JAMA Health Forum
September 2024
Importance: During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (PLTs), to optimize the distribution of scarce therapeutics.
Objective: To evaluate whether a machine learning PLT-based method of scarce resource allocation optimizes the treatment benefit of COVID-19 neutralizing monoclonal antibodies (mAbs) during periods of resource constraint.
Background: A trial performed among unvaccinated, high-risk outpatients with COVID-19 during the delta period showed remdesivir reduced hospitalization. We used our real-world data platform to determine the effectiveness of remdesivir on reducing 28-day hospitalization among outpatients with mild-moderate COVID-19 during an Omicron period including BQ.1/BQ.
View Article and Find Full Text PDFBackground: The high prevalence of desynchronized biological rhythms is becoming a primary public health concern. We assess complex and diverse inter-modulations among multi-frequency rhythms present in blood pressure (BP) and heart rate (HR).
Subjects: and Methods: We performed 7-day/24-hour Ambulatory BP Monitoring in 220 (133 women) residents (23 to 74 years) of a rural Japanese town in Kochi Prefecture under everyday life conditions.