Effects of Socioeconomic Deprivation on UTUC Staging, Mortality, and Recurrence.

Objectives: To determine whether the area deprivation index (ADI), a surrogate for socioeconomic status (SES) associated with patient residence, affected UTUC staging, recurrence rates, and mortality.

Methods: Patients undergoing radical nephroureterectomy or ureterectomy for UTUC at a single institution between February 2010 to August 2021 were classified by ADI. A 50 percentile cut-off of ADI classified patients as "advantaged" or "disadvantaged.

Artificial Intelligence-Prompted Explanations of Common Primary Care Diagnoses.

Background: Artificial intelligence (AI)-generated explanations about medical topics may be clearer and more accessible than traditional evidence-based sources, enhancing patient understanding and autonomy. We evaluated different AI explanations for patients about common diagnoses to aid in patient care.

Methods: We prompted ChatGPT 3.

Evaluating the Concordance of ChatGPT and Physician Recommendations for Bariatric Surgery.

Integrating artificial intelligence (AI) into healthcare prompts the need to measure its proficiency relative to human experts. This study evaluates the proficiency of ChatGPT, an OpenAI language model, in offering guidance concerning bariatric surgery compared to bariatric surgeons. Five clinical scenarios representative of diverse bariatric surgery situations were given to ASMBS-accredited bariatric surgeons and ChatGPT.

Examining dermatology residency applicant profiles for the 2023-2024 cycle: a cross-sectional analysis.

Dermatology remains highly competitive, with strong USMLE Step 1 scores traditionally crucial for securing residency positions. The 2023-2024 cycle introduced significant changes, including pass/fail USMLE Step 1 score reports and an expanded program signaling system. This study explores dermatology residency applicant profiles within this new context.