What is the Delirium Bibliography? The searchable Delirium Bibliography page is one of our most popular features, allowing you to quickly gain access to the literature on delirium and acute care of older persons. It is primarily intended for clinicians and researchers interested in exploring these topics. The NIDUS team keeps it updated for you on a monthly basis!
How to Search for Articles: Search by author, title, year, and/or keywords. Each article is indexed by keywords taken from MEDLINE and other relevant databases. Click on the title of the article to read the abstract, journal, etc.
Reference Information
- Title
- Automated tracking of level of consciousness and delirium in critical illness using deep learning
- Authors
- Sun, H. Kimchi, E. Akeju, O. Nagaraj, S. B. McClain, L. M. Zhou, D. W. Boyle, E. Zheng, W. L. Ge, W. Westover, M. B.
- Year
- 2019
- Journal
- NPJ Digital Medicine
- Abstract
Over- and under-sedation are common in the ICU, and contribute to poor ICU outcomes including delirium. Behavioral assessments, such as Richmond Agitation-Sedation Scale (RASS) for monitoring levels of sedation and Confusion Assessment Method for the ICU (CAM-ICU) for detecting signs of delirium, are often used. As an alternative, brain monitoring with electroencephalography (EEG) has been proposed in the operating room, but is challenging to implement in ICU due to the differences between critical illness and elective surgery, as well as the duration of sedation. Here we present a deep learning model based on a combination of convolutional and recurrent neural networks that automatically tracks both the level of consciousness and delirium using frontal EEG signals in the ICU. For level of consciousness, the system achieves a median accuracy of 70% when allowing prediction to be within one RASS level difference across all patients, which is comparable or higher than the median technician–nurse agreement at 59%. For delirium, the system achieves an AUC of 0.80 with 69% sensitivity and 83% specificity at the optimal operating point. The results show it is feasible to continuously track level of consciousness and delirium in the ICU.
- PMID
- Keywords
propofol
adult
aged
APACHE
article
artificial ventilation
body mass
brain function
clinical research
consciousness level
convolutional neural network
critical illness
deep learning
delirium
elective surgery
electroencephalography
eye movement
female
human
intensive care unit
long short term memory network
major clinical study
male
neuromonitoring
observational study
priority journal
prospective study
recurrent neural network
Richmond Agitation Sedation Scale
sedation
sensitivity and specificity
- Page(s)
- Volume
- 2
- Issue
- 1
| Title | Authors | Journal | Year | Keywords |
|---|---|---|---|---|
| Undiagnosed delirium is frequent and difficult to predict: Results from a prevalence survey of a tertiary hospital. | Lange, P. W. Lamanna, M. Watson, R. Maier, A. B. | J Clin Nurs | 2019 |
Undiagnosed delirium |