53 resultados para Level of service


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Purpose We hypothesized that reduced arousability (Richmond Agitation Sedation Scale, RASS, scores −2 to −3) for any reason during delirium assessment increases the apparent prevalence of delirium in intensive care patients. To test this hypothesis, we assessed delirium using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and Intensive Care Delirium Screening Checklist (ICDSC) in intensive care patients during sedation stops, and related the findings to the level of sedation, as assessed with RASS score. Methods We assessed delirium in 80 patients with ICU stay longer than 48 h using CAM-ICU and ICDSC during daily sedation stops. Sedation was assessed using RASS. The effect of including patients with a RASS of −2 and −3 during sedation stop (“light to moderate sedation”, eye contact less than 10 s or not at all, respectively) on prevalence of delirium was analyzed. Results A total of 467 patient days were assessed. The proportion of CAM-ICU-positive evaluations decreased from 53 to 31 % (p < 0.001) if assessments from patients at RASS −2/−3 (22 % of all assessments) were excluded. Similarly, the number of positive ICDSC results decreased from 51 to 29 % (p < 0.001). Conclusions Sedation per se can result in positive items of both CAM-ICU and ICDSC, and therefore in a diagnosis of delirium. Consequently, apparent prevalence of delirium is dependent on how a depressed level of consciousness after sedation stop is interpreted (delirium vs persisting sedation). We suggest that any reports on delirium using these assessment tools should be stratified for a sedation score during the assessment.

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Previous syntheses on the effects of environmental conditions on the outcome of plant-plant interactions summarize results from pairwise studies. However, the upscaling to the community-level of such studies is problematic because of the existence of multiple species assemblages and species-specific responses to both the environmental conditions and the presence of neighbors. We conducted the first global synthesis of community-level studies from harsh environments, which included data from 71 alpine and 137 dryland communities to: (i) test how important are facilitative interactions as a driver of community structure, (ii) evaluate whether we can predict the frequency of positive plant-plant interactions across differing environmental conditions and habitats, and (iii) assess whether thresholds in the response of plant-plant interactions to environmental gradients exists between ``moderate'' and ``extreme'' environments. We also used those community-level studies performed across gradients of at least three points to evaluate how the average environmental conditions, the length of the gradient studied, and the number of points sampled across such gradient affect the form and strength of the facilitation-environmental conditions relationship. Over 25% of the species present were more spatially associated to nurse plants than expected by chance in both alpine and chyland areas, illustrating the high importance of positive plant-plant interactions for the maintenance of plant diversity in these environments. Facilitative interactions were more frequent, and more related to environmental conditions, in alpine than in dryland areas, perhaps because drylands are generally characterized by a larger variety of environmental stress factors and plant functional traits. The frequency of facilitative interactions in alpine communities peaked at 1000 mm of annual rainfall, and globally decreased with elevation. The frequency of positive interactions in dtyland communities decreased globally with water scarcity or temperature annual range. Positive facilitation-drought stress relationships are more likely in shorter regional gradients, but these relationships are obscured in regions with a greater species turnover or with complex environmental gradients. By showing the different climatic drivers and behaviors of plant-plant interactions in dryland and alpine areas, our results will improve predictions regarding the effect of facilitation on the assembly of plant communities and their response to changes in environmental conditions.

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The Mobile Cloud Networking project develops among others, several virtualized services and applications, in particular: (1) IP Multimedia Subsystem as a Service that gives the possibility to deploy a virtualized and on-demand instance of the IP Multimedia Subsystem platform, (2) Digital Signage Service as a Service that is based on a re-designed Digital Signage Service architecture, adopting the cloud computing principles, and (3) Information Centric Networking/Content Delivery Network as a Service that is used for distributing, caching and migrating content from other services. Possible designs for these virtualized services and applications have been identified and are being implemented. In particular, the architectures of the mentioned services were specified, adopting cloud computing principles, such as infrastructure sharing, elasticity, on-demand and pay-as-you-go. The benefits of Reactive Programming paradigm are presented in the context of Interactive Cloudified Digital Signage services in a Mobile Cloud Platform, as well as the benefit of interworking between different Mobile Cloud Networking Services as Digital Signage Service and Content Delivery Network Service for better performance of Video on Demand content deliver. Finally, the management of Service Level Agreements and the support of rating, charging and billing has also been considered and defined.

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OBJECTIVE The ACCESS treatment model offers assertive community treatment embedded in an integrated care program to patients with psychoses. Compared to standard care and within a controlled study, it proved to be more effective in terms of service disengagement and illness outcomes in patients with schizophrenia spectrum disorders over 12 months. ACCESS was implemented into clinical routine and its effectiveness assessed over 24 months in severe schizophrenia spectrum disorders and bipolar I disorder with psychotic features (DSM-IV) in a cohort study. METHOD All 115 patients treated in ACCESS (from May 2007 to October 2009) were included in the ACCESS II study. The primary outcome was rate of service disengagement. Secondary outcomes were change of psychopathology, severity of illness, psychosocial functioning, quality of life, satisfaction with care, medication nonadherence, length of hospital stay, and rates of involuntary hospitalization. RESULTS Only 4 patients (3.4%) disengaged with the service. Another 11 (9.6%) left because they moved outside the catchment area. Patients received a mean of 1.6 outpatient contacts per week. Involuntary admissions decreased from 34.8% in the 2 previous years to 7.8% during ACCESS (P < .001). Mixed models repeated-measures analyses revealed significant improvements among all patients in psychopathology (effect size d = 0.64, P < .001), illness severity (d = 0.84, P = .03), functioning level (d = 0.65, P < .001), quality of life (d = 0.50, P < .001), and client satisfaction (d = 0.11, P < .001). At 24 months, 78.3% were fully adherent to medication, compared to 25.2% at baseline (P = .002). CONCLUSIONS ACCESS was successfully implemented in clinical routine and maintained excellent rates of service engagement and other outcomes in patients with schizophrenia spectrum disorders or bipolar I disorder with psychotic features over 24 months. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT01888627.

