Detecting Delirium Using a Physiologic Monitor

Area of Science:

• Neuroscience
• Critical Care Medicine
• Geriatrics

Background:

• Delirium affects up to 20% of acute care and 80% of critically ill patients annually.
• Current diagnostic methods rely on behavioral symptoms, leading to missed diagnoses in approximately 80% of cases.
• The economic burden of delirium in the US is estimated at $164 million annually.

Purpose of the Study:

• To evaluate the utility of electroencephalogram (EEG) monitoring for early and accurate delirium detection.
• To explore the potential of newer, cost-effective EEG technologies for routine clinical use.

Main Methods:

• Review of the established utility of conventional electroencephalogram (EEG) in delirium diagnosis.
• Discussion of neurochemical and neuroelectrical changes preceding behavioral symptoms.
• Exploration of newer, limited-lead EEG technology with automatic processing capabilities.

Main Results:

• Neuroelectrical changes associated with delirium occur before behavioral symptoms, making EEG a potential tool for early identification.
• Integrating EEG analysis with clinical assessment significantly enhances delirium detection accuracy.
• Newer EEG technologies may reduce costs and the need for expert interpretation, making it more accessible.

Conclusions:

• EEG monitoring offers an objective method for earlier delirium recognition, potentially before symptom onset.
• Implementing accessible EEG technology could improve nursing interventions and reduce long-term patient consequences.
• Objective EEG assessment could revolutionize delirium care and establish a new standard of care.