157 research outputs found

    Una tarde con Ramón. Entrevista a Ramón Valdés

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    Aquesta entrevista al Catedràtic Emèrit de la UAB, Dr. Ramón Valdés del Toro, la van realitzar l'11 de juliol de 2006 un grup d'alumnes de l'assignatura Etnologia Regional que es va impartir el curs 2005-06 a la Llicenciatura d'Antropologia Social d'aquesta universitat. L'entrevista forma part d'un projecte més ampli vinculat a l'assignatura dirigit per la professora que l'imparteix, Montserrat Clua i Fainé.Esta entrevista al Catedrático Emérito de la UAB, Dr. Ramón Valdés del Toro, fue realizada el 11 de julio de 2006 por un grupo de alumnas de la asignatura Etnología Regional que se impartió el curso 2005-06 en la Licenciatura de Antropología Social de dicha universidad. La entrevista forma parte de un proyecto más amplio vinculado a la asignatura y dirigido por su profesora, Montserrat Clua i Fainé

    Young people’s perception of sexual and reproductive health services in Kenya

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    Background Addressing the Sexual and Reproductive Health (SRH) needs of young people remains a big challenge. This study explored experiences and perceptions of young people in Kenya aged 10–24 with regard to their SRH needs and whether these are met by the available healthcare services. Methods 18 focus group discussions and 39 in-depth interviews were conducted at health care facilities and youth centres across selected urban and rural settings in Kenya. All interviews were tape recorded and transcribed. Data was analysed using the thematic framework approach. Results Young people’s perceptions are not uniform and show variation between boys and girls as well as for type of service delivery. Girls seeking antenatal care and family planning services at health facilities characterise the available services as good and staff as helpful. However, boys perceive services at health facilities as designed for women and children, and therefore feel uncomfortable seeking services. At youth centres, young people value the non-health benefits including availability of recreational facilities, prevention of idleness, building of confidence, improving interpersonal communication skills, vocational training and facilitation of career progression. Conclusion Providing young people with SRH information and services through the existing healthcare system, presents an opportunity that should be further optimised. Providing recreational activities via youth centres is reported by young people themselves to not lead to increased uptake of SRH healthcare services. There is need for more research to evaluate how perceived non-health benefits young people do gain from youth centres could lead to improved SRH of young people

    Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review

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    Purpose: The role of erectile dysfunction (ED) has recently shown an association with the risk of stroke and coronary heart disease (CHD) via the atherosclerotic pathway. Cardiovascular disease (CVD)/stroke risk has been widely understood with the help of carotid artery disease (CTAD), a surrogate biomarker for CHD. The proposed study emphasizes artificial intelligence-based frameworks such as machine learning (ML) and deep learning (DL) that can accurately predict the severity of CVD/stroke risk using carotid wall arterial imaging in ED patients. Methods: Using the PRISMA model, 231 of the best studies were selected. The proposed study mainly consists of two components: (i) the pathophysiology of ED and its link with coronary artery disease (COAD) and CHD in the ED framework and (ii) the ultrasonic-image morphological changes in the carotid arterial walls by quantifying the wall parameters and the characterization of the wall tissue by adapting the ML/DL-based methods, both for the prediction of the severity of CVD risk. The proposed study analyzes the hypothesis that ML/DL can lead to an accurate and early diagnosis of the CVD/stroke risk in ED patients. Our finding suggests that the routine ED patient practice can be amended for ML/DL-based CVD/stroke risk assessment using carotid wall arterial imaging leading to fast, reliable, and accurate CVD/stroke risk stratification. Summary: We conclude that ML and DL methods are very powerful tools for the characterization of CVD/stroke in patients with varying ED conditions. We anticipate a rapid growth of these tools for early and better CVD/stroke risk management in ED patients

