907 resultados para Observational methodologies
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BACKGROUND: Studies carried out on specific travelers' groups such as students describe an increase in the consumption of alcohol and drugs during travel and vacation time. The present study investigates the risk behaviors (alcohol and drugs) in a general adult population in Switzerland travelling abroad who visited a travel clinic before departure. METHODS: This retrospective study was conducted in a travel clinic between January 2006 and December 2008. 14,496 patients came to the clinic for a pre-travel consultation. 3,537 of them answered a questionnaire about their life habits in Switzerland and during their last trip. The only exclusion criterion was an age inferior to 18 years old.The consumption habits of drugs and at-risk alcohol intake (8 standard drinks (SD) per week for women and 15 SD for men) was analyzed according to gender, sex, destination and profession. Predictors of adopting a risky behavior between habits in Switzerland and during their previous trip were also analyzed. RESULTS: 7% (229/3477) of participants declared having at-risk alcohol consumption in Switzerland and 14% (473/3275 [95% CI 13-16]) during their trip. 9% (332/3527) of the participants used drugs in Switzerland and 5% (178/3481) during their trip. Risk factors for at-risk alcohol consumption during a trip were: at-risk alcohol consumption in Switzerland (OR 31[95% CI 21-45]), smoking (1.7 [95% CI 1-2]), use of drugs in Switzerland (OR 2.2 [95% CI 2-3]), leisure travel (OR 1.6 [95% CI 1-2]) and managerial professions (OR 1.8 [95% CI 1-3]). Risk factors for the use of drugs during a trip were: alcohol consumption in Switzerland (OR 2.1 [95% CI 1-4]), smoking (OR 1.9 [95% CI 1-3]), and use of drugs in Switzerland (OR 29.7 [95% CI 19-45]). CONCLUSIONS: At-risk alcohol consumption and, to a lesser extent, use of drugs, affect a large number of travelers which expose them to health problems during a trip. Exploring the alcohol and drugs consumption patterns of people visiting a travel clinic should be part of the pre-travel routine consultation and would allow to identifying people who would benefit most from a specific prevention.
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This paper presents an observational study of the tornado outbreak that took place on the 7 September 2005 in the Llobregat delta river, affecting a densely populated and urbanised area and the Barcelona International airport (NE Spain). The site survey confirmed at least five short-lived tornadoes. Four of them were weak (F0, F1) and the other one was significant (F2 on the Fujita scale). They started mostly as waterspouts and moved later inland causing extensive damage estimated in 9 million Euros, three injured people but fortunately no fatalities. Large scale forcing was provided by upper level diffluence and low level warm air advection. Satellite and weather radar images revealed the development of the cells that spawned the waterspouts along a mesoscale convergence line in a highly sheared and relatively low buoyant environment. Further analysis indicated characteristics that could be attributed indistinctively to non-supercell or to mini-supercell thunderstorms.
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The current operational very short-term and short-term quantitative precipitation forecast (QPF) at the Meteorological Service of Catalonia (SMC) is made by three different methodologies: Advection of the radar reflectivity field (ADV), Identification, tracking and forecasting of convective structures (CST) and numerical weather prediction (NWP) models using observational data assimilation (radar, satellite, etc.). These precipitation forecasts have different characteristics, lead time and spatial resolutions. The objective of this study is to combine these methods in order to obtain a single and optimized QPF at each lead time. This combination (blending) of the radar forecast (ADV and CST) and precipitation forecast from NWP model is carried out by means of different methodologies according to the prediction horizon. Firstly, in order to take advantage of the rainfall location and intensity from radar observations, a phase correction technique is applied to the NWP output to derive an additional corrected forecast (MCO). To select the best precipitation estimation in the first and second hour (t+1 h and t+2 h), the information from radar advection (ADV) and the corrected outputs from the model (MCO) are mixed by using different weights, which vary dynamically, according to indexes that quantify the quality of these predictions. This procedure has the ability to integrate the skill of rainfall location and patterns that are given by the advection of radar reflectivity field with the capacity of generating new precipitation areas from the NWP models. From the third hour (t+3 h), as radar-based forecasting has generally low skills, only the quantitative precipitation forecast from model is used. This blending of different sources of prediction is verified for different types of episodes (convective, moderately convective and stratiform) to obtain a robust methodology for implementing it in an operational and dynamic way.
