Association of EEG and Blood-Based Brain Injury Biomarker Accuracy to Prognosticate Mortality After Pediatric Cardiac Arrest: An Exploratory Study.

BACKGROUND:Evaluate the accuracy of brain-based blood biomarkers neuron-specific enolase (NSE) and S100b and electroencephalography (EEG) features alone and in combination with prognosticate 6-month mortality after pediatric cardiac arrest. We hypothesized that the combination of blood brain-based biomarkers and EEG features would have superior classification accuracy of outcome versus either alone. METHODS:Children (n = 58) aged between 1 week and 17 years admitted to the ICU following cardiac arrest at a tertiary care children's hopital were eligible for this secondary study. Blood NSE and S100b were measured closest to 24 hours after return of spontaneous circulation (ROSC). EEGs closest to 24 hours (median 11, interquartile range [IQR] 6 to 16 h) post-ROSC were evaluated by two epileptologists. EEG grade was informed by background frequency, amplitude, and continuity. Sleep spindles were present or absent. Mortality was assessed at six months post-ROSC. Area under the receiver operator curve (AUC) was performed for individual and combined brain-based biomarkers and EEG features. RESULTS:Children were aged 2.6 (IQR 0.6 to 10.4) years, and 25 (43%) died. Children who died had increased blood NSE (49.7 [28.0 to 63.1] vs 18.2 [9.8 to 31.8] ng/mL) and S100b (0.118 [0.036 to 0.296] vs 0.012 [0.003 to 0.021] ng/mL) and poor (discontinuous or isoelectric) EEG grade (76% vs 33%) more frequently than survivors (P < 0.05). AUC for NSE to predict mortality was 0.789, and was 0.841 when combined with EEG grade and spindles. S100b AUC for mortality was 0.856 and was optimal alone. CONCLUSIONS:In this exploratory study, the combination of brain-based biomarkers and EEG features may provide more accurate prognostication than either test alone after pediatric cardiac arrest.