Evaluation of factors affecting plate waste of inpatients in different healthcare settings.

INTRODUCTION AND AIMS: Satisfaction of inpatients with served food within a hospital care system still constitutes one of the main attempts to modernize food services. The impact of type of menu, food category, hospital centre and timetable on the meals wastage produced in different Spanish healthcare settings, was evaluated. METHODS: Meal wastage was measured through a semiquantitative 5-point scale ("nothing on plate"; "¼ on plate"; "half on plate"; "¾ on plate" and "all on plate"). The study was carried out in two periods of three months each in 2010 and 2011. A trained person took charge of measuring plate waste classified into 726 servings belonging to 11 menus. In total 31,392 plates were served to 7,868 inpatients. A Kruskal-Wallis non-parametric test (p < 0.05) was applied to evaluate significant differences among the variables studied. RESULTS: The menus were satisfactorily consumed because more than 50% of the plates were classified as "nothing on plate". Regarding food categories, 26.78% of the plates corresponded to soups and purées, while pasta and rice, and prepared foods were only distributed in 4-5% of the servings. Desserts were mostly consumed, while cooked vegetables were less accepted by the inpatients evaluated. Other factors such as hospital centre influenced plate waste (p < 0.05) but timetable did not (p > 0.05). CONCLUSION: Visual inspections of plate waste might be useful to optimize type and quality of menus served. The type of menu served and the food category could have a great influence on food acceptability by the inpatientsstudied.

Forest fires cluster detection with space-time scan statistics

Forest fires are defined as uncontrolled fires often occurring in wildland areas, but that can also affect houses or agricultural resources. Causes are both natural (e.g.,lightning phenomena) and anthropogenic (human negligence or arsons).Major environmental factors influencing the fire ignition and propagation are climate and vegetation. Wildfires are most common and severe during drought period and on windy days. Moreover, under water-stress conditions, which occur after a long hot and dry period, the vegetation is more vulnerable to fire. These conditions are common in the United State and Canada, where forest fires represent a big problem. We focused our analysis on the state of Florida, for which a big dataset on forest fires detection is readily available. USDA Forest Service Remote Sensing Application Center, in collaboration with NASA-Goddard Space Flight Center and the University of Maryland, has compiled daily MODIS Thermal Anomalies (fires and biomass burning images) produced by NASA using a contextual algorithm that exploits the strong emission of mid-infrared radiation from fires. Fire classes were converted in GIS format: daily MODIS fire detections are provided as the centroids of the 1 kilometer pixels and compiled into daily Arc/INFO point coverage.

Estimating Gross Value Added (GVA) across multiple scales: theoretical approach and empirical validation

This paper presents an application of the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach to the estimation of quantities of Gross Value Added (GVA) referring to economic entities defined at different scales of study. The method first estimates benchmark values of the pace of GVA generation per hour of labour across economic sectors. These values are estimated as intensive variables –e.g. €/hour– by dividing the various sectorial GVA of the country (expressed in € per year) by the hours of paid work in that same sector per year. This assessment is obtained using data referring to national statistics (top down information referring to the national level). Then, the approach uses bottom-up information (the number of hours of paid work in the various economic sectors of an economic entity –e.g. a city or a province– operating within the country) to estimate the amount of GVA produced by that entity. This estimate is obtained by multiplying the number of hours of work in each sector in the economic entity by the benchmark value of GVA generation per hour of work of that particular sector (national average). This method is applied and tested on two different socio-economic systems: (i) Catalonia (considered level n) and Barcelona (considered level n-1); and (ii) the region of Lima (considered level n) and Lima Metropolitan Area (considered level n-1). In both cases, the GVA per year of the local economic entity –Barcelona and Lima Metropolitan Area – is estimated and the resulting value is compared with GVA data provided by statistical offices. The empirical analysis seems to validate the approach, even though the case of Lima Metropolitan Area indicates a need for additional care when dealing with the estimate of GVA in primary sectors (agriculture and mining).

Epidemiology and antifungal susceptibility of bloodstream fungal isolates in pediatric patients: a Spanish multicenter prospective survey.

