Semaglutide use in people with obesity and type 2 diabetes from real-world utilization data: An analysis of the All of US Program.

Aim: To analyse data from the All of Us Research Program to evaluate the real-world application and long-term effectiveness of semaglutide in treating type 2 diabetes and obesity patients in a large population.

Materials And Methods: We identified patients prescribed semaglutide and analysed differences in route of administration and the time on semaglutide. For individuals diagnosed with obesity, we measured changes in body mass index (BMI) and weight from baseline, while measured changes in HbA1c for those patients with type 2 diabetes.

Alcohol consumption and its correlation with medical conditions: a UK Biobank study.

Background: Alcohol consumption has been associated with the occurrence of many health conditions. We analyzed UK Biobank data to explore associations of various conditions to type and amount of alcohol consumed. UK Biobank is a large biomedical database providing information from UK participants, including lifestyle questionnaires and diagnosis data.

PubMed4Hh: A Point-of-Care Mobile App for Evidence-Based Clinical Decision Support for Nurse Residents in Maryland.

Evidence-based clinical decision-making is considered a core competency for professional nurses. However, barriers such as lack of time in clinical practice; information overload; restricted access to resources; lack of evidence appraisal skills, awareness, and knowledge; and unreliable resources prevent them from adopting evidence-based practice. This study examined the usefulness of the PubMed4Hh (PubMed for Handhelds) mobile application for clinical decision-making at the point of care among Maryland newly licensed RNs.

Opioids for acute and chronic pain when receiving psychiatric medications.

Background: People with mental health disorders (MHD) like depression and anxiety are more likely to experience substance use disorders (SUDs) than those without MHD. This study assesses opioid prescription patterns for acute or chronic pain management in patients receiving medication for depression and/or anxiety.

Methods And Findings: Cross-sectional data trend analysis of 24.

A risk identification model for detection of patients at risk of antidepressant discontinuation.

Purpose: Between 30 and 68% of patients prematurely discontinue their antidepressant treatment, posing significant risks to patient safety and healthcare outcomes. Online healthcare forums have the potential to offer a rich and unique source of data, revealing dimensions of antidepressant discontinuation that may not be captured by conventional data sources.

Methods: We analyzed 891 patient narratives from the online healthcare forum, "askapatient.