Serum neuron-specific enolase as predictor of outcome in comatose cardiac-arrest survivors: a prospective cohort study

Abstract

Abstract Background The prediction of neurological outcome in comatose patients after cardiac arrest has major ethical and socioeconomic implications. The purpose of this study was to assess the capability of serum neuron-specific enolase (NSE), a biomarker of hypoxic brain damage, to predict death or vegetative state in comatose cardiac-arrest survivors. Methods We conducted a prospective observational cohort study in one university hospital and one general hospital Intensive Care Unit (ICU). All consecutive patients who suffered cardiac arrest and were subsequently admitted from June 2007 to February 2009 were considered for inclusion in the study. Patients who died or awoke within the first 48 hours of admission were excluded from the analysis. Patients were followed for 3 months or until death after cardiopulmonary resuscitation. The Cerebral Performance Categories scale (CPC) was used as the outcome measure; a CPC of 4-5 was regarded as a poor outcome, and a CPC of 1-3 a good outcome. Measurement of serum NSE was performed at 24 h and at 72 h after the time of cardiac arrest using an enzyme immunoassay. Clinicians were blinded to NSE results. Results Ninety-seven patients were included. All patients were actively supported during the first days following cardiac arrest. Sixty-five patients (67%) underwent cooling after resuscitation. At 3 months 72 (74%) patients had a poor outcome (CPC 4-5) and 25 (26%) a good outcome (CPC 1-3). The median and Interquartile Range [IQR] levels of NSE at 24 h and at 72 h were significantly higher in patients with poor outcomes: NSE at 24 h: 59.4 ng/mL [37-106] versus 28.8 ng/mL [18-41] (p p Conclusion NSE levels measured early in the course of patient care for those who remained comatose after cardiac arrest were significantly higher in patients with outcomes of death or vegetative state. In addition, we provide a cut-off value for NSE (> 97 ng/mL) with 100% positive predictive value of poor outcome. Nevertheless, for decisions concerning the continuation of treatment in this setting, we emphasize that an approach based on a combination of SSEPs, NSE and clinical EEG would be more accurate for identifying patients with a poor neurological outcome.