501 research outputs found
Stemming the Tide of Antibiotic Resistance (STAR): A protocol for a trial of a complex intervention addressing the 'why' and 'how' of appropriate antibiotic prescribing in general practice
BACKGROUND: After some years of a downward trend, antibiotic prescribing rates in the community have tended to level out in many countries. There is also wide variation in antibiotic prescribing between general practices, and between countries. There are still considerable further gains that could be made in reducing inappropriate antibiotic prescribing, but complex interventions are required. Studies to date have generally evaluated the effect of interventions on antibiotic prescribing in a single consultation and pragmatic evaluations that assess maintenance of new skills are rare. This paper describes the protocol for a pragmatic, randomized evaluation of a complex intervention aimed at reducing antibiotic prescribing by primary care clinicians. METHODS AND DESIGN: We developed a Social Learning Theory based, blended learning program (on-line learning, a practice based seminar, and context bound learning) called the STAR Educational Program. The 'why of change' is addressed by providing clinicians in general practice with information on antibiotic resistance in urine samples submitted by their practice and their antibiotic prescribing data, and facilitating a practice-based seminar on the implications of this data. The 'how of change' is addressed through context-bound communication skills training and information on antibiotic indication and choice. This intervention will be evaluated in a trial involving 60 general practices, with general practice as the unit of randomization (clinicians from each practice to either receive the STAR Educational Program or not) and analysis. The primary outcome will be the number of antibiotic items dispensed over one year. An economic and process evaluation will also be conducted. DISCUSSION: This trial will be the first to evaluate the effectiveness of this type of theory-based, blended learning intervention aimed at reducing antibiotic prescribing by primary care clinicians. Novel aspects include feedback of practice level data on antimicrobial resistance and prescribing, use of principles from motivational interviewing, training in enhanced communication skills that incorporates context-bound experience and reflection, and using antibiotic dispensing over one year (as opposed to antibiotic prescribing in a single consultation) as the main outcome
Unconventional semiclassical method for calculating the energetic values of diatomic molecules
Monotonicity Detection and Enforcement in Longitudinal Classification
Longitudinal datasets contain repeated measurements of the same variables at different points in time, which can be used by researchers to discover useful knowledge based on the changes of the data over time. Monotonic relations often occur in real-world data and need to be preserved in data mining models in order for the models to be acceptable by users. We propose a new methodology for detecting monotonic relations in longitudinal datasets and applying them in longitudinal classification model construction. Two different approaches were used to detect monotonic relations and include them into the classification task. The proposed approaches are evaluated using data from the English Lon- gitudinal Study of Ageing (ELSA) with 10 different age-related diseases used as class variables to be predicted. A gradient boosting algorithm (XGBoost) is used for constructing classification models in two scenarios: enforcing and not enforcing the constraints. The results show that enforcement of monotonicity constraints can consistently improve the predictive accuracy of the constructed models. The produced models are fully monotonic according to the monotonicity constraints, which can have a positive impact on model acceptance in real world applications
Topical use of 5% acyclovir cream for the treatment of occult and verrucous equine sarcoids: a double-blinded placebo-controlled study
Effects of vacuum packaging on the physical quality of minimally processed potatoes
In recent years, consumers have become more health conscious in their food choices but they also have less time to prepare healthy meals. As a result, minimally processed (MP) products have become an important sector of the food industry because of their âfresh-likeâ qualities, convenience and speed of meal preparation. In this study, the physical qualities of MP potatoes (âDĂ©sirĂ©eâ variety) stored for 7 days in vacuum packaging were evaluated. The shelf life of MP potatoes was effectively extended to nearly 1 week under refrigerated storage by using vacuum packaging systems. The main quality parameters were constant during storage
Repeated BCG treatment of mouse bladder selectively stimulates small GTPases and HLA antigens and inhibits single-spanning uroplakins
