Tapering opioids is an effective strategy to reduce the risks associated with long-term opioid therapy. However, patients' experience with tapering can influence the success of this treatment. Understanding patients' experiences with opioid tapering will allow for patient-centered approaches to be adopted to tailor interventions to achieve safe and successful taper outcomes.
View Article and Find Full Text PDFAims: We measured the association between prescribed stimulant medications and overdose among individuals receiving opioid agonist therapy (OAT) for opioid use disorder.
Design: Retrospective cohort study using the British Columbia Provincial Overdose Cohort, a linked administrative database.
Setting: We used data from British Columbia, Canada, from January 2015 through February 2020.
Synthetic data have emerged as an attractive option for developing machine-learning methods in human neuroimaging, particularly in magnetic resonance imaging (MRI)-a modality where image contrast depends enormously on acquisition hardware and parameters. This retrospective paper reviews a family of recently proposed methods, based on synthetic data, for generalizable machine learning in brain MRI analysis. Central to this framework is the concept of domain randomization, which involves training neural networks on a vastly diverse array of synthetically generated images with random contrast properties.
View Article and Find Full Text PDFPurpose: Metabolic syndrome (MetS) is a cluster of risk factors that increase the risk of cardiometabolic diseases. The prevalence of MetS and individual components across pregnancy has not been reviewed in the literature. This research was conducted to identify the prevalence of MetS and its components among pregnant women.
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