    Ultrasound-based stroke/cardiovascular risk stratification using Framingham Risk Score and ASCVD Risk Score based on “Integrated Vascular Age” instead of “Chronological Age”: A multi-ethnic study of Asian Indian, Caucasian, and Japanese cohorts

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    Background: Vascular age (VA) has recently emerged for CVD risk assessment and can either be computed using conventional risk factors (CRF) or by using carotid intima-media thickness (cIMT) derived from carotid ultrasound (CUS). This study investigates a novel method of integrating both CRF and cIMT for estimating VA [so-called integrated VA (IVA)]. Further, the study analyzes and compares CVD/stroke risk using the Framingham Risk Score (FRS)-based risk calculator when adapting IVA against VA. Methods: The system follows a four-step process: (I) VA using cIMT based using linear-regression (LR) model and its coefficients; (II) VA prediction using ten CRF using a multivariate linear regression (MLR)based model with gender adjustment; (III) coefficients from the LR-based model and MLR-based model are combined using a linear model to predict the final IVA; (IV) the final step consists of FRS-based risk stratification with IVA as inputs and benchmarked against FRS using conventional method of CA. Area-under-the-curve (AUC) is computed using IVA and benchmarked against CA while taking the response variable as a standardized combination of cIMT and glycated hemoglobin. Results: The study recruited 648 patients, 202 were Japanese, 314 were Asian Indian, and 132 were Caucasians. Both left and right common carotid arteries (CCA) of all the population were scanned, thus a total of 1,287 ultrasound scans. The 10-year FRS using IVA reported higher AUC (AUC =0.78) compared with 10-year FRS using CA (AUC =0.66) by ~18%

    Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application

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    Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the United States of America and globally. Carotid arterial plaque, a cause and also a marker of such CVD, can be detected by various non-invasive imaging modalities such as magnetic resonance imaging (MRI), computer tomography (CT), and ultrasound (US). Characterization and classification of carotid plaque-type in these imaging modalities, especially into symptomatic and asymptomatic plaque, helps in the planning of carotid endarterectomy or stenting. It can be challenging to characterize plaque components due to (I) partial volume effect in magnetic resonance imaging (MRI) or (II) varying Hausdorff values in plaque regions in CT, and (III) attenuation of echoes reflected by the plaque during US causing acoustic shadowing. Artificial intelligence (AI) methods have become an indispensable part of healthcare and their applications to the non-invasive imaging technologies such as MRI, CT, and the US. In this narrative review, three main types of AI models (machine learning, deep learning, and transfer learning) are analyzed when applied to MRI, CT, and the US. A link between carotid plaque characteristics and the risk of coronary artery disease is presented. With regard to characterization, we review tools and techniques that use AI models to distinguish carotid plaque types based on signal processing and feature strengths. We conclude that AI-based solutions offer an accurate and robust path for tissue characterization and classification for carotid artery plaque imaging in all three imaging modalities. Due to cost, user-friendliness, and clinical effectiveness, AI in the US has dominated the most

    Post-Acquisition Processing Confounds in Brain Volumetric Quantification of White Matter Hyperintensities

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    BACKGROUND: Disparate research sites using identical or near-identical magnetic resonance imaging (MRI) acquisition techniques often produce results that demonstrate significant variability regarding volumetric quantification of white matter hyperintensities (WMH) in the aging population. The sources of such variability have not previously been fully explored. NEW METHOD: 3D FLAIR sequences from a group of randomly selected aged subjects were analyzed to identify sources-of-variability in post-acquisition processing that can be problematic when comparing WMH volumetric data across disparate sites. The methods developed focused on standardizing post-acquisition protocol processing methods to develop a protocol with less than 0.5% inter-rater variance. RESULTS: A series of experiments using standard MRI acquisition sequences explored post-acquisition sources-of-variability in the quantification of WMH volumetric data. Sources-of-variability included: the choice of image center, software suite and version, thresholding selection, and manual editing procedures (when used). Controlling for the identified sources-of-variability led to a protocol with less than 0.5% variability between independent raters in post-acquisition WMH volumetric quantification. COMPARISON WITH EXISTING METHOD(S): Post-acquisition processing techniques can introduce an average variance approaching 15% in WMH volume quantification despite identical scan acquisitions. Understanding and controlling for such sources-of-variability can reduce post-acquisition quantitative image processing variance to less than 0.5%. DISCUSSION: Considerations of potential sources-of-variability in MRI volume quantification techniques and reduction in such variability is imperative to allow for reliable cross-site and cross-study comparisons

