR = 1.06; 95% CI = 1.01-1.12; p = .029) were independently associated with AF recurrence in persistent AF, while no independent predictors could be identified in paroxysmal AF. Conclusion The current study demonstrates that beyond left ventricular systolic dysfunction, LAA enlargement is associated with higher rate of AF recurrence after catheter ablation in persistent AF, but not in patients with paroxysmal AF.Cardiovascular Aspects of Radiolog
Guidance for the Management of Patients with Vascular Disease or Cardiovascular Risk Factors and COVID-19: Position Paper from VAS-European Independent Foundation in Angiology/Vascular Medicine .
COVID-19 is also manifested with hypercoagulability, pulmonary intravascular coagulation, microangiopathy, and venous thromboembolism (VTE) or arterial thrombosis. Predisposing risk factors to severe COVID-19 are male sex, underlying cardiovascular disease, or cardiovascular risk factors including noncontrolled diabetes mellitus or arterial hypertension, obesity, and advanced age. The VAS-European Independent Foundation in Angiology/Vascular Medicine draws attention to patients with vascular disease (VD) and presents an integral strategy for the management of patients with VD or cardiovascular risk factors (VD-CVR) and COVID-19. VAS recommends (1) a COVID-19-oriented primary health care network for patients with VD-CVR for identification of patients with VD-CVR in the community and patients' education for disease symptoms, use of eHealth technology, adherence to the antithrombotic and vascular regulating treatments, and (2) close medical follow-up for efficacious control of VD progression and prompt application of physical and social distancing measures in case of new epidemic waves. For patients with VD-CVR who receive home treatment for COVID-19, VAS recommends assessment for (1) disease worsening risk and prioritized hospitalization of those at high risk and (2) VTE risk assessment and thromboprophylaxis with rivaroxaban, betrixaban, or low-molecular-weight heparin (LMWH) for those at high risk. For hospitalized patients with VD-CVR and COVID-19, VAS recommends (1) routine thromboprophylaxis with weight-adjusted intermediate doses of LMWH (unless contraindication); (2) LMWH as the drug of choice over unfractionated heparin or direct oral anticoagulants for the treatment of VTE or hypercoagulability; (3) careful evaluation of the risk for disease worsening and prompt application of targeted antiviral or convalescence treatments; (4) monitoring of D-dimer for optimization of the antithrombotic treatment; and (5) evaluation of the risk of VTE before hospital discharge using the IMPROVE-D-dimer score and prolonged post-discharge thromboprophylaxis with rivaroxaban, betrixaban, or LMWH
Prediction of Promiscuous P-Glycoprotein Inhibition Using a Novel Machine Learning Scheme
BACKGROUND: P-glycoprotein (P-gp) is an ATP-dependent membrane transporter that plays a pivotal role in eliminating xenobiotics by active extrusion of xenobiotics from the cell. Multidrug resistance (MDR) is highly associated with the over-expression of P-gp by cells, resulting in increased efflux of chemotherapeutical agents and reduction of intracellular drug accumulation. It is of clinical importance to develop a P-gp inhibition predictive model in the process of drug discovery and development. METHODOLOGY/PRINCIPAL FINDINGS: An in silico model was derived to predict the inhibition of P-gp using the newly invented pharmacophore ensemble/support vector machine (PhE/SVM) scheme based on the data compiled from the literature. The predictions by the PhE/SVM model were found to be in good agreement with the observed values for those structurally diverse molecules in the training set (n = 31, r(2) = 0.89, q(2) = 0.86, RMSE = 0.40, s = 0.28), the test set (n = 88, r(2) = 0.87, RMSE = 0.39, s = 0.25) and the outlier set (n = 11, r(2) = 0.96, RMSE = 0.10, s = 0.05). The generated PhE/SVM model also showed high accuracy when subjected to those validation criteria generally adopted to gauge the predictivity of a theoretical model. CONCLUSIONS/SIGNIFICANCE: This accurate, fast and robust PhE/SVM model that can take into account the promiscuous nature of P-gp can be applied to predict the P-gp inhibition of structurally diverse compounds that otherwise cannot be done by any other methods in a high-throughput fashion to facilitate drug discovery and development by designing drug candidates with better metabolism profile
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
Prognostic value of early, conventional proton magnetic resonance spectroscopy in cooled asphyxiated infants
BACKGROUND: Neonatal hypoxic-ischemic encephalopathy (HIE) commonly leads to neurodevelopmental impairment, raising the need for prognostic tools which may guide future therapies in time. Prognostic value of proton MR spectroscopy (H-MRS) between 1 and 46 days of age has been extensively studied; however, the reproducibility and generalizability of these methods are controversial in a general clinical setting. Therefore, we investigated the prognostic performance of conventional H-MRS during first 96 postnatal hours in hypothermia-treated asphyxiated neonates. METHODS: Fifty-one consecutive hypothermia-treated HIE neonates were examined by H-MRS at three echo-times (TE = 35, 144, 288 ms) between 6 and 96 h of age, depending on clinical stability. Patients were divided into favorable (n = 35) and unfavorable (n = 16) outcome groups based on psychomotor and mental developmental index (PDI and MDI, Bayley Scales of Infant Development II) scores (>/= 70 versus < 70 or death, respectively), assessed at 18-26 months of age. Associations between 36 routinely measured metabolite ratios and outcome were studied. Age-dependency of metabolite ratios in whole patient population was assessed. Prognostic performance of metabolite ratios was evaluated by Receiver Operating Characteristics (ROC) analysis. RESULTS: Three metabolite ratios showed significant difference between outcome groups after correction for multiple testing (p < 0.0014): myo-inositol (mIns)/N-acetyl-aspartate (NAA) height, mIns/creatine (Cr) height, both at TE = 35 ms, and NAA/Cr height at TE = 144 ms. Assessment of age-dependency showed that all 3 metabolite ratios (mIns/NAA, NAA/Cr and mIns/Cr) stayed constant during first 96 postnatal hours, rendering them optimal for prediction. ROC analysis revealed that mIns/NAA gives better prediction for outcome than NAA/Cr and mIns/Cr with cut-off values 0.6798 0.6274 and 0.7798, respectively, (AUC 0.9084, 0.8396 and 0.8462, respectively, p < 0.00001); mIns/NAA had the highest specificity (95.24%) and sensitivity (84.62%) for predicting outcome of neonates with HIE any time during the first 96 postnatal hours. CONCLUSIONS: Our findings suggest that during first 96 h of age even conventional H-MRS could be a useful prognostic tool in predicting the outcome of asphyxiated neonates; mIns/NAA was found to be the best and age-independent predictor
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