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Association of long-term weight management pharmacotherapy with multiple health outcomes: an umbrella review and evidence map.
Int J Obes (Lond)
January 2025
Center for Optometry, Gansu Provincial Hospital, Lanzhou, China.
Background: Multiple meta-analyses (MAs) have demonstrated that six pharmacotherapies, including orlistat, liraglutide, phentermine/topiramate, naltrexone/bupropion, semaglutide, and tirzepatide, improve weight loss and weight maintenance. However, few studies have synthesized and evaluated the quality of this evidence.
Objective: To identify the relevant MAs of randomized clinical trials (RCTs) that explored the association between the six pharmacotherapies and obesity-related health outcomes and adverse events (AEs).
Content validation of drug problem-oriented clinical record.
Res Social Adm Pharm
January 2025
Laboratory of Teaching and Research in Social Pharmacy (LEPFS), Department of Pharmacy, Federal University of Sergipe, Cidade Universitária "Prof. José Aloísio Campos", Jardim Rosa Elze, São Cristóvão, SE, CEP: 49100- 000, Brazil. Electronic address:
Background: Worldwide, hospitals are responsible for restoring health. However, poorly executed processes in these institutions can lead to risks and harm to patients, especially in identifying drug related problems. This fact justifies the proposal of tools to support the diagnosis, management and resolution of these problems.
View Article and Find Full Text PDFClassifying Unstructured Text in Electronic Health Records for Mental Health Prediction Models: Large Language Model Evaluation Study.
JMIR Med Inform
January 2025
School of Social Policy & Practice, University of Pennsylvania, Philadelphia, PA, United States.
Background: Prediction models have demonstrated a range of applications across medicine, including using electronic health record (EHR) data to identify hospital readmission and mortality risk. Large language models (LLMs) can transform unstructured EHR text into structured features, which can then be integrated into statistical prediction models, ensuring that the results are both clinically meaningful and interpretable.
Objective: This study aims to compare the classification decisions made by clinical experts with those generated by a state-of-the-art LLM, using terms extracted from a large EHR data set of individuals with mental health disorders seen in emergency departments (EDs).
The experiences of women diagnosed with precancerous cervical lesions, and their spouses, according to the Roy Adaptation Model: Model-based qualitative research.
Appl Nurs Res
February 2025
Department of Obstetrics and Gynecology Nursing, Ege University, 35100 Izmir, Turkey.
Purpose: The aim of this study was to examine the experiences of women diagnosed with precancerous cervical lesions, and their spouses, according to the Roy Adaptation Model.
Method: A phenomenological design was used in this study, with its conceptual framework being formed by the Roy Adaptation Model. The sample was composed of women with precancerous cervical lesions (n:23) and their spouses (n:5).
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