Audio-Based Care for Managing Chronic Conditions in Adults: A Systematic Review.

Background: There is a lack of consensus on the effectiveness of audio-based care to manage chronic conditions. This knowledge gap has implications for health policy decisions and for health equity, as underserved populations are more likely to access care by telephone.

Objectives: We compared the effectiveness of audio-based care to usual care for managing chronic conditions (except diabetes).

Audio-Based Care for Managing Diabetes in Adults: A Systematic Review.

Objectives: We compared the effectiveness of audio-based care, as a replacement or a supplement to usual care, for managing diabetes.

Background: Diabetes is a chronic condition afflicting many in the United States. The impact of audio-based care on the health of individuals with diabetes is unclear, particularly for those at risk for disparities-many of whom may only be able to access telehealth services through telephone.

Determinants of Surgical Outcomes in Tricuspid Valve Endocarditis.

Background: Current treatment guidelines for infective endocarditis focus on left-sided infective endocarditis. Because right-sided infective endocarditis has different presentations and outcomes, it is crucial to further delineate surgical outcomes for isolated tricuspid valve endocarditis (TVE).

Methods: This retrospective study reviewed 374 surgically treated patients with isolated TVE from January 2012 through April 2022 who underwent isolated tricuspid valve surgical procedures.

Evaluation of COVID-19 Diagnosis Codes for Identification of SARS-CoV-2 Infections in a Nursing Home Cohort, 2022-2023.

Objectives: This study aimed to evaluate the utility of electronic health record (EHR) diagnosis codes for monitoring SARS-CoV-2 infections among nursing home residents.

Design: A retrospective cohort study design was used to analyze data collected from nursing homes operating under the tradename Signature Healthcare between January 2022 and June 2023.

Setting And Participants: Data from 31,136 nursing home residents across 76 facilities in Kentucky, Tennessee, Indiana, Ohio, North Carolina, Georgia, Alabama, and Virginia were included.

Toward Non-Invasive Diagnosis of Bankart Lesions with Deep Learning.

Bankart lesions, or anterior-inferior glenoid labral tears, are diagnostically challenging on standard MRIs due to their subtle imaging features-often necessitating invasive MRI arthrograms (MRAs). This study develops deep learning (DL) models to detect Bankart lesions on both standard MRIs and MRAs, aiming to improve diagnostic accuracy and reduce reliance on MRAs. We curated a dataset of 586 shoulder MRIs (335 standard, 251 MRAs) from 558 patients who underwent arthroscopy.