    Burden of Risk Alleles for Hypertension Increases Risk of Intracerebral Hemorrhage

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    Background and Purpose-Genetic variation influences risk of intracerebral hemorrhage (ICH). Hypertension (HTN) is a potent risk factor for ICH and several common genetic variants (single nucleotide polymorphisms [SNPs]) associated with blood pressure levels have been identified. We sought to determine whether the cumulative burden of blood pressure-related SNPs is associated with risk of ICH and pre-ICH diagnosis of HTN. Methods-We conducted a prospective multicenter case-control study in 2272 subjects of European ancestry (1025 cases and 1247 control subjects). Thirty-nine SNPs reported to be associated with blood pressure levels were identified from the National Human Genome Research Institute genomewide association study catalog. Single-SNP association analyses were performed for the outcomes ICH and pre-ICH HTN. Subsequently, weighted and unweighted genetic risk scores were constructed using these SNPs and entered as the independent variable in logistic regression models with ICH and pre-ICH HTN as the dependent variables. Results-No single SNP was associated with either ICH or pre-ICH HTN. The blood pressure-based unweighted genetic risk score was associated with risk of ICH (OR, 1.11; 95% CI, 1.02-1.21; P=0.01) and the subset of ICH in deep regions (OR, 1.18; 95% CI, 1.07-1.30; P=0.001), but not with the subset of lobar ICH. The score was associated with a history of HTN among control subjects (OR, 1.17; 95% CI, 1.04-1.31; P=0.009) and ICH cases (OR, 1.15; 95% CI, 1.01-1.31; P=0.04). Similar results were obtained when using a weighted score. Conclusion-Increasing numbers of high blood pressure-related alleles are associated with increased risk of deep ICH as well as with clinically identified HTN. (Stroke. 2012; 43: 2877-2883.

    Endothelial Progenitor Cells Predict Cardiovascular Events after Atherothrombotic Stroke and Acute Myocardial Infarction. A PROCELL Substudy.

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    Introduction: The aim of this study was to determine prognostic factors for the risk of new vascular events during the first 6 months after acute myocardial infarction (AMI) or atherothrombotic stroke (AS). We were interested in the prognostic role of endothelial progenitor cells (EPC) and circulating endothelial cells (CEC). Methods: Between February 2009 and July 2012, 100 AMI and 50 AS patients were consecutively studied in three Spanish centres. Patients with previously documented coronary artery disease or ischemic strokes were excluded. Samples were collected within 24h of onset of symptoms. EPC and CEC were studied using flow cytometry and categorized by quartiles. Patients were followed for up to 6 months. NVE was defined as new acute coronary syndrome, transient ischemic attack (TIA), stroke, or any hospitalization or death from cardiovascular causes. The variables included in the analysis included: vascular risk factors, carotid intima-media thickness (IMT), atherosclerotic burden and basal EPC and CEC count. Multivariate survival analysis was performed using Cox regression analysis. Results: During follow-up, 19 patients (12.66%) had a new vascular event (5 strokes; 3 TIAs; 4 AMI; 6 hospitalizations; 1 death). Vascular events were associated with age (P = 0.039), carotid IMT≥0.9 (P = 0.044), and EPC count (P = 0.041) in the univariate analysis. Multivariate Cox regression analysis showed an independent association with EPC in the lowest quartile (HR: 10.33, 95%CI (1.22-87.34), P = 0.032] and IMT≥0.9 [HR: 4.12, 95%CI (1.21-13.95), P = 0.023]. Conclusions: Basal EPC and IMT≥0.9 can predict future vascular events in patients with AMI and AS, but CEC count does not affect cardiovascular risk