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On 1 January 2012 Swiss Diagnosis Related Groups (DRG), a new uniform payment system for in-patients was introduced in Switzerland with the intention to replace a "cost-based" with a "case-based" reimbursement system to increase efficiency. With the introduction of the new payment system we aim to answer questions raised regarding length of stay as well as patients' outcome and satisfaction. This is a prospective, two-centre observational cohort study with data from University Hospital Basel and the Cantonal Hospital Aarau, Switzerland, from January to June 2011 and 2012, respectively. Consecutive in-patients with the main diagnosis of either community-acquired pneumonia, exacerbation of COPD, acute heart failure or hip fracture were included. A questionnaire survey was sent out after discharge investigating changes before and after SwissDRG implementation. Our primary endpoint was LOS. Of 1,983 eligible patients 841 returned the questionnaire and were included into the analysis (429 in 2011, 412 in 2012). The median age was 76.7 years (50.8% male). Patients in the two years were well balanced in regard to main diagnoses and co-morbidities. Mean LOS in the overall patient population was 10.0 days and comparable between the 2011 cohort and the 2012 cohort (9.7 vs 10.3; p = 0.43). Overall satisfaction with care changed only slightly after introduction of SwissDRG and remained high (89.0% vs 87.8%; p = 0.429). Investigating the influence of the implementation of SwissDRG in 2012 regarding LOS patients' outcome and satisfaction, we found no significant changes. However, we observed some noteworthy trends, which should be monitored closely.
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Background. Early identification of pathogens from blood cultures using matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry may optimize the choice of empirical antibiotic therapy in the setting of bloodstream infections. We aimed to assess the impact of this new technology on the use of antibiotic treatment in patients with gram-negative bacteremia. Methods. We conducted a prospective observational study from January to December 2010 to evaluate the sequential and separate impacts of Gram stain reporting and MALDI-TOF bacterial identification performed on blood culture pellets in patients with gram-negative bacteremia. The primary outcome was the impact of MALDI-TOF on empirical antibiotic choice. Results. Among 202 episodes of gram-negative bacteremia, Gram stain reporting had an impact in 42 cases (20.8%). MALDI-TOF identification led to a modification of empirical therapy in 71 of all 202 cases (35.1%), and in 16 of 27 cases (59.3%) of monomicrobial bacteremia caused by AmpC-producing Enterobacteriaceae. The most frequently observed impact was an early appropriate broadening of the antibiotic spectrum in 31 of 71 cases (43.7%). In total, 143 of 165 episodes (86.7%) of monomicrobial bacteremia were correctly identified at genus level by MALDI-TOF. Conclusions. In a low prevalence area for extended spectrum betalactamases (ESBL) and multiresistant gram-negative bacteria, MALDI-TOF performed on blood culture pellets had an impact on the clinical management of 35.1% of all gram-negative bacteremia cases, demonstrating a greater impact than Gram stain reporting. Thus, MALDI-TOF could become a vital second step beside Gram stain in guiding the empirical treatment of patients with bloodstream infection.
