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An Unexpected Benefit of Adding the Patient Voice to Medical Education - Train Providers to be Better.
J Card Fail
January 2025
Amyloidosis Speakers Bureau/Mackenzie's Mission. Electronic address:
Background: Amyloidosis is a complex multi-systemic disease. Lack of knowledge about amyloidosis and subsequent mis- or under-diagnosis are major obstacles to treatment, which result in life-threatening organ damage, heart failure, morbidity, and mortality. At present, medical didactic education about amyloidosis leaves new physicians woefully unprepared to suspect and diagnose amyloidosis.
View Article and Find Full Text PDFDeconstructing the Monolith: An Educational Module for Understanding Disparities Within Asian American, Native Hawaiian, and Pacific Islander Populations.
MedEdPORTAL
January 2025
Professor, Department of Pediatrics, Columbia University Irving Medical Center.
Introduction: Asian American, Native Hawaiian, and Pacific Islander (AANHPI) people represent one of the largest and most rapidly growing groups in the United States and are often aggregated as a homogeneous, rather than diverse, population in medical research and education. Currently, few educational interventions focus on the disaggregation of AANHPI patient populations and the improvement of knowledge about health disparities that affect AANHPI patients.
Methods: We developed, implemented, and facilitated a workshop for medical students to address AANHPI health disparities, adaptable for in-person and online formats.
Multilabel segmentation and analysis of skeletal muscle and adipose tissue in routine abdominal CT scans.
Comput Biol Med
January 2025
Department of Simulation and Graphics, Faculty of Computer Science, University of Magdeburg, Universitätsplatz 2 39106, Magdeburg, Germany; Department of Computational Medicine, Ilmenau University of Technology, Germany.
Purpose: This paper presents a deep learning-based multi-label segmentation network that extracts a total of three separate adipose tissues and five different muscle tissues in CT slices of the third lumbar vertebra and additionally improves the segmentation of the intermuscular fat.
Method: Based on a self-created data set of 130 patients, an extended Unet structure was trained and evaluated with the help of Dice score, IoU and Pixel Accuracy. In addition, the interobserver variability for the decision between ground truth and post-processed segmentation was calculated to illustrate the relevance in everyday clinical practice.
Academic Detailing Interventions and Evidence-Based Prescribing: A Systematic Review.
JAMA Netw Open
January 2025
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Importance: Academic detailing (interactive educational outreach) is a widely used strategy to encourage evidence-based prescribing by clinicians.
Objective: To evaluate academic detailing programs targeted at improving prescribing behavior and describe program aspects associated with positive outcomes.
Evidence Review: A systematic search of MEDLINE from April 1, 2007, through December 31, 2022, was performed for randomized trials and nonrandomized studies of academic detailing interventions to improve prescribing.
Digitalised multidisciplinary conferences effectively identify and prevent imaging-related medical error in intensive care patients during the COVID-19 pandemic.
Sci Rep
January 2025
Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
This study aims to assess the effectiveness of digital multidisciplinary conferences (MDCs) in preventing imaging-related quality management (QM) events during the coronavirus-disease-19 (COVID-19) pandemic. COVID-19 challenged interdisciplinary exchange and QM measures for patient safety. Regular MDCs between radiologists and intensive care unit (ICU) physicians, introduced in our hospital in 2018, enable re-evaluation of imaging examinations and bilateral feedback.
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