Early Presence of Sleep Spindles on Electroencephalography Is Associated With Good Outcome After Pediatric Cardiac Arrest.

Objectives: The role of sleep architecture as a biomarker for prognostication after resuscitation from cardiac arrest in children hospitalized in an ICU remains poorly defined. We sought to investigate the association between features of normal sleep architecture in children after cardiac arrest and a favorable neurologic outcome at 6 months.

Design: Retrospective review of medical records and continuous electroencephalography monitoring.

Setting: Cardiac and PICU of a tertiary children's hospital.

Patients: All patients from 6 months to 18 years old resuscitated from cardiac arrest who underwent continuous electroencephalography monitoring in the first 24 hours after in- or out-of-hospital cardiac arrest from January 2010 to June 2015.

Interventions: None.

Measurements And Main Results: Thirty-four patients underwent continuous electroencephalography monitoring after cardiac arrest. The median age was 6.1 years (interquartile range, 1.5-12.5 yr), 20 patients were male (59%). Most cases (n = 23, 68%) suffered from in-hospital cardiac arrest. Electroencephalography monitoring was initiated a median of 9.3 hours (5.8-14.9 hr) after return of spontaneous circulation, for a median duration of 14.3 hours (6.0-16.0 hr) within the first 24-hour period after the cardiac arrest. Five patients had normal spindles, five had abnormal spindles, and 24 patients did not have any sleep architecture. The presence of spindles was associated with a favorable neurologic outcome at 6-month postcardiac arrest (p = 0.001).

Conclusions: Continuous electroencephalography monitoring can be used in children to assess spindles in the ICU. The presence of spindles on continuous electroencephalography monitoring in the first 24 hours after resuscitation from cardiac arrest is associated with a favorable neurologic outcome. Assessment of sleep architecture on continuous electroencephalography after cardiac arrest could improve outcome prediction.