Suchergebnisse

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Funding from the National Institute for Health Research Health Technology Assessment Programme. The views and opinions expressed are those of the authors and do not necessarily reflect those of the Health Technology Assessment (HTA) Programme, the UK National Institute of Health Research (NIHR), National Health Service or Department of Health. The TOPKAT study is funded by the NIHR HTA Programme (number HTA 08/14/08), sponsored by the University of Oxford, and supported by Oxford Surgical Intervention Trials Unit (SITU; supported by Oxford NIHR Biomedical Research Centre) in the Royal College of Surgeons Surgical Trials Initiative. Study management was divided between the SITU (Oxford) and the Aberdeen trials centre, the Centre for Healthcare Randomised Trials. JAC held a Medical Research Council Methodology Fellowship (G1002292) for part of the study. The Health Services Research Unit is core funded by the chief scientist office of the Scottish Government Health and Social Care Directorates. We would like to thank the principal investigators and their teams at each of the TOPKAT sites. The data collected for the study, including individual participant data and a data dictionary defining each field in the set, will be made available to researchers on request to the study team and with appropriate reason when accompanied by a peer-reviewed protocol, with publication and on agreement of the Trial Steering Committee. The shared data will be deidentified participant data. Data will be shared with investigator support, after approval of a proposal, with a signed data access agreement. The study protocol, statistical analysis plan, and informed consent form are available online. ; Peer reviewed ; Publisher PDF

Funding Information: Supported in part by a grant from the French government through the Programme Investissement d'Avenir (I-SITE ULNE) managed by the Agence Nationale de la Recherche (coVAPid project). I.M.-L. has been supported by Science Foundation Ireland grant number 20/COV/0038. The funders of the study had no role in the study design, data collection, analysis, interpretation, writing of the report, or decision to submit for publication. Publisher Copyright: Copyright © 2021 by the American Thoracic Society ; Rationale: Early empirical antimicrobial treatment is frequently prescribed to critically ill patients with coronavirus disease (COVID-19) based on Surviving Sepsis Campaign guidelines. Objectives: We aimed to determine the prevalence of early bacterial identification in intubated patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia, as compared with influenza pneumonia, and to characterize its microbiology and impact on outcomes. Methods: A multicenter retrospective European cohort was performed in 36 ICUs. All adult patients receiving invasive mechanical ventilation > 48 hours were eligible if they had SARS-CoV-2 or influenza pneumonia at ICU admission. Bacterial identification was defined by a positive bacterial culture within 48 hours after intubation in endotracheal aspirates, BAL, blood cultures, or a positive pneumococcal or legionella urinary antigen test. Measurements and Main Results: A total of 1,050 patients were included (568 in SARS-CoV-2 and 482 in influenza groups). The prevalence of bacterial identification was significantly lower in patients with SARS-CoV-2 pneumonia compared with patients with influenza pneumonia (9.7 vs. 33.6%; unadjusted odds ratio, 0.21; 95% confidence interval [CI], 0.15-0.30; adjusted odds ratio, 0.23; 95% CI, 0.16-0.33; P,0.0001). Gram-positive cocci were responsible for 58% and 72% of coinfection in patients with SARS-CoV-2 and influenza pneumonia, respectively. Bacterial identification was associated with increased adjusted hazard ratio for 28-day mortality in patients with SARS-CoV-2 pneumonia (1.57; 95% CI, 1.01-2.44; P =0.043). However, no significant difference was found in the heterogeneity of outcomes related to bacterial identification between the two study groups, suggesting that the impact of coinfection on mortality was not different between patients with SARS-CoV-2 and influenza. Conclusions: Bacterial identification within 48 hours after intubation is significantly less frequent in patients with SARSCoV-2 pneumonia than patients with influenza pneumonia. ; publishersversion ; published

As higher education institutions increasingly teach online and offer greater levels of choice to students (over which modules to study, in which order to study, and how long to extend study before qualification) new challenges are introduced. One of these challenges is how to maintain an understanding of the student experience. This understanding is necessary to provide feedback to both students and faculty, and institutionally for the continued enhancement of quality. This paper is the first attempt at providing a narrative describing one approach to this challenge and the experience within a large distance learning University. It demonstrates a new approach to data is key to enabling the analysis of student study pathways. For many years, this University has offered great flexibility of study and as wide a study choice as it is possible to offer with conventional modules. By design, the Institution holds high levels of data for all student study. However, whilst it is possible to create bespoke queries, we found that this has been insufficient to readily enable analysis of the student experience. By moving from a traditional relational database structure to a multi-model database, many of the difficulties are resolved. In this paper, we report on this approach and describe next steps, including the potential to apply machine learning algorithms and test other data theories like that of Markov Chains.

Funding The project was funded by the National Institute for Health Research Health Technology Assessment Programme (Project Number 07/60/18). The Health Services Research Unit is funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. Acknowledgements The authors wish to thank the women who participated in the PROSPECT study. We also thank Margaret MacNeil for her secretarial support and data management, the programming team in CHaRT and the staff at the recruitment sites who facilitated the recruitment, treatment and follow up of study participants. ; Peer reviewed ; Publisher PDF