The prognostic value of health-related quality-of-life data in predicting survival in glioblastoma cancer patients: results from an international randomised phase III EORTC Brain Tumour and Radiation Oncology Groups, and NCIC Clinical Trials Group study.

This is one of the few studies that have explored the value of baseline symptoms and health-related quality of life (HRQOL) in predicting survival in brain cancer patients. Baseline HRQOL scores (from the EORTC QLQ-C30 and the Brain Cancer Module (BN 20)) were examined in 490 newly diagnosed glioblastoma cancer patients for the relationship with overall survival by using Cox proportional hazards regression models. Refined techniques as the bootstrap re-sampling procedure and the computation of C-indexes and R(2)-coefficients were used to try and validate the model. Classical analysis controlled for major clinical prognostic factors selected cognitive functioning (P=0.0001), global health status (P=0.0055) and social functioning (P<0.0001) as statistically significant prognostic factors of survival. However, several issues question the validity of these findings. C-indexes and R(2)-coefficients, which are measures of the predictive ability of the models, did not exhibit major improvements when adding selected or all HRQOL scores to clinical factors. While classical techniques lead to positive results, more refined analyses suggest that baseline HRQOL scores add relatively little to clinical factors to predict survival. These results may have implications for future use of HRQOL as a prognostic factor in cancer patients.

Efficacy of two educational interventions about inhalation techniques in patients with chronic obstructive pulmonary disease (COPD). TECEPOC: study protocol for a partially randomized controlled trial (preference trial).

BACKGROUND Drugs for inhalation are the cornerstone of therapy in obstructive lung disease. We have observed that up to 75 % of patients do not perform a correct inhalation technique. The inability of patients to correctly use their inhaler device may be a direct consequence of insufficient or poor inhaler technique instruction. The objective of this study is to test the efficacy of two educational interventions to improve the inhalation techniques in patients with Chronic Obstructive Pulmonary Disease (COPD). METHODS This study uses both a multicenter patients´ preference trial and a comprehensive cohort design with 495 COPD-diagnosed patients selected by a non-probabilistic method of sampling from seven Primary Care Centers. The participants will be divided into two groups and five arms. The two groups are: 1) the patients´ preference group with two arms and 2) the randomized group with three arms. In the preference group, the two arms correspond to the two educational interventions (Intervention A and Intervention B) designed for this study. In the randomized group the three arms comprise: intervention A, intervention B and a control arm. Intervention A is written information (a leaflet describing the correct inhalation techniques). Intervention B is written information about inhalation techniques plus training by an instructor. Every patient in each group will be visited six times during the year of the study at health care center. DISCUSSION Our hypothesis is that the application of two educational interventions in patients with COPD who are treated with inhaled therapy will increase the number of patients who perform a correct inhalation technique by at least 25 %. We will evaluate the effectiveness of these interventions on patient inhalation technique improvement, considering that it will be adequate and feasible within the context of clinical practice.

Lésions cérébrales du prématuré et techniques d'imagerie à visée pronostique du développement neurocognitif [Cerebral brain injury in preterm infants and the role of neuroimaging in predicting neurodevelopmental outcomes].

Due to advances in neonatal intensive care over the last decades, the pattern of brain injury seen in very preterm infants has evolved in more subtle lesions that are still essential to diagnose in regard to neurodevelopmental outcome. While cranial ultrasound is still used at the bedside, magnetic resonance imaging (MRI) is becoming increasingly used in this population for the assessment of brain maturation and white and grey matter lesions. Therefore, MRI provides a better prognostic value for the neurodevelopmental outcome of these preterms. Furthermore, the development of new MRI techniques, such as diffusion tensor imaging, resting state functional connectivity and magnetic resonance spectroscopy, may further increase the prognostic value, helping to counsel parents and allocate early intervention services.

Microarray profiling of mononuclear peripheral blood cells identifies novel candidate genes related to chemoradiation response in rectal cancer.

