Use of artificial intelligence to predict outcomes in mild aortic valve stenosis.

Aims: Aortic stenosis (AS) is a common and progressive disease, which, if left untreated, results in increased morbidity and mortality. Monitoring and follow-up care can be challenging due to significant variability in disease progression. This study aimed to develop machine learning models to predict the risks of disease progression and mortality in patients with mild AS.

Two-year outcomes using fast-acting sub-perception therapy for spinal cord stimulation: results of a real-world multicenter study in the United States.

Background: Fast-acting Sub-perception Therapy (FAST) is a novel spinal cord stimulation (SCS) modality delivering paresthesia-free pain relief. Our study evaluated the longer-term, real-world impact of FAST on chronic pain.

Research Design And Methods: As part of a multicenter, real-world, consecutive case series, we retrospectively identified patients who used FAST-SCS and analyzed their data.

Proteomic profiling reveals CEACAM6 function in driving gallbladder cancer aggressiveness through integrin receptor, PRKCD and AKT/ERK signaling.

Gallbladder cancer (GBC) presents as an aggressive malignancy with poor patient outcome. Like other epithelial cancers, the mechanisms of GBC cancer progression remain vague and efforts in finding targeted therapies fall below expectations. This study combined proteomic analysis of formalin-fixed paraffin-embedded (FFPE) GBC samples, functional and molecular characterization of potential oncogenes and identification of potential therapeutic strategies for GBC.

Development and Validation of the Youth Back Activity Questionnaire: A Measure of Function for Adolescents with Low Back Pain.

Design: Psychometric study.

Objective: To develop a reliable and valid patient-reported outcome measure to assess functional ability in adolescents with low back pain (LBP) using the Rasch model.

Summary Of Background Data: LBP is quite common in adolescence.