Nonopioid vs opioid analgesics after impacted third-molar extractions: The Opioid Analgesic Reduction Study randomized clinical trial.

Background: Opioids are still being prescribed to manage acute postsurgical pain. Unnecessary opioid prescriptions can lead to addiction and death, as unused tablets are easily diverted.

Methods: To determine whether combination nonopioid analgesics are at least as good as opioid analgesics, a multisite, double-blind, randomized, stratified, noninferiority comparative effectiveness trial was conducted, which examined patient-centered outcomes after impacted mandibular third-molar extraction surgery.

Dynamic survival prediction of end-stage kidney disease using random survival forests for competing risk analysis.

Background And Hypothesis: A static predictive model relying solely on baseline clinicopathological data cannot capture the heterogeneity in predictor trajectories observed in the progression of chronic kidney disease (CKD). To address this, we developed and validated a dynamic survival prediction model using longitudinal clinicopathological data to predict end-stage kidney disease (ESKD), with death as a competing risk.

Methods: We trained a sequence of random survival forests using a landmarking approach and optimized the model with a pre-specified prediction horizon of 5 years.

Complete genomes of common bacterial hosts of RNA bacteriophage Φ6.

Bacterial plant pathogens pv. , pv. , pv.

View-symmetric representations of faces in human and artificial neural networks.

View symmetry has been suggested to be an important intermediate representation between view-specific and view-invariant representations of faces in the human brain. Here, we compared view-symmetry in humans and a deep convolutional neural network (DCNN) trained to recognise faces. First, we compared the output of the DCNN to head rotations in yaw (left-right), pitch (up-down) and roll (in-plane rotation).