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In health care, work-related musculoskeletal disorders are largely attributed to patient-handling tasks. Reliable assessments of patient mobility are imperative to mitigate the musculoskeletal burden on healthcare providers. This study explores the reliability of MK5 Mobility Classes, a patient mobility classification system.

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Choline Metabolites, Genetic Susceptibility, and Incident Heart Failure.

JACC Adv

January 2025

Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Background: Little is known about the associations between choline metabolites (total choline, phosphatidylcholine, and glycine) and the incidence of heart failure (HF).

Objectives: The purpose of this study was to assess the associations of choline metabolites with incident HF and examine the effect modification by genetic susceptibility.

Methods: This prospective cohort study followed 245,072 participants from the UK Biobank from baseline (2006-2010) until March 30, 2023.

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Background: Hemophagocytic lymphohistiocytosis (HLH), is characterized by systemic uncontrolled inflammation resulting from immune dysregulation secondary to various triggers, including genetics, infections, autoimmune diseases, and malignancies. Macrophage activation syndrome (MAS) is an immune dysregulation phenomenon, in which an underlying rheumatological disease is present. We report a rare, interesting case of a middle-aged female, with a systemic lupus erythematosus (SLE) flare complicated by macrophage activation syndrome (MAS), in which tuberculous meningitis (TBM) was the identified trigger.

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Objectives: To determine the impact of scenario-based lecture and personalized video feedback on anesthesia residents' communication skills during preoperative visits.

Methods: A total of 24 anesthesia residents were randomly divided into a video group and a control group. Residents in both groups took part in a simulated interview and received a scenario-based lecture on how to communicate with patients during preoperative visits.

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G-SET-DCL: a guided sequential episodic training with dual contrastive learning approach for colon segmentation.

Int J Comput Assist Radiol Surg

January 2025

Computer Vision and Image Processing Lab., UofL, Louisville, KY, 40292, USA.

Purpose: This article introduces a novel deep learning approach to substantially improve the accuracy of colon segmentation even with limited data annotation, which enhances the overall effectiveness of the CT colonography pipeline in clinical settings.

Methods: The proposed approach integrates 3D contextual information via guided sequential episodic training in which a query CT slice is segmented by exploiting its previous labeled CT slice (i.e.

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