Data on fungemia epidemiology and antifungal susceptibility of isolates from children are scarce, leading frequently to pediatric empirical treatment based on available adult data. The present study was designed to update the epidemiological, mycological, and in vitro susceptibility data on fungal isolates from children with fungemia in Spain. All fungemia episodes were identified prospectively by blood culture over 13 months at 30 hospitals. Tests of susceptibility to amphotericin B, flucytosine, fluconazole, itraconazole, posaconazole, voriconazole, anidulafungin, caspofungin, and micafungin were performed at participant institutions by a microdilution colorimetric method. New species-specific clinical breakpoints for fluconazole, voriconazole, and echinocandins were also applied. A total of 203 episodes of fungemia in 200 children were identified. A higher proportion of fungal isolates was from general wards than intensive care units (ICU). Candida parapsilosis (46.8%), Candida albicans (36.5%), Candida tropicalis (5.9%), Candida glabrata (3.9%), and Candida guilliermondii (2.5%) were the leading species. C. parapsilosis was the predominant species except in neonates. C. albicans was the most frequent in neonatal ICU settings (51.9%). Intravascular catheter (79.3%), surgery (35%), prematurity (30%), and neutropenia (11%) were the most frequent predisposing factors. Most Candida isolates (95.1%) were susceptible to all antifungals. When the new species-specific clinical breakpoints were applied, all C. parapsilosis isolates were susceptible to echinocandins except one, which was micafungin resistant. This is the largest published series of fungemia episodes in the pediatric setting. C. parapsilosis is the most prevalent species in Spain, followed by C. albicans and C. tropicalis. Resistance to azole and echinocandin agents is extremely rare among Candida species. The fluconazole resistance rate in Spain has decreased in the last 10 years.

Qualité des statistiques de causes de décès: problèmes actuels et perspectives. [Quality of statistics on causes of death: current problems and perspectives].

Statistics of causes of death remain an important source of epidemiological data for the evaluation of various medical and health problems. The improvement of analytical techniques and, above all, the transformation of demographic and morbid structures of populations have prompted researchers in the field to give more importance to the quality of death certificates. After describing the data collection system presently used in Switzerland, the paper discusses various indirect estimations of the quality of Swiss data and reviews the corresponding international literature.

Adaptación y validación al español del cuestionario 4CornerSAT para la medida de la satisfacción profesional del personal médico de atención especializada.

BACKGROUND Satisfaction of physicians is a concern in the healthcare sector, and it requires a multi-dimensional questionnaire in Spanish which studies their high-order needs. The objectives of this study are to adapt the 4CornerSAT Questionnaire to measure career satisfaction of physicians and to evaluate its validity in our context. METHOD The 4CornerSAT Questionnaire was adapted into Spanish, validating it among physicians of hospitals in Andalusia, Spain. A confirmatory factor analysis (CFA) was performed to corroborate the a priori model, and it was evaluated the internal consistency and the construct validity through the Cronbach's alpha and the correlation between the scale and the global item, respectively. RESULTS The adapted questionnaire was administrated to 121 specialist physicians. The CFA corroborated the four dimensions of the questionnaire (χ2=114.64, df=94, p<0.07; χ2/df=1.22; RMSEA=0.04). The internal consistency obtained an α=0.92 and the correlation between the summed scale and the global item verified the construct validity (r=0.77; p<0.001). CONCLUSIONS The 4CornerSAT questionnaire was adapted to Spanish, identifying an adequate construct validity and internal consistency.

3-d residual eddy current field characterisation: applied to diffusion weighted magnetic resonance imaging.

Clinical use of the Stejskal-Tanner diffusion weighted images is hampered by the geometric distortions that result from the large residual 3-D eddy current field induced. In this work, we aimed to predict, using linear response theory, the residual 3-D eddy current field required for geometric distortion correction based on phantom eddy current field measurements. The predicted 3-D eddy current field induced by the diffusion-weighting gradients was able to reduce the root mean square error of the residual eddy current field to ~1 Hz. The model's performance was tested on diffusion weighted images of four normal volunteers, following distortion correction, the quality of the Stejskal-Tanner diffusion-weighted images was found to have comparable quality to image registration based corrections (FSL) at low b-values. Unlike registration techniques the correction was not hindered by low SNR at high b-values, and results in improved image quality relative to FSL. Characterization of the 3-D eddy current field with linear response theory enables the prediction of the 3-D eddy current field required to correct eddy current induced geometric distortions for a wide range of clinical and high b-value protocols.

Nutrient patterns and their food sources in an International Study Setting: report from the EPIC study.

