8 resultados para decision support systems, GIS, interpolation, multiple regression


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Clinical Decision Support Systems (CDSS) are software applications that support clinicians in making healthcare decisions providing relevant information for individual patients about their specific conditions. The lack of integration between CDSS and Electronic Health Record (EHR) has been identified as a significant barrier to CDSS development and adoption. Andalusia Healthcare Public System (AHPS) provides an interoperable health information infrastructure based on a Service Oriented Architecture (SOA) that eases CDSS implementation. This paper details the deployment of a CDSS jointly with the deployment of a Terminology Server (TS) within the AHPS infrastructure. It also explains a case study about the application of decision support to thromboembolism patients and its potential impact on improving patient safety. We will apply the inSPECt tool proposal to evaluate the appropriateness of alerts in this scenario.

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The prefrontal (PFC) and orbitofrontal cortex (OFC) appear to be associated with both executive functions and olfaction. However, there is little data relating olfactory processing and executive functions in humans. The present study aimed at exploring the role of olfaction on executive functioning, making a distinction between primary and more cognitive aspects of olfaction. Three executive tasks of similar difficulty were used. One was used to assess hot executive functions (Iowa Gambling Task-IGT), and two as a measure of cold executive functioning (Stroop Colour and Word Test-SCWT and Wisconsin Card Sorting Test-WCST). Sixty two healthy participants were included: 31 with normosmia and 31 with hyposmia. Olfactory abilities were assessed using the ''Sniffin' Sticks'' test and the olfactory threshold, odour discrimination and odour identification measures were obtained. All participants were female, aged between 18 and 60. Results showed that participants with hyposmia displayed worse performance in decision making (IGT; Cohen's-d = 0.91) and cognitive flexibility (WCST; Cohen's-d between 0.54 and 0.68) compared to those with normosmia. Multiple regression adjusted by the covariates participants' age and education level showed a positive association between odour identification and the cognitive inhibition response (SCWT-interference; Beta = 0.29; p = .034). The odour discrimination capacity was not a predictor of the cognitive executive performance. Our results suggest that both hot and cold executive functions seem to be associated with higher-order olfactory functioning in humans. These results robustly support the hypothesis that olfaction and executive measures have a common neural substrate in PFC and OFC, and suggest that olfaction might be a reliable cognitive marker in psychiatric and neurologic disorders.

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Hyperuricaemia is one of the components of metabolic syndrome. Both oxidative stress and hyperinsulinism are important variables in the genesis of this syndrome and have a close association with uric acid (UA). We evaluated the effect of an oral glucose challenge on UA concentrations. The study included 656 persons aged 18 to 65 years. Glycaemia, insulin, UA and plasma proteins were measured at baseline and 120 min after an oral glucose tolerance test (OGTT). The baseline sample also included measurements of total cholesterol, triacylglycerol (TAG) and HDL-cholesterol. Insulin resistance was calculated with the homeostasis model assessment. UA levels were significantly lower after the OGTT (281.93 (sd 92.19) v. 267.48 (sd 90.40) micromol/l; P < 0.0001). Subjects with a drop in UA concentrations >40.86 micromol/l (>75th percentile) had higher plasma TAG levels (P = 0.0001), baseline insulin (P = 0.02) and greater insulin resistance (P = 0.034). Women with a difference in plasma concentrations of UA above the 75th percentile had higher baseline insulin levels (P = 0.019), concentration of plasma TAG (P = 0.0001) and a greater insulin resistance index (P = 0.029), whereas the only significant difference in men was the level of TAG. Multiple regression analysis showed that the basal TAG levels, insulin at 120 min, glycaemia at 120 min and waist:hip ratio significantly predicted the variance in the UA difference (r2 0.077). Levels of UA were significantly lower after the OGTT and the individuals with the greatest decrease in UA levels are those who have greater insulin resistance and higher TAG levels.

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Oxidative modification of LDL is thought to play an important role in the development of atherosclerosis. Susceptibility of LDL to peroxidation may partly depend on the compositional characteristics of the antioxidant and fatty acid content. The aim of this study was to examine the association between levels of antibodies to oxidized LDL and the various serum fatty acids in women. A total of 465 women aged 18-65 years were selected randomly from the adult population census of Pizarra, a town in southern Spain. Measurement of anti-oxidized-LDL was done by ELISA and the fatty acid composition of serum phospholipids was determined by GC. The levels of anti-oxidized-LDL antibodies were significantly related with age (r - 0.341, P < 0.001), BMI (r - 0.239, P < 0.001), waist:hip ratio (r - 0.285, P < 0.001), glucose (r - 0.208, P < 0.001), cholesterol (r - 0.243, P < 0.001), LDL-cholesterol (r - 0.185, P = 0.002), EPA (r - 0.159, P = 0.003), DHA (r - 0.121, P = 0.026), and the sum of the serum phospholipid n-3 PUFA (r - 0.141, P = 0.009). Multiple regression analysis showed that the variables that explained the behaviour of the levels of anti-oxidized-LDL antibodies were age (P < 0.001) and the serum phospholipid EPA (P < 0.001). This study showed that the fatty acid composition of serum phospholipids, and especially the percentage of EPA, was inversely related with the levels of anti-oxidized-LDL antibodies.

