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Published in: Journal of Clinical Monitoring and Computing 2/2018

01-04-2018 | Brief Communication

Infrared pupillometry helps to detect and predict delirium in the post-anesthesia care unit

Authors: Eric Yang, Matthias Kreuzer, September Hesse, Paran Davari, Simon C. Lee, Paul S. García

Published in: Journal of Clinical Monitoring and Computing | Issue 2/2018

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Abstract

This study evaluates the capability of pupillary parameters to detect and predict delirium in the post-anesthesia care unit (PACU-D) following general anesthesia. PACU-D may complicate and prolong the patient’s postoperative course, consequently increasing hospital costs. After institutional approval, 47 patients undergoing surgical interventions with general anesthesia were included in the study. We measured the pupillary reflexes at signing of informed consent, during surgery 20 min after intubation and when the primary inhaled anesthetic was turned off, and 15 and 45 min after PACU admittance and upon discharge from the PACU. We evaluated patients for delirium using the confusion assessment method for the intensive care unit (CAM-ICU) score after 15 and 60 min in the PACU. We chose receiver operating curve (ROC) and area under the curve (AUC) to compare the performance of non-pupillary parameters to pupillary parameters, such as pupil diameter, percent constriction, and dilation velocity, to detect and predict PACU-D. Percent constriction (AUC = 0.93, optimal threshold = 18.5%) and dilation velocity (AUC = 0.93, optimal threshold = 0.35 mm/s) showed excellent ability to detect and predict delirium persisting throughout the PACU stay. These pupillary measures showed superior performance compared to other pupillary measures and features commonly associated with delirium, e.g., age (AUC = 0.73), total opioids (AUC = 0.56), or length of surgery (AUC = 0.40). Our results suggest that pupillometry and the parameters derived from the recording may identify delirious patients in the PACU. This information can help to efficiently structure their care in a timely manner, and potentially avoid adverse complications for the patient and financial consequences for the hospital.
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Metadata
Title
Infrared pupillometry helps to detect and predict delirium in the post-anesthesia care unit
Authors
Eric Yang
Matthias Kreuzer
September Hesse
Paran Davari
Simon C. Lee
Paul S. García
Publication date
01-04-2018
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 2/2018
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-017-0009-z

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