Preoperative chemoradiation significantly improves oncological outcome in locally advanced rectal cancer. However there is no effective method of predicting tumor response to chemoradiation in these patients. Peripheral blood mononuclear cells have emerged recently as pathology markers of cancer and other diseases, making possible their use as therapy predictors. Furthermore, the importance of the immune response in radiosensivity of solid organs led us to hypothesized that microarray gene expression profiling of peripheral blood mononuclear cells could identify patients with response to chemoradiation in rectal cancer. Thirty five 35 patients with locally advanced rectal cancer were recruited initially to perform the study. Peripheral blood samples were obtained before neaodjuvant treatment. RNA was extracted and purified to obtain cDNA and cRNA for hybridization of microarrays included in Human WG CodeLink bioarrays. Quantitative real time PCR was used to validate microarray experiment data. Results were correlated with pathological response, according to Mandard´s criteria and final UICC Stage (patients with tumor regression grade 1-2 and downstaging being defined as responders and patients with grade 3-5 and no downstaging as non-responders). Twenty seven out of 35 patients were finally included in the study. We performed a multiple t-test using Significance Analysis of Microarrays, to find those genes differing significantly in expression, between responders (n = 11) and non-responders (n = 16) to CRT. The differently expressed genes were: BC 035656.1, CIR, PRDM2, CAPG, FALZ, HLA-DPB2, NUPL2, and ZFP36. The measurement of FALZ (p = 0.029) gene expression level determined by qRT-PCR, showed statistically significant differences between the two groups. Gene expression profiling reveals novel genes in peripheral blood samples of mononuclear cells that could predict responders and non-responders to chemoradiation in patients with locally advanced rectal cancer. Moreover, our investigation added further evidence to the importance of mononuclear cells' mediated response in the neoadjuvant treatment of rectal cancer.

Techniques for the detection of pathogenic Cryptococcus species in wood decay substrata and the evaluation of viability in stored samples

In this study, we evaluated several techniques for the detection of the yeast form of Cryptococcus in decaying wood and measured the viability of these fungi in environmental samples stored in the laboratory. Samples were collected from a tree known to be positive for Cryptococcus and were each inoculated on 10 Niger seed agar (NSA) plates. The conventional technique (CT) yielded a greater number of positive samples and indicated a higher fungal density [in colony forming units per gram of wood (CFU.g-1)] compared to the humid swab technique (ST). However, the difference in positive and false negative results between the CT-ST was not significant. The threshold of detection for the CT was 0.05.10³ CFU.g-1, while the threshold for the ST was greater than 0.1.10³ CFU-1. No colonies were recovered using the dry swab technique. We also determined the viability of Cryptococcus in wood samples stored for 45 days at 25ºC using the CT and ST and found that samples not only continued to yield a positive response, but also exhibited an increase in CFU.g-1, suggesting that Cryptococcus is able to grow in stored environmental samples. The ST.1, in which samples collected with swabs were immediately plated on NSA medium, was more efficient and less laborious than either the CT or ST and required approximately 10 min to perform; however, additional studies are needed to validate this technique.

Risk of type 2 diabetes according to traditional and emerging anthropometric indices in Spain, a Mediterranean country with high prevalence of obesity: results from a large-scale prospective cohort study.

Background: Obesity is a major risk factor for type 2 diabetes mellitus (T2DM). A proper anthropometric characterisation of T2DM risk is essential for disease prevention and clinical risk assessement. Methods: Longitudinal study in 37 733 participants (63% women) of the Spanish EPIC (European Prospective Investigation into Cancer and Nutrition) cohort without prevalent diabetes. Detailed questionnaire information was collected at baseline and anthropometric data gathered following standard procedures. A total of 2513 verified incident T2DM cases occurred after 12.1 years of mean follow-up. Multivariable Cox regression was used to calculate hazard ratios of T2DM by levels of anthropometric variables. Results: Overall and central obesity were independently associated with T2DM risk. BMI showed the strongest association with T2DM in men whereas waist-related indices were stronger independent predictors in women. Waist-to-height ratio revealed the largest area under the ROC curve in men and women, with optimal cut-offs at 0.60 and 0.58, respectively. The most discriminative waist circumference (WC) cut-off values were 99.4 cm in men and 90.4 cm in women. Absolute risk of T2DM was higher in men than women for any combination of age, BMI and WC categories, and remained low in normal-waist women. The population risk of T2DM attributable to obesity was 17% in men and 31% in women. Conclusions: Diabetes risk was associated with higher overall and central obesity indices even at normal BMI and WC values. The measurement of waist circumference in the clinical setting is strongly recommended for the evaluation of future T2DM risk in women.

Development and validation of a risk score predicting substantial weight gain over 5 years in middle-aged European men and women.

BACKGROUND Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population. METHODS We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥ 10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample). RESULTS Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥ 200 points were 9% and 96%, respectively. CONCLUSION The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.

