Delirium after cardiac arrest: Phenotype, prediction, and outcome.

Resuscitation

Department of Neurology, Rijnstate Hospital, Arnhem, The Netherlands; Department of Clinical Neurophysiology, Technical Medical Center, University of Twente, Enschede, The Netherlands.

Published: June 2020

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Article Abstract

Aim: To establish incidence, phenotype, long-term functional outcome, and early EEG predictors of delirium after cardiac arrest.

Methods: This is an ad hoc analysis of a prospective cohort study on outcome prediction of comatose patients after cardiac arrest. Patients with recovery of consciousness, who survived until hospital discharge, were subdivided in groups with and without delirium based on psychiatric consultation. Delirium phenotype and medical treatment were retrieved from patient files. All other data were prospectively collected. We used univariate analyses of baseline and early EEG characteristics for identification of possible delirium predictors. Association of delirium with neurological recovery at six months was analyzed with multinomial logistic regression analysis.

Results: Of 233 patients, 141 survived until hospital discharge, of whom 47 (33%) were diagnosed with delirium. There were no differences in baseline characteristics between patients with and without delirium. All delirious patients were treated with relatively high dosages of psychopharmaceuticals, mostly haloperidol and benzodiazepine agonists. Prevalent characteristics were disturbed cognition, perception and psychomotor functioning (98%). Half of the patients had language disorders or shouting. Delirium was associated with longer ICU and hospital admission, and more frequent discharge to rehabilitation centre or nursing home. There was a trend towards poorer neurological recovery. EEG measurements within 12 h after cardiac arrest could predict delirium with 91% specificity and 40% sensitivity.

Discussion: Delirium is common after cardiac arrest, and probably leads to longer hospitalization and poorer outcome. Optimal treatment is unclear. Early EEG holds potential to identify patients at risk.

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Source
http://dx.doi.org/10.1016/j.resuscitation.2020.03.020DOI Listing

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