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Acute confusion, Delirium, EEG, Older adult



  1. Mulkey, Malissa A. PhD, APRN, CCNS, CCRN, CNRN
  2. Gantt, Laura T. PhD, RN, CEN, CHSE
  3. Hardin, Sonya R. PhD, NP-C, FAAN
  4. Munro, Cindy L. PhD, ANP-BC, FAAN, FAANP, FAAAS
  5. Everhart, D. Erik PhD, ABPP
  6. Kim, Sunghan PhD
  7. Schoeman, Alexander M. PhD
  8. Roberson, Donna W. PhD, FNP-BC
  9. McAuliffe, Maura PhD, CRNA, FAAN
  10. Olson, DaiWai M. PhD, RN, CCRN, FNC


Background: Delirium-related biochemical derangements lead to electrical changes that can be detected in electroencephalographic (EEG) patterns followed by behavioral signs and symptoms. Studies using limited lead EEG show a large difference between patients with and without delirium while discriminating delirium from other causes. Handheld rapid EEG devices may be capable of detecting delirium before symptom onset, thus providing an objective physiological method to detect delirium when it is most amenable to interventions.


Objective: The aim of this study was to explore the potential for rapid EEG to detect waveform pattern changes consistent with delirium status.


Methods: This prospective exploratory pilot study used a correlational design and mixed models to explore the relationships between handheld portable EEG data and delirium status.


Results: While being under powered minimized opportunities to detect statistical differences in EEG-derived ratios using spectral density analysis, sleep-to-wake ratios tended to be higher in patients with delirium.


Conclusions: Limited lead EEG may be useful in predicting adverse outcomes and risk for delirium in older critically ill patients. Although this population is at the highest risk for mortality, delirium is not easily identified by current clinical assessments. Therefore, further investigation of limited lead EEG for delirium detection is warranted.