Automated EEG-Based Brainwave Analysis for the Detection of Postoperative Delirium Does Not Result in a Shorter Length of Stay in Geriatric Hip Fracture Patients: A Multicentre Randomized Controlled Trial.

: Delirium in postoperative geriatric hip fracture patients is a serious and often preventable condition. If detected in time, it can be treated, but a delay in the diagnosis and initiation of treatment impairs outcomes. A novel approach to detect delirium is to use point-of-care electro-encephalogram (EEG) recording with automated analysis.

Search for Soft Unclustered Energy Patterns in Proton-Proton Collisions at 13 TeV.

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics.

Search for the Z Boson Decay to ττμμ in Proton-Proton Collisions at sqrt[s]=13 TeV.

The first search for the Z boson decay to ττμμ at the CERN LHC is presented, based on data collected by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 138  fb^{-1}. The data are compatible with the predicted background. For the first time, an upper limit at the 95% confidence level of 6.

A prediction model for electroconvulsive therapy effectiveness in patients with major depressive disorder from the Dutch ECT Consortium (DEC).

Reliable predictors for electroconvulsive therapy (ECT) effectiveness would allow a more precise and personalized approach for the treatment of major depressive disorder (MDD). Prediction models were created using a priori selected clinical variables based on previous meta-analyses. Multivariable linear regression analysis was used, applying backwards selection to determine predictor variables while allowing non-linear relations, to develop a prediction model for depression outcome post-ECT (and logistic regression for remission and response as secondary outcome measures).