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BACKGROUND: Rotational thromboelastometry (ROTEM) is a whole blood point-of-test used to assess the patient's coagulation status. Three of the available ROTEM tests are EXTEM, INTEM and HEPTEM. In the latter, heparinase added to the INTEM reagent inactivates heparin to reveal residual heparin effect. Performing ROTEM analysis during cardiopulmonary bypass (CPB) might allow the anaesthesiologist to anticipate the need for blood products. OBJECTIVE: The goal of this study was to validate ROTEM analysis in the presence of very high heparin concentrations during CPB. DESIGN: Prospective, observational trial. SETTING: Single University Hospital. PARTICIPANTS: Twenty patients undergoing coronary artery bypass grafting. MAIN OUTCOME MEASURE: ROTEM analysis was performed before heparin administration (T0), 10 min after heparin (T1), at the end of CPB (T2) and 10 min after protamine (T3). The following tests were performed: EXTEM, INTEM, and HEPTEM. Heparin concentrations were measured at T1 and at the end of bypass (T2). RESULTS: At T1, EXTEM differed from baseline for coagulation time: +26.7 s (18.4 to 34.9, P < 0.0001), α: -3° (1.0 to 5.4, P = 0.006) and A10: -4.4 mm (2.3 to 6.5, P = 0.0004). INTEM at T0 was different from HEPTEM at T1 for coagulation time: + 47 s (34.3 to 59.6, P >0.0001), A10: -2.3 mm (0.5 to 4.0, P = 0.01) and α -2° (1.0 to 3.0; P = 0.0007). At T2, all parameters in EXTEM and HEPTEM related to fibrin-platelet interaction deteriorated significantly compared to T1. At T3, EXTEM and INTEM were comparable to EXTEM and HEPTEM at T2. CONCLUSION: HEPTEM and EXTEM measurements are valid in the presence of very high heparin concentrations and can be performed before protamine administration in patients undergoing cardiac surgery with CPB. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01455454.
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La présente étude est à la fois une évaluation du processus de la mise en oeuvre et des impacts de la police de proximité dans les cinq plus grandes zones urbaines de Suisse - Bâle, Berne, Genève, Lausanne et Zurich. La police de proximité (community policing) est à la fois une philosophie et une stratégie organisationnelle qui favorise un partenariat renouvelé entre la police et les communautés locales dans le but de résoudre les problèmes relatifs à la sécurité et à l'ordre public. L'évaluation de processus a analysé des données relatives aux réformes internes de la police qui ont été obtenues par l'intermédiaire d'entretiens semi-structurés avec des administrateurs clés des cinq départements de police, ainsi que dans des documents écrits de la police et d'autres sources publiques. L'évaluation des impacts, quant à elle, s'est basée sur des variables contextuelles telles que des statistiques policières et des données de recensement, ainsi que sur des indicateurs d'impacts construit à partir des données du Swiss Crime Survey (SCS) relatives au sentiment d'insécurité, à la perception du désordre public et à la satisfaction de la population à l'égard de la police. Le SCS est un sondage régulier qui a permis d'interroger des habitants des cinq grandes zones urbaines à plusieurs reprises depuis le milieu des années 1980. L'évaluation de processus a abouti à un « Calendrier des activités » visant à créer des données de panel permettant de mesurer les progrès réalisés dans la mise en oeuvre de la police de proximité à l'aide d'une grille d'évaluation à six dimensions à des intervalles de cinq ans entre 1990 et 2010. L'évaluation des impacts, effectuée ex post facto, a utilisé un concept de recherche non-expérimental (observational design) dans le but d'analyser les impacts de différents modèles de police de proximité dans des zones comparables à travers les cinq villes étudiées. Les quartiers urbains, délimités par zone de code postal, ont ainsi été regroupés par l'intermédiaire d'une typologie réalisée à l'aide d'algorithmes d'apprentissage automatique (machine learning). Des algorithmes supervisés et non supervisés ont été utilisés sur les données à haute dimensionnalité relatives à la criminalité, à la structure socio-économique et démographique et au cadre bâti dans le but de regrouper les quartiers urbains les plus similaires dans des clusters. D'abord, les cartes auto-organisatrices (self-organizing maps) ont été utilisées dans le but de réduire la variance intra-cluster des variables contextuelles et de maximiser simultanément la variance inter-cluster des réponses au sondage. Ensuite, l'algorithme des forêts d'arbres décisionnels (random forests) a permis à la fois d'évaluer la pertinence de la typologie de quartier élaborée et de sélectionner les variables contextuelles clés afin de construire un modèle parcimonieux faisant un minimum d'erreurs de classification. Enfin, pour l'analyse des impacts, la méthode des appariements des coefficients de propension (propensity score matching) a été utilisée pour équilibrer les échantillons prétest-posttest en termes d'âge, de sexe et de niveau d'éducation des répondants au sein de chaque type de quartier ainsi identifié dans chacune des villes, avant d'effectuer un test statistique de la différence observée dans les indicateurs d'impacts. De plus, tous les résultats statistiquement significatifs ont été soumis à une analyse de sensibilité (sensitivity analysis) afin d'évaluer leur robustesse face à un biais potentiel dû à des covariables non observées. L'étude relève qu'au cours des quinze dernières années, les cinq services de police ont entamé des réformes