<p>Abstract</p> <p>Background</p> <p>Despite being a mainstay for treating superficial bladder carcinoma and a promising agent for interstitial cystitis, the precise mechanism of Bacillus Calmette-Guerin (BCG) remains poorly understood. It is particularly unclear whether BCG is capable of altering gene expression beyond its well-recognized pro-inflammatory effects and how this relates to its therapeutic efficacy. The objective of this study was to determine differentially expressed genes in the mouse bladder following repeated intravesical BCG therapy.</p> <p>Methods</p> <p>Mice were transurethrally instilled with BCG or pyrogen-free on days 1, 7, 14, and 21. Seven days after the last instillation, urothelia along with the submucosa was removed and amplified ds-DNA was prepared from control- and BCG-treated bladder mucosa and used to generate suppression subtractive hybridization (SSH). Plasmids from control- and BCG-specific differentially expressed clones and confirmed by Virtual Northern were then purified and the inserts were sequenced and annotated. Finally, chromatin immune precipitation combined with real-time polymerase chain reaction assay (ChIP/Q-PCR) was used to validate SSH-selected transcripts.</p> <p>Results</p> <p>Repeated intravesical BCG treatment induced an up regulation of genes associated with antigen presentation (B2M, HLA-A, HLA-DQA1, HLA-DQB2, HLA-E, HLA-G, IGHG, and IGH) and representatives of two IFNÎł-induced small GTPase families: the GBPs (GBP1, GBP2, and GBP5) and the p47GTPases (IIGTP1, IIGTP2, and TGTP). Genes expressed in saline-treated bladders but down-regulated by BCG included: the single-spanning uroplakins (UPK3a and UPK2), SPRR2G, GSTM5, and RSP 19.</p> <p>Conclusion</p> <p>Here we introduced a hypothesis-generator approach to determine key genes involved in the urothelium/sumbmucosa responses to BCG therapy. Urinary bladder responds to repeated BCG treatment by up-regulating not only antigen presentation-related genes, but also GBP and p47 small GTPases, both potentially serving to mount a resistance to the replication of the <it>Mycobacterium</it>. It will be of tremendous future interest to determine whether these immune response cascades play a role in the anti-cancer effects exerted by BCG.</p
Benefits of ICU admission in critically ill patients: Whether instrumental variable methods or propensity scores should be used
<p>Abstract</p> <p>Background</p> <p>The assessment of the causal effect of Intensive Care Unit (ICU) admission generally involves usual observational designs and thus requires controlling for confounding variables. Instrumental variable analysis is an econometric technique that allows causal inferences of the effectiveness of some treatments during situations to be made when a randomized trial has not been or cannot be conducted. This technique relies on the existence of one variable or "instrument" that is supposed to achieve similar observations with a different treatment for "arbitrary" reasons, thus inducing substantial variation in the treatment decision with no direct effect on the outcome. The objective of the study was to assess the benefit in terms of hospital mortality of ICU admission in a cohort of patients proposed for ICU admission (ELDICUS cohort).</p> <p>Methods</p> <p>Using this cohort of 8,201 patients triaged for ICU (including 6,752 (82.3%) patients admitted), the benefit of ICU admission was evaluated using 3 different approaches: instrumental variables, standard regression and propensity score matched analyses. We further evaluated the results obtained using different instrumental variable methods that have been proposed for dichotomous outcomes.</p> <p>Results</p> <p>The physician's main specialization was found to be the best instrument. All instrumental variable models adequately reduced baseline imbalances, but failed to show a significant effect of ICU admission on hospital mortality, with confidence intervals far higher than those obtained in standard or propensity-based analyses.</p> <p>Conclusions</p> <p>Instrumental variable methods offer an appealing alternative to handle the selection bias related to nonrandomized designs, especially when the presence of significant unmeasured confounding is suspected. Applied to the ELDICUS database, this analysis failed to show any significant beneficial effect of ICU admission on hospital mortality. This result could be due to the lack of statistical power of these methods.</p
Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV
The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of âs = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pTâ„20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60â€pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2â€{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration
Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector
The inclusive and dijet production cross-sections have been measured for jets
containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass
energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The
measurements use data corresponding to an integrated luminosity of 34 pb^-1.
The b-jets are identified using either a lifetime-based method, where secondary
decay vertices of b-hadrons in jets are reconstructed using information from
the tracking detectors, or a muon-based method where the presence of a muon is
used to identify semileptonic decays of b-hadrons inside jets. The inclusive
b-jet cross-section is measured as a function of transverse momentum in the
range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet
cross-section is measured as a function of the dijet invariant mass in the
range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets
and the angular variable chi in two dijet mass regions. The results are
compared with next-to-leading-order QCD predictions. Good agreement is observed
between the measured cross-sections and the predictions obtained using POWHEG +
Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet
cross-section. However, it does not reproduce the measured inclusive
cross-section well, particularly for central b-jets with large transverse
momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final
version published in European Physical Journal
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