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Electroencephalogram-Based Complexity Measures as Predictors of Post-operative Neurocognitive Dysfunction.

Leah Acker1,2, Christine Ha2, Junhong Zhou3,4

  • 1Department of Anesthesiology, Duke University School of Medicine, Durham, NC, United States.

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|December 3, 2021
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Summary

Electroencephalogram (EEG) complexity, measured by multi-scale entropy (MSE), increases during surgery in older adults. The specific crossover point where preoperative and intraoperative EEG complexity meet may help predict postoperative delirium.

Keywords:
anesthesiaattentioncognitioncomplexitydeliriumelectroencephalogram (EEG)perioperative medicineresilience

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Area of Science:

  • Neuroscience
  • Gerontology
  • Medical Engineering

Background:

  • Physiologic signals like electroencephalogram (EEG) exhibit complex behaviors due to multi-scale control processes.
  • Multi-scale entropy (MSE) quantifies this complexity, with higher complexity generally indicating better health.
  • Postoperative delirium is difficult to predict, necessitating novel biomarkers.

Purpose of the Study:

  • To investigate if preoperative and intraoperative frontal EEG complexity, using MSE, can predict postoperative delirium and inattention in older adults.
  • To analyze the relationship between EEG complexity changes and the development of postoperative delirium.

Main Methods:

  • Computed MSE for frontal EEG recordings in 50 patients aged 60 and above, before and during surgery.
  • Assessed complexity by calculating the area under the curve of sample entropy plotted against different time scales.
  • Examined the crossover point where preoperative and intraoperative MSE curves intersected.

Main Results:

  • Average EEG MSE was significantly higher intra-operatively compared to pre-operatively (p = 0.0003).
  • A scale-dependent interaction was observed: intraoperative MSE was lower at small scales and higher at large scales than preoperative MSE (interaction p < 0.001).
  • Overall EEG complexity did not correlate with delirium or attention, but the crossover point scale showed a trend towards inverse association with delirium severity change (Spearman ρ = -0.31, p = 0.054).

Conclusions:

  • Intraoperative EEG complexity increases in older adults but is dependent on the scale of analysis.
  • The crossover point of preoperative and intraoperative EEG complexity may serve as a potential predictor for postoperative delirium.
  • Further research is warranted to explore if this crossover point reflects neural mechanisms underlying delirium susceptibility.