Whole Blood Metal Levels in the Setting of an Oncologic Endoprosthesis: Is There Cause for Concern?

Background: Massive modular endoprostheses have become a primary means of reconstruction after oncologic resection of a lower extremity tumor. These implants are commonly made with cobalt-chromium alloys that can undergo wear and corrosion, releasing cobalt and chromium ions into the surrounding tissue and blood. However, there are few studies about the blood metal levels in these patients.

The use of deep learning in medical imaging to improve spine care: A scoping review of current literature and clinical applications.

Background: Artificial intelligence is a revolutionary technology that promises to assist clinicians in improving patient care. In radiology, deep learning (DL) is widely used in clinical decision aids due to its ability to analyze complex patterns and images. It allows for rapid, enhanced data, and imaging analysis, from diagnosis to outcome prediction.

Can the American Joint Replacement Registry Utilize Administrative Claims Data to Accurately Classify Revision Total Hip Arthroplasty (THA) Surgical Diagnoses?

Background: The American Joint Replacement Registry (AJRR) is a valuable tool for studying revision total hip arthroplasty (rTHA). Currently, International Classification of Diseases-10 (ICD-10) codes are utilized by the AJRR for classifying surgical diagnoses. However, the validity of this methodology is unknown.

Longitudinal factors associated with increased alcohol consumption in adults during the COVID-19 pandemic.

Alcohol is the most abused substance among adults in the United States. The COVID-19 pandemic impacted patterns of alcohol use, but data are conflicting, and previous studies are largely limited to cross-sectional analyses. This study aimed to longitudinally assess sociodemographic and psychological correlates of changes in three patterns of alcohol use (number of alcoholic drinks, drinking regularity, and binge drinking) during COVID-19.

Prediction Models for Knee Osteoarthritis: Review of Current Models and Future Directions.

Background: Knee osteoarthritis (OA) is a prevalent joint disease. Clinical prediction models consider a wide range of risk factors for knee OA. This review aimed to evaluate published prediction models for knee OA and identify opportunities for future model development.