Can Artificial Intelligence Be Utilized to Predict Real-Time Adverse Outcomes in Individuals Arriving at the Emergency Department With Hyperglycemic Crises?: Implications for APRN Practice.
Alisha Amin BhimaniTova Safier FrenkelAdam Kaizer HashamPublished in: Advanced emergency nursing journal (2024)
This column on translating research into practice is crafted to offer advanced practice registered nurses an analysis of current research topics that hold practical relevance for emergency care settings. The article titled "Using Artificial Intelligence to Predict Adverse Outcomes in Emergency Department Patients With Hyperglycemic Crises in Real Time," authored by C. Hsu et al. (2023), investigates through a randomized control trial, the effectiveness of artificial intelligence as a practical tool compared with the traditional predicting hyperglycemic crisis death score to clinically predict adverse outcomes in individuals presenting to the emergency department with hyperglycemic crises. The results are discussed in the context of averting adverse outcomes associated with sepsis/septic shock, intensive care unit admission, and all-cause mortality within a 1-month time frame.
Keyphrases
- artificial intelligence
- emergency department
- septic shock
- healthcare
- intensive care unit
- machine learning
- big data
- deep learning
- primary care
- quality improvement
- public health
- randomized controlled trial
- palliative care
- systematic review
- mental health
- mechanical ventilation
- high resolution
- mass spectrometry
- simultaneous determination