Quality indicators for patients with traumatic brain injury in European intensive care units

Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe

Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Measurement of the cross section of high transverse momentum Z→bb̄ production in proton–proton collisions at √s = 8 TeV with the ATLAS detector

This Letter reports the observation of a high transverse momentum Z→bb̄ signal in proton–proton collisions at √s=8 TeV and the measurement of its production cross section. The data analysed were collected in 2012 with the ATLAS detector at the LHC and correspond to an integrated luminosity of 19.5 fb−¹. The Z→bb̄ decay is reconstructed from a pair of b -tagged jets, clustered with the anti-ktkt jet algorithm with R=0.4R=0.4, that have low angular separation and form a dijet with pT>200 GeVpT>200 GeV. The signal yield is extracted from a fit to the dijet invariant mass distribution, with the dominant, multi-jet background mass shape estimated by employing a fully data-driven technique that reduces the dependence of the analysis on simulation. The fiducial cross section is determined to be σZ→bb¯fid=2.02±0.20 (stat.) ±0.25 (syst.)±0.06 (lumi.) pb=2.02±0.33 pb, in good agreement with next-to-leading-order theoretical predictions

Measurement of the branching ratio Γ(Λb⁰ → ψ(2S)Λ0)/Γ(Λb⁰ → J/ψΛ0) with the ATLAS detector

An observation of the $\Lambda_b^0 \rightarrow \psi(2S) \Lambda^0$ decay and a comparison of its branching fraction with that of the $\Lambda_b^0 \rightarrow J/\psi \Lambda^0$ decay has been made with the ATLAS detector in proton--proton collisions at $\sqrt{s}=8\,$TeV at the LHC using an integrated luminosity of $20.6\,$fb$^{-1}$. The $J/\psi$ and $\psi(2S)$ mesons are reconstructed in their decays to a muon pair, while the $\Lambda^0\rightarrow p\pi^-$ decay is exploited for the $\Lambda^0$ baryon reconstruction. The $\Lambda_b^0$ baryons are reconstructed with transverse momentum $p_{\rm T}>10\,$GeV and pseudorapidity $|\eta|<2.1$. The measured branching ratio of the $\Lambda_b^0 \rightarrow \psi(2S) \Lambda^0$ and $\Lambda_b^0 \rightarrow J/\psi \Lambda^0$ decays is $\Gamma(\Lambda_b^0 \rightarrow \psi(2S)\Lambda^0)/\Gamma(\Lambda_b^0 \rightarrow J/\psi\Lambda^0) = 0.501\pm 0.033 ({\rm stat})\pm 0.019({\rm syst})$, lower than the expectation from the covariant quark model.Comment: 12 pages plus author list (28 pages total), 5 figures, 1 table, published on Physics Letters B 751 (2015) 63-80. All figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/BPHY-2013-08

Measurement of the View the tt production cross-section using eμ events with b-tagged jets in pp collisions at √s = 13 TeV with the ATLAS detector

This paper describes a measurement of the inclusive top quark pair production cross-section (σtt¯) with a data sample of 3.2 fb−1 of proton–proton collisions at a centre-of-mass energy of √s = 13 TeV, collected in 2015 by the ATLAS detector at the LHC. This measurement uses events with an opposite-charge electron–muon pair in the final state. Jets containing b-quarks are tagged using an algorithm based on track impact parameters and reconstructed secondary vertices. The numbers of events with exactly one and exactly two b-tagged jets are counted and used to determine simultaneously σtt¯ and the efficiency to reconstruct and b-tag a jet from a top quark decay, thereby minimising the associated systematic uncertainties. The cross-section is measured to be: σtt¯ = 818 ± 8 (stat) ± 27 (syst) ± 19 (lumi) ± 12 (beam) pb, where the four uncertainties arise from data statistics, experimental and theoretical systematic effects, the integrated luminosity and the LHC beam energy, giving a total relative uncertainty of 4.4%. The result is consistent with theoretical QCD calculations at next-to-next-to-leading order. A fiducial measurement corresponding to the experimental acceptance of the leptons is also presented

Search for TeV-scale gravity signatures in high-mass final states with leptons and jets with the ATLAS detector at sqrt [ s ] = 13TeV

A search for physics beyond the Standard Model, in final states with at least one high transverse momentum charged lepton (electron or muon) and two additional high transverse momentum leptons or jets, is performed using 3.2 fb−1 of proton–proton collision data recorded by the ATLAS detector at the Large Hadron Collider in 2015 at √s = 13 TeV. The upper end of the distribution of the scalar sum of the transverse momenta of leptons and jets is sensitive to the production of high-mass objects. No excess of events beyond Standard Model predictions is observed. Exclusion limits are set for models of microscopic black holes with two to six extra dimensions