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BACKGROUND Adipose tissue lipid storage and processing capacity can be a key factor for obesity-related metabolic disorders such as insulin resistance and diabetes. Lipid uptake is the first step to adipose tissue lipid storage. The aim of this study was to analyze the gene expression of factors involved in lipid uptake and processing in subcutaneous (SAT) and visceral (VAT) adipose tissue according to body mass index (BMI) and the degree of insulin resistance (IR). METHODS AND PRINCIPAL FINDINGS VLDL receptor (VLDLR), lipoprotein lipase (LPL), acylation stimulating protein (ASP), LDL receptor-related protein 1 (LRP1) and fatty acid binding protein 4 (FABP4) gene expression was measured in VAT and SAT from 28 morbidly obese patients with Type 2 Diabetes Mellitus (T2DM) or high IR, 10 morbidly obese patients with low IR, 10 obese patients with low IR and 12 lean healthy controls. LPL, FABP4, LRP1 and ASP expression in VAT was higher in lean controls. In SAT, LPL and FABP4 expression were also higher in lean controls. BMI, plasma insulin levels and HOMA-IR correlated negatively with LPL expression in both VAT and SAT as well as with FABP4 expression in VAT. FABP4 gene expression in SAT correlated inversely with BMI and HOMA-IR. However, multiple regression analysis showed that BMI was the main variable contributing to LPL and FABP4 gene expression in both VAT and SAT. CONCLUSIONS Morbidly obese patients have a lower gene expression of factors related with lipid uptake and processing in comparison with healthy lean persons.

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BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

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INTRODUCTION Selenium is an essential micronutrient for human health, being a cofactor for enzymes with antioxidant activity that protect the organism from oxidative damage. An inadequate intake of this mineral has been associated with the onset and progression of chronic diseases such as hypertension, diabetes, coronary diseases, asthma, and cancer. For this reason, knowledge of the plasma and erythrocyte selenium levels of a population makes a relevant contribution to assessment of its nutritional status. OBJECTIVE The objective of the present study was to determine the nutritional status of selenium and risk of selenium deficiency in a healthy adult population in Spain by examining food and nutrient intake and analyzing biochemical parameters related to selenium metabolism, including plasma and erythrocyte levels and selenium-dependent glutathione peroxidase (GPx) enzymatic activity. MATERIAL AND METHODS We studied 84 healthy adults (31 males and 53 females) from the province of Granada, determining their plasma and erythrocyte selenium concentrations and the association of these levels with the enzymatic activity of glutathione peroxidase (GPx) and with life style factors. We also gathered data on their food and nutrient intake and the results of biochemical analyses. Correlations were studied among all of these variables. RESULTS The mean plasma selenium concentration was 76.6 ± 17.3 μg/L (87.3 ± 17.4 μg/L in males, 67.3 ± 10.7 μg/L in females), whereas the mean erythrocyte selenium concentration was 104.6 μg/L (107.9 ± 26.1 μg/L in males and 101.7 ± 21.7 μg/L in females). The nutritional status of selenium was defined by the plasma concentration required to reach maximum GPx activity, establishing 90 μg/L as reference value. According to this criterion, 50% of the men and 53% of the women were selenium deficient. CONCLUSIONS Selenium is subjected to multiple regulation mechanisms. Erythrocyte selenium is a good marker of longer term selenium status, while plasma selenium appears to be a marker of short-term nutritional status. The present findings indicate a positive correlation between plasma selenium concentration and the practice of physical activity. Bioavailability studies are required to establish appropriate reference levels of this mineral for the Spanish population.

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The restoration of body composition (BC) parameters is considered to be one of the most important goals in the treatment of patients with anorexia nervosa (AN). However, little is known about differences between AN diagnostic subtypes [restricting (AN-R) and binge/purging (AN-BP)] and weekly changes in BC during refeeding treatment. Therefore, the main objectives of our study were twofold: 1) to assess the changes in BC throughout nutritional treatment in an AN sample and 2) to analyze predictors of BC changes during treatment, as well as predictors of treatment outcome. The whole sample comprised 261 participants [118 adult females with AN (70 AN-R vs. 48 AN-BP), and 143 healthy controls]. BC was measured weekly during 15 weeks of day-hospital treatment using bioelectrical impedance analysis (BIA). Assessment measures also included the Eating Disorders Inventory-2, as well as a number of other clinical indices. Overall, the results showed that AN-R and AN-BP patients statistically differed in all BC measures at admission. However, no significant time×group interaction was found for almost all BC parameters. Significant time×group interactions were only found for basal metabolic rate (p = .041) and body mass index (BMI) (p = .035). Multiple regression models showed that the best predictors of pre-post changes in BC parameters (namely fat-free mass, muscular mass, total body water and BMI) were the baseline values of BC parameters. Stepwise predictive logistic regressions showed that only BMI and age were significantly associated with outcome, but not with the percentage of body fat. In conclusion, these data suggest that although AN patients tended to restore all BC parameters during nutritional treatment, only AN-BP patients obtained the same fat mass values as healthy controls. Put succinctly, the best predictors of changes in BC were baseline BC values, which did not, however, seem to influence treatment outcome.