Publications by authors named "J K Mayfield"
Background: In-hospital mortality risk prediction is an important tool for benchmarking quality and patient prognostication. Given changes in patient characteristics and treatments over time, a contemporary risk model for patients with acute myocardial infarction (MI) is needed.
Methods: Data from 313 825 acute MI hospitalizations between January 2019 and December 2020 for adults aged ≥18 years at 784 sites in the National Cardiovascular Data Registry Chest Pain-MI Registry were used to develop a risk-standardized model to predict in-hospital mortality.
Small cohorts of certain disease states are common especially in medical imaging. Despite the growing culture of data sharing, information safety often precludes open sharing of these datasets for creating generalizable machine learning models. To overcome this barrier and maintain proper health information protection, foundational models are rapidly evolving to provide deep learning solutions that have been pretrained on the native feature spaces of the data.
View Article and Find Full Text PDFInfectious disease is the result of interactions between host and pathogen and can depend on genetic variations in both. We conduct a genome-to-genome study of paired human and Mycobacterium tuberculosis genomes from a cohort of 1556 tuberculosis patients in Lima, Peru. We identify an association between a human intronic variant (rs3130660, OR = 10.
View Article and Find Full Text PDFThe rapid growth in consumer-facing mobile and sensor technologies has created tremendous opportunities for patient-driven personalized health management. The diagnosis and management of cardiac arrhythmias are particularly well suited to benefit from these easily accessible consumer health technologies. In particular, smartphone-based and wrist-worn wearable electrocardiogram (ECG) and photoplethysmography (PPG) technology can facilitate relatively inexpensive, long-term rhythm monitoring.
View Article and Find Full Text PDFArticle Synopsis
- Mycobacterium tuberculosis (Mtb) makes a special molecule called 1-tuberculosinyladenosine (1-TbAd) that helps it survive in human immune cells by blocking their functions.
- Researchers found that certain genes are important for making 1-TbAd and used new software to study how Mtb produces lipids, leading to discoveries of many related molecules.
- They also discovered that the genes for making 1-TbAd are present in some bacteria outside the usual group known for tuberculosis, showing how these genes could have spread and suggesting that these molecules might be important for understanding human TB disease.