false
OasisLMS
Catalog
SCCM Resource Library
Year in Review: Late-Breaking Nursing Studies
Year in Review: Late-Breaking Nursing Studies
Back to course
[Please upgrade your browser to play this video content]
Video Transcription
Video Summary
This video presentation discusses late-breaking nursing studies, with a particular focus on a complex study from the University of Pittsburgh. This study explored the use of machine learning to improve ECG diagnosis and risk stratification of occlusive myocardial infarction (OMI). The algorithm, called ECG-SMART, demonstrated outstanding diagnostic accuracy in identifying OMI, which is typically hard to detect due to subtle signs not visible on standard 12-lead EKGs. It showed a good potential to aid emergency personnel in the field by significantly improving OMI detection rates and potentially saving lives. Additionally, the presentation touches on two other studies: one on using an interactive hand grip game to improve psychological and physical outcomes in ICU patients, and another on a swallowing and oral care program to help patients resume oral feeding and reduce pneumonia risk post-extubation. These studies emphasize innovations in patient care and potential areas for nurse-led research initiatives.
Asset Caption
Year in Review | Year in Review: Nursing
Meta Tag
Content Type
Presentation
Membership Level
Professional
Membership Level
Select
Year
2024
Keywords
machine learning
ECG diagnosis
occlusive myocardial infarction
nursing studies
patient care innovations
×
Please select your language
1
English