Predicting postoperative delirium in patients undergoing deep hypothermia circulatory arrest

Owen Ma, Arindam Dutta, Daniel W. Bliss, Amy Z. Crepeau

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cardiac surgeries involving deep hypothermia circulatory arrest present a risk of cognitive impairment. This study attempts to uncover intraoperative electroencephalogram (EEG) biomarkers predictive of postoperative delirium, which is associated with long term health complications. We predict postoperative delirium diagnoses by examining changes in ensemble neural activity during surgeries through spatiotemporal eigenspectra extracted from patient EEG data. Artifact detection and feature normalization schemes are developed to facilitate this. At most 14 of 16 cases were correctly predicted with a p-value of 0.0015. An area under the receiver operating characteristics (ROC) curve of 0.8364 was achieved-0.9091 when considering the convex hull.

Original languageEnglish (US)
Title of host publicationConference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1313-1317
Number of pages5
Volume2017-October
ISBN (Electronic)9781538618233
DOIs
StatePublished - Apr 10 2018
Event51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 - Pacific Grove, United States
Duration: Oct 29 2017Nov 1 2017

Other

Other51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
CountryUnited States
CityPacific Grove
Period10/29/1711/1/17

Fingerprint

hypothermia
Hypothermia
electroencephalography
Electroencephalography
surgery
Surgery
biomarkers
impairment
Receiver Operating Characteristic Curve
Biomarkers
p-Value
Complications
Convex Hull
Cardiac
Normalization
health
artifacts
Health
Ensemble
receivers

Keywords

  • Deep Hypothermia Circulatory Arrest
  • Electroencephalography
  • Intra-operative Monitoring
  • Neurophysiology
  • Signal Processing

ASJC Scopus subject areas

  • Control and Optimization
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Biomedical Engineering
  • Instrumentation

Cite this

Ma, O., Dutta, A., Bliss, D. W., & Crepeau, A. Z. (2018). Predicting postoperative delirium in patients undergoing deep hypothermia circulatory arrest. In Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 (Vol. 2017-October, pp. 1313-1317). [8335566] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACSSC.2017.8335566

Predicting postoperative delirium in patients undergoing deep hypothermia circulatory arrest. / Ma, Owen; Dutta, Arindam; Bliss, Daniel W.; Crepeau, Amy Z.

Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Vol. 2017-October Institute of Electrical and Electronics Engineers Inc., 2018. p. 1313-1317 8335566.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ma, O, Dutta, A, Bliss, DW & Crepeau, AZ 2018, Predicting postoperative delirium in patients undergoing deep hypothermia circulatory arrest. in Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. vol. 2017-October, 8335566, Institute of Electrical and Electronics Engineers Inc., pp. 1313-1317, 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017, Pacific Grove, United States, 10/29/17. https://doi.org/10.1109/ACSSC.2017.8335566
Ma O, Dutta A, Bliss DW, Crepeau AZ. Predicting postoperative delirium in patients undergoing deep hypothermia circulatory arrest. In Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Vol. 2017-October. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1313-1317. 8335566 https://doi.org/10.1109/ACSSC.2017.8335566
Ma, Owen ; Dutta, Arindam ; Bliss, Daniel W. ; Crepeau, Amy Z. / Predicting postoperative delirium in patients undergoing deep hypothermia circulatory arrest. Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Vol. 2017-October Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1313-1317
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