The association between dietary energy density and type 2 diabetes in Europe: results from the EPIC-InterAct Study

BACKGROUND Observational studies implicate higher dietary energy density (DED) as a potential risk factor for weight gain and obesity. It has been hypothesized that DED may also be associated with risk of type 2 diabetes (T2D), but limited evidence exists. Therefore, we investigated the association between DED and risk of T2D in a large prospective study with heterogeneity of dietary intake. METHODOLOGY/PRINCIPAL FINDINGS A case-cohort study was nested within the European Prospective Investigation into Cancer (EPIC) study of 340,234 participants contributing 3.99 million person years of follow-up, identifying 12,403 incident diabetes cases and a random subcohort of 16,835 individuals from 8 European countries. DED was calculated as energy (kcal) from foods (except beverages) divided by the weight (gram) of foods estimated from dietary questionnaires. Prentice-weighted Cox proportional hazard regression models were fitted by country. Risk estimates were pooled by random effects meta-analysis and heterogeneity was evaluated. Estimated mean (sd) DED was 1.5 (0.3) kcal/g among cases and subcohort members, varying across countries (range 1.4-1.7 kcal/g). After adjustment for age, sex, smoking, physical activity, alcohol intake, energy intake from beverages and misreporting of dietary intake, no association was observed between DED and T2D (HR 1.02 (95% CI: 0.93-1.13), which was consistent across countries (I(2) = 2.9%). CONCLUSIONS/SIGNIFICANCE In this large European case-cohort study no association between DED of solid and semi-solid foods and risk of T2D was observed. However, despite the fact that there currently is no conclusive evidence for an association between DED and T2DM risk, choosing low energy dense foods should be promoted as they support current WHO recommendations to prevent chronic diseases.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

An empirical study of machine learning techniques applied to image watermarking

A study of how the machine learning technique, known as gentleboost, could improve different digital watermarking methods such as LSB, DWT, DCT2 and Histogram shifting.

Estudio de los exitus con diagnóstico secundario de desnutrición en un hospital de tercer nivel.

BACKGROUND: Malnutrition is a major public health problems, according to WHO, is the leading cause of death, when it affects the group of hospitalized patients, making denominating separate entity "hospital malnutrition". OBJECTIVES: The overall objective is to quantify the main diagnoses frequently high, causing exitus, with secondary diagnosis of malnutrition. METHODS: This is a descriptive study, which included all hospital discharges in 2011 and first half of 2012, which have been exitus and whose secondary diagnosis of malnutrition, with the total of 33. We performed a descriptive analysis, effected the Mann-Whitney nonparametric test (p < 0.05). RESULTS: The most frequent main diagnoses among 33 analyzed are high sepsis (12.1%), liver metastases (9.1%), pneumonia (6.1%), acute respiratory failure (6.1%) and renal acute renal (6.1%). CONCLUSIONS: Although the most frequent primary diagnosis of sepsis, by grouping the diagnoses, the most frequent DRG is respiratory disease, so it has to make comprehensive and quality coding to adjust the relative weight of the same reality. It is essential to specify the source of clinical information used for coding, the degree of malnutrition, for greater specificity in the data.

Comparison of drug survival rates for tumor necrosis factor antagonists in rheumatoid arthritis.

BACKGROUND Persistence of anti-tumor necrosis factor (TNF) therapy in rheumatoid arthritis (RA) is an overall marker of treatment success. OBJECTIVE To assess the survival of anti-TNF treatment and to define the potential predictors of drug discontinuation in RA, in order to verify the adequacy of current practices. DESIGN An observational, descriptive, longitudinal, retrospective study. SETTING The Hospital Clínico Universitario de Valladolid, Valladolid, Spain. PATIENTS RA patients treated with anti-TNF therapy between January 2011 and January 2012. MEASUREMENTS Demographic information and therapy assessments were gathered from medical and pharmaceutical records. Data is expressed as means (standard deviations) for quantitative variables and frequency distribution for qualitative variables. Kaplan-Meier survival analysis was used to assess persistence, and Cox multivariate regression models were used to assess potential predictors of treatment discontinuation. RESULTS In total, 126 treatment series with infliximab (n = 53), etanercept (n = 51) or adalimumab (n = 22) were administered to 91 patients. Infliximab has mostly been used as a first-line treatment, but it was the drug with the shortest time until a change of treatment. Significant predictors of drug survival were: age; the anti-TNF agent; and the previous response to an anti-TNF drug. LIMITATION The small sample size. CONCLUSION The overall efficacy of anti-TNF drugs diminishes with time, with infliximab having the shortest time until a change of treatment. The management of biologic therapy in patients with RA should be reconsidered in order to achieve disease control with a reduction in costs.

Neurological complications of infective endocarditis: risk factors, outcome, and impact of cardiac surgery: a multicenter observational study.