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Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

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OBJECTIVES In Europe and elsewhere, health inequalities among HIV-positive individuals are of concern. We investigated late HIV diagnosis and late initiation of combination antiretroviral therapy (cART) by educational level, a proxy of socioeconomic position. DESIGN AND METHODS We used data from nine HIV cohorts within COHERE in Austria, France, Greece, Italy, Spain and Switzerland, collecting data on level of education in categories of the UNESCO/International Standard Classification of Education standard classification: non-completed basic, basic, secondary and tertiary education. We included individuals diagnosed with HIV between 1996 and 2011, aged at least 16 years, with known educational level and at least one CD4 cell count within 6 months of HIV diagnosis. We examined trends by education level in presentation with advanced HIV disease (AHD) (CD4 <200 cells/μl or AIDS within 6 months) using logistic regression, and distribution of CD4 cell count at cART initiation overall and among presenters without AHD using median regression. RESULTS Among 15 414 individuals, 52, 45,37, and 31% with uncompleted basic, basic, secondary and tertiary education, respectively, presented with AHD (P trend <0.001). Compared to patients with tertiary education, adjusted odds ratios of AHD were 1.72 (95% confidence interval 1.48-2.00) for uncompleted basic, 1.39 (1.24-1.56) for basic and 1.20 (1.08-1.34) for secondary education (P < 0.001). In unadjusted and adjusted analyses, median CD4 cell count at cART initiation was lower with poorer educational level. CONCLUSIONS Socioeconomic inequalities in delayed HIV diagnosis and initiation of cART are present in European countries with universal healthcare systems and individuals with lower educational level do not equally benefit from timely cART initiation.

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BACKGROUND A cost-effective strategy to increase the density of available markers within a population is to sequence a small proportion of the population and impute whole-genome sequence data for the remaining population. Increased densities of typed markers are advantageous for genome-wide association studies (GWAS) and genomic predictions. METHODS We obtained genotypes for 54 602 SNPs (single nucleotide polymorphisms) in 1077 Franches-Montagnes (FM) horses and Illumina paired-end whole-genome sequencing data for 30 FM horses and 14 Warmblood horses. After variant calling, the sequence-derived SNP genotypes (~13 million SNPs) were used for genotype imputation with the software programs Beagle, Impute2 and FImpute. RESULTS The mean imputation accuracy of FM horses using Impute2 was 92.0%. Imputation accuracy using Beagle and FImpute was 74.3% and 77.2%, respectively. In addition, for Impute2 we determined the imputation accuracy of all individual horses in the validation population, which ranged from 85.7% to 99.8%. The subsequent inclusion of Warmblood sequence data further increased the correlation between true and imputed genotypes for most horses, especially for horses with a high level of admixture. The final imputation accuracy of the horses ranged from 91.2% to 99.5%. CONCLUSIONS Using Impute2, the imputation accuracy was higher than 91% for all horses in the validation population, which indicates that direct imputation of 50k SNP-chip data to sequence level genotypes is feasible in the FM population. The individual imputation accuracy depended mainly on the applied software and the level of admixture.

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Social desirability and the fear of sanctions can deter survey respondents from responding truthfully to sensitive questions. Self-reports on norm breaking behavior such as shoplifting, non-voting, or tax evasion may therefore be subject to considerable misreporting. To mitigate such misreporting, various indirect techniques for asking sensitive questions, such as the randomized response technique (RRT), have been proposed in the literature. In our study, we evaluate the viability of several variants of the RRT, including the recently proposed crosswise-model RRT, by comparing respondents’ self-reports on cheating in dice games to actual cheating behavior, thereby distinguishing between false negatives (underreporting) and false positives (overreporting). The study has been implemented as an online survey on Amazon Mechanical Turk (N = 6,505). Our results indicate that the forced-response RRT and the unrelated-question RRT, as implemented in our survey, fail to reduce the level of misreporting compared to conventional direct questioning. For the crosswise-model RRT, we do observe a reduction of false negatives (that is, an increase in the proportion of cheaters who admit having cheated). At the same time, however, there is an increase in false positives (that is, an increase in non-cheaters who falsely admit having cheated). Overall, our findings suggest that none of the implemented sensitive questions techniques substantially outperforms direct questioning. Furthermore, our study demonstrates the importance of distinguishing false negatives and false positives when evaluating the validity of sensitive question techniques.