Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Description: In the past 3 years, the use of intestinal ultrasound (IUS) for monitoring inflammatory bowel disease in clinical practice has grown substantially in the United States. This American Gastroenterological Association (AGA) Institute Clinical Practice Update (CPU) aims to review the available evidence and guidance regarding the role of intestinal ultrasound in inflammatory bowel disease care.
Methods: This CPU was commissioned and approved by the AGA Institute Clinical Practice Updates Committee (CPUC) and the AGA Governing Board to provide timely guidance on a topic of high clinical importance to the AGA membership and underwent internal peer review by the CPUC and external peer review through standard procedures of Clinical Gastroenterology and Hepatology. This expert commentary incorporates important and recently published studies in this field, and it reflects the experiences of the multidisciplinary group of authors composed of adult and pediatric gastroenterologists.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.cgh.2024.04.039 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Evaluating the effectiveness of ChemoNurse: A mobile chemotherapy drug guide for cancer nurses - A randomized controlled trial.
Eur J Oncol Nurs
August 2025
Koç University Hospital, Faculty of Medicine, Department of Medical Oncology, Istanbul, Türkiye. Electronic address:
Purpose: This study aimed to evaluate the effectiveness of a mobile chemotherapy drug guide application, ChemoNurse, developed for cancer nurses, in improving their knowledge and attitudes toward chemotherapy practices.
Methods: A randomized controlled trial with a repeated-measures design was conducted with 59 nurses (29 intervention, 30 control) who participated. Nurses in the intervention group used the ChemoNurse mobile application for six months, while the control group received no additional intervention.
Addressing Missingness in Predictive Models That Use Electronic Health Record Data.
Ann Intern Med
September 2025
Department of Medicine, Johns Hopkins University School of Medicine, and Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (J.B.S.).
Electronic health record (EHR) data are increasingly used to develop prediction models that guide clinical decision making at the point of care. These include algorithms that use high-frequency data, like in sepsis prediction, as well as simpler equations, such as the Pooled Cohort Equations for cardiovascular outcome prediction. Although EHR data used in prediction models are often highly granular and more current than other data, there is systematic and nonsystematic missingness in EHR data as there is with most data.
View Article and Find Full Text PDFEvaluating the Effect of a Molecular Point-of-Care Test on Acute Respiratory Infections in General Practice: Protocol for a Cluster Randomized Trial.
JMIR Res Protoc
September 2025
Research Unit of General Practice, Department of Public Health, University of Southern Denmark, Odense M, Denmark.
Background: Acute respiratory infections (ARIs) are frequent reasons for medical consultations in general practice and can lead to unnecessary recontacts. Introducing new point-of-care (POC) polymerase chain reaction (PCR) diagnostic equipment may offer an attractive and efficient way of providing a more precise and exact microbial diagnosis. Successful uptake of POC PCR equipment could potentially lead to a reduction in recontacts with benefits for both staff and patients.
View Article and Find Full Text PDFNeed Analysis of Clinician-Oriented Integrated Precision Oncology Decision Support Tools: Qualitative Descriptive Study.
JMIR Hum Factors
September 2025
College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Background: The rapid advancement of next-generation sequencing has significantly expanded the landscape of precision medicine. However, health care professionals face increasing challenges in keeping pace with the growing body of oncological knowledge and integrating it effectively into clinical workflows. Precision oncology decision support (PODS) tools aim to assist clinicians in navigating this complexity, yet their current functionalities only partially address clinical needs.
View Article and Find Full Text PDF