BACKGROUND Compared to food patterns, nutrient patterns have been rarely used particularly at international level. We studied, in the context of a multi-center study with heterogeneous data, the methodological challenges regarding pattern analyses. METHODOLOGY/PRINCIPAL FINDINGS We identified nutrient patterns from food frequency questionnaires (FFQ) in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study and used 24-hour dietary recall (24-HDR) data to validate and describe the nutrient patterns and their related food sources. Associations between lifestyle factors and the nutrient patterns were also examined. Principal component analysis (PCA) was applied on 23 nutrients derived from country-specific FFQ combining data from all EPIC centers (N = 477,312). Harmonized 24-HDRs available for a representative sample of the EPIC populations (N = 34,436) provided accurate mean group estimates of nutrients and foods by quintiles of pattern scores, presented graphically. An overall PCA combining all data captured a good proportion of the variance explained in each EPIC center. Four nutrient patterns were identified explaining 67% of the total variance: Principle component (PC) 1 was characterized by a high contribution of nutrients from plant food sources and a low contribution of nutrients from animal food sources; PC2 by a high contribution of micro-nutrients and proteins; PC3 was characterized by polyunsaturated fatty acids and vitamin D; PC4 was characterized by calcium, proteins, riboflavin, and phosphorus. The nutrients with high loadings on a particular pattern as derived from country-specific FFQ also showed high deviations in their mean EPIC intakes by quintiles of pattern scores when estimated from 24-HDR. Center and energy intake explained most of the variability in pattern scores. CONCLUSION/SIGNIFICANCE The use of 24-HDR enabled internal validation and facilitated the interpretation of the nutrient patterns derived from FFQs in term of food sources. These outcomes open research opportunities and perspectives of using nutrient patterns in future studies particularly at international level.

Construcción y validación del cuestionario G_Clinic para medir la satisfacción laboral en profesionales de enfermería de las unidades de gestión clínica.

BACKGROUND Job satisfaction of nurses is a determinant factor in the quality and organizational adaptation of clinical management models in the current socio-economic context. The aim of this study was to construct and validate a questionnaire to measure job satisfaction of nurses in the Clinical Management Units in the Andalusian Public Health System. METHODS Clinimetric and cross-sectional study with a sample of 314 nurses of two university hospitals from Seville. Nurses were surveyed in 2011, from March to June. We used the Font Roja questionnaire adapted to our study variables. We performed analyses of correlations, reliability and construct validity, using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to test the a priori model. RESULTS The end questionnaire consists of 10 items, whose internal consistency was 0.75, with a percentage of variance explaining of 63.67%. CFA confirmed 4 dimensions (work environment, work relationships, motivation, and recognition): significant χ2 (p < .001); χ2/gl = 2.013; GFI= 0.958, RMR = 0.055 y RMSEA = 0.057; AGFI = 0.927, NFI = 0.878, TLI = 0.902, CFI =0.933 e IFI = 0.935; AIC = 132.486 y ECVI = 0.423. CONCLUSION This new questionnaire (G_Clinic) improves clinimetric values of the Font Roja questionnaire, because it reduces the number of items, improves the reliability of the dimensions, increases the value of variance explained, and allows knowing job satisfaction of nurses in clinical managementt.

A nuclear ribosomal DNA pseudogene in triatomines opens a new research field of fundamental and applied implications in Chagas disease

A pseudogene, designated as "ps(5.8S+ITS-2)", paralogous to the 5.8S gene and internal transcribed spacer (ITS)-2 of the nuclear ribosomal DNA (rDNA), has been recently found in many triatomine species distributed throughout North America, Central America and northern South America. Among characteristics used as criteria for pseudogene verification, secondary structures and free energy are highlighted, showing a lower fit between minimum free energy, partition function and centroid structures, although in given cases the fit only appeared to be slightly lower. The unique characteristics of "ps(5.8S+ITS-2)" as a processed or retrotransposed pseudogenic unit of the ghost type are reviewed, with emphasis on its potential functionality compared to the functionality of genes and spacers of the normal rDNA operon. Besides the technical problem of the risk for erroneous sequence results, the usefulness of "ps(5.8S+ITS-2)" for specimen classification, phylogenetic analyses and systematic/taxonomic studies should be highlighted, based on consistence and retention index values, which in pseudogenic sequence trees were higher than in functional sequence trees. Additionally, intraindividual, interpopulational and interspecific differences in pseudogene amount and the fact that it is a pseudogene in the nuclear rDNA suggests a potential relationships with fitness, behaviour and adaptability of triatomine vectors and consequently its potential utility in Chagas disease epidemiology and control.

Markov chain montecarlo method applied to rounding zeros of compositional data: first approach

As stated in Aitchison (1986), a proper study of relative variation in a compositional data set should be based on logratios, and dealing with logratios excludes dealing with zeros. Nevertheless, it is clear that zero observations might be present in real data sets, either because the corresponding part is completelyabsent –essential zeros– or because it is below detection limit –rounded zeros. Because the second kind of zeros is usually understood as “a trace too small to measure”, it seems reasonable to replace them by a suitable small value, and this has been the traditional approach. As stated, e.g. by Tauber (1999) and byMartín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000), the principal problem in compositional data analysis is related to rounded zeros. One should be careful to use a replacement strategy that does not seriously distort the general structure of the data. In particular, the covariance structure of the involvedparts –and thus the metric properties– should be preserved, as otherwise further analysis on subpopulations could be misleading. Following this point of view, a non-parametric imputation method isintroduced in Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000). This method is analyzed in depth by Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2003) where it is shown that thetheoretical drawbacks of the additive zero replacement method proposed in Aitchison (1986) can be overcome using a new multiplicative approach on the non-zero parts of a composition. The new approachhas reasonable properties from a compositional point of view. In particular, it is “natural” in the sense thatit recovers the “true” composition if replacement values are identical to the missing values, and it is coherent with the basic operations on the simplex. This coherence implies that the covariance structure of subcompositions with no zeros is preserved. As a generalization of the multiplicative replacement, in thesame paper a substitution method for missing values on compositional data sets is introduced

Truncated robust distance for clinical laboratory safety data monitoring and assessment.

