Management of early pregnancy loss with mifepristone and misoprostol: clinical predictors of treatment success from a randomized trial.

BackgroundEarly pregnancy loss is a common event in the first trimester, occurring in 15%-20% of confirmed pregnancies. A common evidence-based medical regimen for early pregnancy loss uses misoprostol, a prostaglandin E1 analog, with a dosage of 800 μg, self-administered vaginally. The clinical utility of this regimen is limited by suboptimal effectiveness in patients with a closed cervical os, with 29% of patients experiencing early pregnancy loss requiring a second dose after 3 days and 16% of patients eventually requiring a uterine aspiration procedure.ObjectiveThis study aimed to evaluate clinical predictors associated with treatment success in patients receiving medical management with mifepristone-misoprostol or misoprostol alone for early pregnancy loss.Study designWe performed a planned secondary analysis of a randomized trial comparing mifepristone-misoprostol with misoprostol alone for management of early pregnancy loss. The published prediction model for treatment success of single-dose misoprostol administered vaginally included the following variables: active bleeding, type of early pregnancy loss (anembryonic pregnancy or embryonic and/or fetal demise), parity, gestational age, and treatment site; previous significant predictors were vaginal bleeding within the past 24 hours and parity of 0 or 1 vs >1. To determine if these characteristics predicted differential proportions of patients with treatment success or failure, we performed bivariate analyses; given the small proportion of treatment failures in the combined treatment arm, both arms were combined for analysis. Thereafter, we performed a logistic regression analysis to assess the effect of these predictors collectively in each of the 2 treatment groups separately as well as in the full cohort as a proxy for the combined treatment arm. Finally, by using receiver operating characteristic curves, we tested the ability of these predictors in association with misoprostol treatment success to discriminate between treatment success and treatment failure. To quantify the ability of the score to discriminate between treatment success and treatment failure in each treatment arm as well as in the entire cohort, we calculated the area under the curve. Using multivariable logistic regression, we then assessed our study population for other predictors of treatment success in both treatment groups, with and without mifepristone pretreatment.ResultsOverall, 297 evaluable participants were included in the primary study, with 148 in the mifepristone-misoprostol combined treatment group and 149 in the misoprostol-alone treatment group. Among patients who had vaginal bleeding at the time of treatment, 15 of 17 (88%) in the mifepristone-misoprostol combined treatment group and 12 of 17 (71%) in the misoprostol-alone treatment group experienced expulsion of pregnancy tissue. Among patients with a parity of 0 or 1, 94 of 108 (87%) in the mifepristone-misoprostol treatment group and 66 of 95 (69%) in the misoprostol-alone treatment group experienced expulsion of pregnancy tissue. These clinical characteristics did not predict treatment success in the combined cohort alone (area under the curve=0.56; 95% confidence interval, 0.48-0.64). No other baseline clinical factors predicted treatment success in the misoprostol-alone treatment arm or mifepristone pretreatment arm. In the full cohort, the significant predictors of treatment success were pretreatment with mifepristone (adjusted odds ratio=2.51; 95% confidence interval, 1.43-4.43) and smoking (adjusted odds ratio=2.15; 95% confidence interval, 1.03-4.49).ConclusionNo baseline clinical factors predicted treatment success in women receiving medical management with misoprostol for early pregnancy loss. Adding mifepristone to the medical management regimen of early pregnancy loss improved treatment success; thus, mifepristone treatment should be considered for management of early pregnancy loss regardless of baseline clinical factors

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector

A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13  TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139  fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV

Search for direct stau production in events with two hadronic tau-leptons in root s=13 TeV pp collisions with the ATLAS detector

A search for the direct production of the supersymmetric partners ofτ-leptons (staus) in final stateswith two hadronically decayingτ-leptons is presented. The analysis uses a dataset of pp collisions corresponding to an integrated luminosity of139fb−1, recorded with the ATLAS detector at the LargeHadron Collider at a center-of-mass energy of 13 TeV. No significant deviation from the expected StandardModel background is observed. Limits are derived in scenarios of direct production of stau pairs with eachstau decaying into the stable lightest neutralino and oneτ-lepton in simplified models where the two staumass eigenstates are degenerate. Stau masses from 120 GeV to 390 GeV are excluded at 95% confidencelevel for a massless lightest neutralino

Evidence for the Higgs-boson Yukawa coupling to tau leptons with the ATLAS detector

Results of a search for H → τ τ decays are presented, based on the full set of proton-proton collision data recorded by the ATLAS experiment at the LHC during 2011 and 2012. The data correspond to integrated luminosities of 4.5 fb−1 and 20.3 fb−1 at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV respectively. All combinations of leptonic (τ → `νν¯ with ` = e, µ) and hadronic (τ → hadrons ν) tau decays are considered. An excess of events over the expected background from other Standard Model processes is found with an observed (expected) significance of 4.5 (3.4) standard deviations. This excess provides evidence for the direct coupling of the recently discovered Higgs boson to fermions. The measured signal strength, normalised to the Standard Model expectation, of µ = 1.43 +0.43 −0.37 is consistent with the predicted Yukawa coupling strength in the Standard Model

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Economic predictors of differences in interview faking between countries : economic inequality matters, not the state of economy

Many companies recruit employees from different parts of the globe, and faking behavior by potential employees is a ubiquitous phenomenon. It seems that applicants from some countries are more prone to faking compared to others, but the reasons for these differences are largely unexplored. This study relates country-level economic variables to faking behavior in hiring processes. In a cross-national study across 20 countries, participants (N = 3839) reported their faking behavior in their last job interview. This study used the random response technique (RRT) to ensure participants anonymity and to foster honest answers regarding faking behavior. Results indicate that general economic indicators (gross domestic product per capita [GDP] and unemployment rate) show negligible correlations with faking across the countries, whereas economic inequality is positively related to the extent of applicant faking to a substantial extent. These findings imply that people are sensitive to inequality within countries and that inequality relates to faking, because inequality might actuate other psychological processes (e.g., envy) which in turn increase the probability for unethical behavior in many forms

Mixture of latent trait analyzers for model-based clustering of categorical data

Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspondence between the estimated latent classes and groups in the population of interest. The mixture of latent trait analyzers model extends latent class analysis by assuming a model for the categorical response variables that depends on both a categorical latent class and a continuous latent trait variable; the discrete latent class accommodates group structure and the continuous latent trait accommodates dependence within these groups. Fitting the mixture of latent trait analyzers model is potentially difficult because the likelihood function involves an integral that cannot be evaluated analytically. We develop a variational approach for fitting the mixture of latent trait models and this provides an efficient model fitting strategy. The mixture of latent trait analyzers model is demonstrated on the analysis of data from the National Long Term Care Survey (NLTCS) and voting in the U.S. Congress. The model is shown to yield intuitive clustering results and it gives a much better fit than either latent class analysis or latent trait analysis alone