    Genetic Variants in CETP Increase Risk of Intracerebral Hemorrhage

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    OBJECTIVE: In observational epidemiologic studies, higher plasma high-density lipoprotein cholesterol (HDL-C) has been associated with increased risk of intracerebral hemorrhage (ICH). DNA sequence variants that decrease cholesteryl ester transfer protein (CETP) gene activity increase plasma HDL-C; as such, medicines that inhibit CETP and raise HDL-C are in clinical development. Here, we test the hypothesis that CETP DNA sequence variants associated with higher HDL-C also increase risk for ICH.METHODS: We performed 2 candidate-gene analyses of CETP. First, we tested individual CETP variants in a discovery cohort of 1,149 ICH cases and 1,238 controls from 3 studies, followed by replication in 1,625 cases and 1,845 controls from 5 studies. Second, we constructed a genetic risk score comprised of 7 independent variants at the CETP locus and tested this score for association with HDL-C as well as ICH risk.RESULTS: Twelve variants within CETP demonstrated nominal association with ICH, with the strongest association at the rs173539 locus (odds ratio [OR] = 1.25, standard error [SE] = 0.06, p = 6.0 × 10(-4) ) with no heterogeneity across studies (I(2) = 0%). This association was replicated in patients of European ancestry (p = 0.03). A genetic score of CETP variants found to increase HDL-C by ∼2.85mg/dl in the Global Lipids Genetics Consortium was strongly associated with ICH risk (OR = 1.86, SE = 0.13, p = 1.39 × 10(-6) ).INTERPRETATION: Genetic variants in CETP associated with increased HDL-C raise the risk of ICH. Given ongoing therapeutic development in CETP inhibition and other HDL-raising strategies, further exploration of potential adverse cerebrovascular outcomes may be warranted. Ann Neurol 2016;80:730-740

    Fatigue in primary Sjögren's syndrome (pSS) is associated with lower levels of proinflammatory cytokines: a validation study

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    Primary Sjögren’s syndrome (pSS) is a chronic autoimmune rheumatic disease with symptoms including dryness, fatigue, and pain. The previous work by our group has suggested that certain proinflammatory cytokines are inversely related to patient-reported levels of fatigue. To date, these findings have not been validated. This study aims to validate this observation. Blood levels of seven cytokines were measured in 120 patients with pSS from the United Kingdom Primary Sjögren’s Syndrome Registry and 30 age-matched healthy non-fatigued controls. Patient-reported scores for fatigue were classified according to severity and compared to cytokine levels using analysis of variance. The differences between cytokines in cases and controls were evaluated using Wilcoxon test. A logistic regression model was used to determine the most important identifiers of fatigue. Five cytokines, interferon-γ-induced protein-10 (IP-10), tumour necrosis factor-α (TNFα), interferon-α (IFNα), interferon-γ (IFN-γ), and lymphotoxin-α (LT-α) were significantly higher in patients with pSS (n = 120) compared to non-fatigued controls (n = 30). Levels of two proinflammatory cytokines, TNF-α (p = 0.021) and LT-α (p = 0.043), were inversely related to patient-reported levels of fatigue. Cytokine levels, disease-specific and clinical parameters as well as pain, anxiety, and depression were used as predictors in our validation model. The model correctly identifies fatigue levels with 85% accuracy. Consistent with the original study, pain, depression, and proinflammatory cytokines appear to be the most powerful predictors of fatigue in pSS. TNF-α and LT-α have an inverse relationship with fatigue severity in pSS challenging the notion that proinflammatory cytokines directly mediate fatigue in chronic immunological conditions
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