Publications by authors named "C A Bremer"
Objective: To describe the outcome of dietary management of canine noninfectious acute colitis with or without concurrent oral administration of metronidazole using a randomized controlled clinical trial.
Animals: 59 client-owned dogs with noninfectious acute colitis.
Procedures: Dogs with acute noninfectious colitis were enrolled in a 30-day diet trial after exclusion of parasitic infectious etiologies (fecal centrifugation floatation, Giardia/Cryptosporidium antigen testing) and systemic disease (CBC, biochemistry, urinalysis).
Article Synopsis
- The study aimed to standardize and fill in missing units from electronic health records (EHRs) by developing a systematic method for converting and validating these measurements, focusing on COVID-19 research.
- The researchers worked with over 3.1 billion patient records and 19,000 unique measurements, successfully harmonizing 88.1% of values and imputing units for 78.2% of records that initially lacked them.
- This new approach enhances the ability to analyze diverse EHR data, making valuable information accessible for public health insights and research efforts.
Importance: Understanding of SARS-CoV-2 infection in US children has been limited by the lack of large, multicenter studies with granular data.
Objective: To examine the characteristics, changes over time, outcomes, and severity risk factors of children with SARS-CoV-2 within the National COVID Cohort Collaborative (N3C).
Design, Setting, And Participants: A prospective cohort study of encounters with end dates before September 24, 2021, was conducted at 56 N3C facilities throughout the US.
Importance: SARS-CoV-2.
Objective: To determine the characteristics, changes over time, outcomes, and severity risk factors of SARS-CoV-2 affected children within the National COVID Cohort Collaborative (N3C).
Design: Prospective cohort study of patient encounters with end dates before May 27th, 2021.
Article Synopsis
- - The National COVID Cohort Collaborative (N3C) is a massive electronic health record database that provides valuable insights into COVID-19, supporting the development of better diagnostic tools and clinical practices.
- - This study analyzed data from nearly 2 million adults across 34 medical centers to evaluate the severity of COVID-19 and its risk factors over time, using advanced machine learning techniques to predict severe outcomes.
- - Among the 174,568 adults infected with SARS-CoV-2, a significant portion experienced severe illness, highlighting the need for continuous monitoring and adjustment of treatment approaches based on demographic characteristics and disease severity.