majeures de leur organisation ainsi que de leurs stratégies opérationnelles et qu'ils ont noué des partenariats stratégiques afin de mettre en oeuvre la police de proximité. La typologie de quartier développée a abouti à une réduction de la variance intra-cluster des variables contextuelles et permet d'expliquer une partie significative de la variance inter-cluster des indicateurs d'impacts avant la mise en oeuvre du traitement. Ceci semble suggérer que les méthodes de géocomputation aident à équilibrer les covariables observées et donc à réduire les menaces relatives à la validité interne d'un concept de recherche non-expérimental. Enfin, l'analyse des impacts a révélé que le sentiment d'insécurité a diminué de manière significative pendant la période 2000-2005 dans les quartiers se trouvant à l'intérieur et autour des centres-villes de Berne et de Zurich. Ces améliorations sont assez robustes face à des biais dus à des covariables inobservées et covarient dans le temps et l'espace avec la mise en oeuvre de la police de proximité. L'hypothèse alternative envisageant que les diminutions observées dans le sentiment d'insécurité soient, partiellement, un résultat des interventions policières de proximité semble donc être aussi plausible que l'hypothèse nulle considérant l'absence absolue d'effet. Ceci, même si le concept de recherche non-expérimental mis en oeuvre ne peut pas complètement exclure la sélection et la régression à la moyenne comme explications alternatives. The current research project is both a process and impact evaluation of community policing in Switzerland's five major urban areas - Basel, Bern, Geneva, Lausanne, and Zurich. Community policing is both a philosophy and an organizational strategy that promotes a renewed partnership between the police and the community to solve problems of crime and disorder. The process evaluation data on police internal reforms were obtained through semi-structured interviews with key administrators from the five police departments as well as from police internal documents and additional public sources. The impact evaluation uses official crime records and census statistics as contextual variables as well as Swiss Crime Survey (SCS) data on fear of crime, perceptions of disorder, and public attitudes towards the police as outcome measures. The SCS is a standing survey instrument that has polled residents of the five urban areas repeatedly since the mid-1980s. The process evaluation produced a "Calendar of Action" to create panel data to measure community policing implementation progress over six evaluative dimensions in intervals of five years between 1990 and 2010. The impact evaluation, carried out ex post facto, uses an observational design that analyzes the impact of the different community policing models between matched comparison areas across the five cities. Using ZIP code districts as proxies for urban neighborhoods, geospatial data mining algorithms serve to develop a neighborhood typology in order to match the comparison areas. To this end, both unsupervised and supervised algorithms are used to analyze high-dimensional data on crime, the socio-economic and demographic structure, and the built environment in order to classify urban neighborhoods into clusters of similar type. In a first step, self-organizing maps serve as tools to develop a clustering algorithm that reduces the within-cluster variance in the contextual variables and simultaneously maximizes the between-cluster variance in survey responses. The random forests algorithm then serves to assess the appropriateness of the resulting neighborhood typology and to select the key contextual variables in order to build a parsimonious model that makes a minimum of classification errors. Finally, for the impact analysis, propensity score matching methods are used to match the survey respondents of the pretest and posttest samples on age, gender, and their level of education for each neighborhood type identified within each city, before conducting a statistical test of the observed difference in the outcome measures. Moreover, all significant results were subjected to a sensitivity analysis to assess the robustness of these findings in the face of potential bias due to some unobserved covariates. The study finds that over the last fifteen years, all five police departments have undertaken major reforms of their internal organization and operating strategies and forged strategic partnerships in order to implement community policing. The resulting neighborhood typology reduced the within-cluster variance of the contextual variables and accounted for a significant share of the between-cluster variance in the outcome measures prior to treatment, suggesting that geocomputational methods help to balance the observed covariates and hence to reduce threats to the internal validity of an observational design. Finally, the impact analysis revealed that fear of crime dropped significantly over the 2000-2005 period in the neighborhoods in and around the urban centers of Bern and Zurich. These improvements are fairly robust in the face of bias due to some unobserved covariate and covary temporally and spatially with the implementation of community policing. The alternative hypothesis that the observed reductions in fear of crime were at least in part a result of community policing interventions thus appears at least as plausible as the null hypothesis of absolutely no effect, even if the observational design cannot completely rule out selection and regression to the mean as alternative explanations.
