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Latest revisions to the International Health Regulations will fail to prevent future travel chaos.
BMJ Glob Health
January 2025
Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada.
The poor management of public health risks associated with travel by most countries proved among the most contentious issue areas during the COVID-19 pandemic. Evidence from previous outbreaks suggested travel restrictions were largely unnecessary and counterproductive to timely reporting. This led to initial WHO recommendations against the use of travel restrictions.
View Article and Find Full Text PDFMedical management pathways for Cushing's disease in pituitary tumors centers of excellence (PTCOEs).
Pituitary
January 2025
Division of Endocrinology, Santiago de Compostela University and Ciber OBN, Santiago, Spain.
Purpose: A recent update of consensus guidelines for the management of Cushing's disease (CD) included indications for medical therapy. However, there is limited evidence regarding their implementation in clinical practice. This study aimed to evaluate current medical therapy approaches by expert pituitary centers through an audit conducted to validate the criteria of Pituitary Tumors Centers of Excellence (PTCOEs) and provide an initial standard of medical care for CD.
View Article and Find Full Text PDFSmoke-free hospitality environments and cognitive health: A population-based study in the United States.
Prev Med Rep
February 2025
Departments of Medicine, Health, and Society & Sociology, Vanderbilt University, 2201 West End Ave, Nashville, TN 37235, USA.
Introduction: Cigarette smoking is among the largest risk factors for cognitive decline in later life. This study examines the associations between hospitality smoke-free coverage in the US and the prevalence of self-rated cognitive function decline and disparities therein.
Methods: I use the repeated cross-sectional Behavioral Risk Factor Surveillance data collected between 2017 and 2022 from a sample of Americans 45 years and older and estimate logistic regression models predicting self-rated cognitive function decline by calculated smoke-free hospitality coverage in restaurants and bars.
Purpose: This brief report aims to summarize and discuss the methodologies of eXplainable Artificial Intelligence (XAI) and their potential applications in surgery.
Methods: We briefly introduce explainability methods, including global and individual explanatory features, methods for imaging data and time series, as well as similarity classification, and unraveled rules and laws.
Results: Given the increasing interest in artificial intelligence within the surgical field, we emphasize the critical importance of transparency and interpretability in the outputs of applied models.
Penalized landmark supermodels (penLM) for dynamic prediction for time-to-event outcomes in high-dimensional data.
BMC Med Res Methodol
January 2025
Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, 3180 Porter Drive, Office 118, Stanford, CA, 94304, USA.
Background: To effectively monitor long-term outcomes among cancer patients, it is critical to accurately assess patients' dynamic prognosis, which often involves utilizing multiple data sources (e.g., tumor registries, treatment histories, and patient-reported outcomes).
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