BACKGROUND The purpose of this study was to assess the incidence of neurological complications in patients with infective endocarditis, the risk factors for their development, their influence on the clinical outcome, and the impact of cardiac surgery. METHODS AND RESULTS This was a retrospective analysis of prospectively collected data on a multicenter cohort of 1345 consecutive episodes of left-sided infective endocarditis from 8 centers in Spain. Cox regression models were developed to analyze variables predictive of neurological complications and associated mortality. Three hundred forty patients (25%) experienced such complications: 192 patients (14%) had ischemic events, 86 (6%) had encephalopathy/meningitis, 60 (4%) had hemorrhages, and 2 (1%) had brain abscesses. Independent risk factors associated with all neurological complications were vegetation size ≥3 cm (hazard ratio [HR] 1.91), Staphylococcus aureus as a cause (HR 2.47), mitral valve involvement (HR 1.29), and anticoagulant therapy (HR 1.31). This last variable was particularly related to a greater incidence of hemorrhagic events (HR 2.71). Overall mortality was 30%, and neurological complications had a negative impact on outcome (45% of deaths versus 24% in patients without these complications; P<0.01), although only moderate to severe ischemic stroke (HR 1.63) and brain hemorrhage (HR 1.73) were significantly associated with a poorer prognosis. Antimicrobial treatment reduced (by 33% to 75%) the risk of neurological complications. In patients with hemorrhage, mortality was higher when surgery was performed within 4 weeks of the hemorrhagic event (75% versus 40% in later surgery). CONCLUSIONS Moderate to severe ischemic stroke and brain hemorrhage were found to have a significant negative impact on the outcome of infective endocarditis. Early appropriate antimicrobial treatment is critical, and transitory discontinuation of anticoagulant therapy should be considered.

Evidence of new risk genetic factor to systemic lupus erythematosus: the UBASH3A gene

The ubiquitin associated and Src-homology 3 (SH3) domain containing A (UBASH3a) is a suppressor of T-cell receptor signaling, underscoring antigen presentation to T-cells as a critical shared mechanism of diseases pathogenesis. The aim of the present study was to determine whether the UBASH3a gene influence the susceptibility to systemic lupus erythematosus (SLE) in Caucasian populations. We evaluated five UBASH3a polymorphisms (rs2277798, rs2277800, rs9976767, rs13048049 and rs17114930), using TaqMan® allelic discrimination assays, in a discovery cohort that included 906 SLE patients and 1165 healthy controls from Spain. The SNPs that exhibit statistical significance difference were evaluated in a German replication cohort of 360 SLE patients and 379 healthy controls. The case-control analysis in the Spanish population showed a significant association between the rs9976767 and SLE (Pc = 9.9E-03 OR = 1.21 95%CI = 1.07-1.37) and a trend of association for the rs2277798 analysis (P = 0.09 OR = 0.9 95%CI = 0.79-1.02). The replication in a German cohort and the meta-analysis confirmed that the rs9976767 (Pc = 0.02; Pc = 2.4E-04, for German cohort and meta-analysis, respectively) and rs2277798 (Pc = 0.013; Pc = 4.7E-03, for German cohort and meta-analysis, respectively) UBASH3a variants are susceptibility factors for SLE. Finally, a conditional regression analysis suggested that the most likely genetic variation responsible for the association was the rs9976767 polymorphism. Our results suggest that UBASH3a gene plays a role in the susceptibility to SLE. Moreover, our study indicates that UBASH3a can be considered as a common genetic factor in autoimmune diseases.

Computer-assisted cup placement techniques in total hip arthroplasty improve accuracy of placement.

Malposition of the acetabular component during hip arthroplasty increases the occurrence of impingement, reduces range of motion, and increases the risk of dislocation and long-term wear. To prevent malpositioned hip implants, an increasing number of computer-assisted orthopaedic systems have been described, but their accuracy is not well established. The purpose of this study was to determine the reproducibility and accuracy of conventional versus computer-assisted techniques for positioning the acetabular component in total hip arthroplasty. Using a lateral approach, 150 cups were placed by 10 surgeons in 10 identical plastic pelvis models (freehand, with a mechanical guide, using computer assistance). Conditions for cup implantations were made to mimic the operating room situation. Preoperative planning was done from a computed tomography scan. The accuracy of cup abduction and anteversion was assessed with an electromagnetic system. Freehand placement revealed a mean accuracy of cup anteversion and abduction of 10 degrees and 3.5 degrees, respectively (maximum error, 35 degrees). With the cup positioner, these angles measured 8 degrees and 4 degrees (maximum error, 29.8 degrees), respectively, and using computer assistance, 1.5 degrees and 2.5 degrees degrees (maximum error, 8 degrees), respectively. Computer-assisted cup placement was an accurate and reproducible technique for total hip arthroplasty. It was more accurate than traditional methods of cup positioning.