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BACKGROUND: Poor tolerance and adverse drug reactions are main reasons for discontinuation of antiretroviral therapy (ART). Identifying predictors of ART discontinuation is a priority in HIV care. METHODS: A genetic association study in an observational cohort to evaluate the association of pharmacogenetic markers with time to treatment discontinuation during the first year of ART. Analysis included 577 treatment-naive individuals initiating tenofovir (n = 500) or abacavir (n = 77), with efavirenz (n = 272), lopinavir/ritonavir (n = 184), or atazanavir/ritonavir (n = 121). Genotyping included 23 genetic markers in 15 genes associated with toxicity or pharmacokinetics of the study medication. Rates of ART discontinuation between groups with and without genetic risk markers were assessed by survival analysis using Cox regression models. RESULTS: During the first year of ART, 190 individuals (33%) stopped 1 or more drugs. For efavirenz and atazanavir, individuals with genetic risk markers experienced higher discontinuation rates than individuals without (71.15% vs 28.10%, and 62.5% vs 14.6%, respectively). The efavirenz discontinuation hazard ratio (HR) was 3.14 (95% confidence interval (CI): 1.35-7.33, P = .008). The atazanavir discontinuation HR was 9.13 (95% CI: 3.38-24.69, P < .0001). CONCLUSIONS: Several pharmacogenetic markers identify individuals at risk for early treatment discontinuation. These markers should be considered for validation in the clinical setting.
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Background: Hospitals in countries with public health systems have recently adopted organizational changes to improve efficiency and resource allocation, and reducing inappropriate hospitalizations has been established as an important goal. AIMS: Our goal was to describe the functioning of a Quick Diagnosis Unit in a Spanish public university hospital after evaluating 1,000 consecutive patients. We also aimed to ascertain the degree of satisfaction among Quick Diagnosis Unit patients and the costs of the model compared to conventional hospitalization practices. DESIGN: Observational, descriptive study. METHODS: Our sample comprised 1,000 patients evaluated between November 2008 and January 2010 in the Quick Diagnosis Unit of a tertiary university public hospital in Barcelona. Included patients were those who had potentially severe diseases and would normally require hospital admission for diagnosis but whose general condition allowed outpatient treatment. We analyzed several variables, including time to diagnosis, final diagnoses and hospitalizations avoided, and we also investigated the mean cost (as compared to conventional hospitalization) and the patients' satisfaction. RESULTS: In 88% of cases, the reasons for consultation were anemia, anorexia-cachexia syndrome, febrile syndrome, adenopathies, abdominal pain, chronic diarrhea and lung abnormalities. The most frequent diagnoses were cancer (18.8%; mainly colon cancer and lymphoma) and Iron-deficiency anemia (18%). The mean time to diagnosis was 9.2 days (range 1 to 19 days). An estimated 12.5 admissions/day in a one-year period (in the internal medicine department) were avoided. In a subgroup analysis, the mean cost per process (admission-discharge) for a conventional hospitalization was 3,416.13 Euros, while it was 735.65 Euros in the Quick Diagnosis Unit. Patients expressed a high degree of satisfaction with Quick Diagnosis Unit care. CONCLUSIONS: Quick Diagnosis Units represent a useful and cost-saving model for the diagnostic study of patients with potentially severe diseases. Future randomized study designs involving comparisons between controls and intervention groups would help elucidate the usefulness of Quick Diagnosis Units as an alternative to conventional hospitalization.
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Document Type: Meeting Abstract
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Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.