Laboratory safety data are routinely collected in clinical studies for safety monitoring and assessment. We have developed a truncated robust multivariate outlier detection method for identifying subjects with clinically relevant abnormal laboratory measurements. The proposed method can be applied to historical clinical data to establish a multivariate decision boundary that can then be used for future clinical trial laboratory safety data monitoring and assessment. Simulations demonstrate that the proposed method has the ability to detect relevant outliers while automatically excluding irrelevant outliers. Two examples from actual clinical studies are used to illustrate the use of this method for identifying clinically relevant outliers.

Use of Hy's law and a new composite algorithm to predict acute liver failure in patients with drug-induced liver injury.

BACKGROUND & AIMS Hy's Law, which states that hepatocellular drug-induced liver injury (DILI) with jaundice indicates a serious reaction, is used widely to determine risk for acute liver failure (ALF). We aimed to optimize the definition of Hy's Law and to develop a model for predicting ALF in patients with DILI. METHODS We collected data from 771 patients with DILI (805 episodes) from the Spanish DILI registry, from April 1994 through August 2012. We analyzed data collected at DILI recognition and at the time of peak levels of alanine aminotransferase (ALT) and total bilirubin (TBL). RESULTS Of the 771 patients with DILI, 32 developed ALF. Hepatocellular injury, female sex, high levels of TBL, and a high ratio of aspartate aminotransferase (AST):ALT were independent risk factors for ALF. We compared 3 ways to use Hy's Law to predict which patients would develop ALF; all included TBL greater than 2-fold the upper limit of normal (×ULN) and either ALT level greater than 3 × ULN, a ratio (R) value (ALT × ULN/alkaline phosphatase × ULN) of 5 or greater, or a new ratio (nR) value (ALT or AST, whichever produced the highest ×ULN/ alkaline phosphatase × ULN value) of 5 or greater. At recognition of DILI, the R- and nR-based models identified patients who developed ALF with 67% and 63% specificity, respectively, whereas use of only ALT level identified them with 44% specificity. However, the level of ALT and the nR model each identified patients who developed ALF with 90% sensitivity, whereas the R criteria identified them with 83% sensitivity. An equal number of patients who did and did not develop ALF had alkaline phosphatase levels greater than 2 × ULN. An algorithm based on AST level greater than 17.3 × ULN, TBL greater than 6.6 × ULN, and AST:ALT greater than 1.5 identified patients who developed ALF with 82% specificity and 80% sensitivity. CONCLUSIONS When applied at DILI recognition, the nR criteria for Hy's Law provides the best balance of sensitivity and specificity whereas our new composite algorithm provides additional specificity in predicting the ultimate development of ALF.

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Modulatory effects of 5Hz rTMS over the primary somatosensory cortex in focal dystonia--an fMRI-TMS study.

Dystonia is associated with impaired somatosensory ability. The electrophysiological method of repetitive transcranial magnetic stimulation (rTMS) can be used for noninvasive stimulation of the human cortex and can alter cortical excitability and associated behavior. Among others, rTMS can alter/improve somatosensory discrimation abilities, as shown in healthy controls. We applied 5Hz-rTMS over the left primary somatosensory cortex (S1) in 5 patients with right-sided writer's dystonia and 5 controls. We studied rTMS effects on tactile discrimination accuracy and concomitant rTMS-induced changes in hemodynamic activity measured by functional magnetic resonance imaging (fMRI). Before rTMS, patients performed worse on the discrimination task than controls even though fMRI showed greater task-related activation bilaterally in the basal ganglia (BG). In controls, rTMS led to improved discrimination; fMRI revealed this was associated with increased activity of the stimulated S1, bilateral premotor cortex and BG. In dystonia patients, rTMS had no effect on discrimination; fMRI showed similar cortical effects to controls except for no effects in BG. Improved discrimination after rTMS in controls is linked to enhanced activation of S1 and BG. Failure of rTMS to increase BG activation in dystonia may be associated with the lack of effect on sensory discrimination in this group and may reflect impaired processing in BG-S1 connections. Alternatively, the increased BG activation seen in the baseline state without rTMS may reflect a compensatory strategy that saturates a BG contribution to this task.