Serial NSE measurement identifies non-survivors following out of hospital cardiac arrest

Aims: Prognostication following out-of-hospital cardiac arrest (OHCA) remains challenging. A multimodal approach is favoured, including consideration of the biomarker neuron-specific enolase (NSE) (Sandroni et al., 2014). Our objective was to investigate the utility of serial NSE measurements and to determine an appropriate cut-off value for prediction of death before hospital discharge using data from our tertiary care center.

Methods: Retrospective analysis of patients admitted to the critical care unit of a tertiary center critical care unit in the UK following an out-of-hospital cardiac arrest.

Measurements and main results: We analysed data from 72 patients admitted to our unit over 8 months following out-of-hospital cardiac arrest. Initial NSE level (NSE₀) was a poor predictor of outcome. Both NSE level at 48 h post-admission (NSE₄₈) and change in NSE from baseline to 48 h post-admission (Δ_NSE) were good predictors of outcome. A cut-off of NSE₄₈ > 69.8 ng/ml gave a specificity of 1.00 and sensitivity of 0.62 for prediction of death before hospital discharge in our patient group, whilst a cut-off of Δ_NSE > 31.3 ng/ml gave a specificity of 1.00 and sensitivity of 0.54. In patients who did not survive to hospital discharge, Δ_NSE > 9.4 ng/ml was associated with other poor prognostic factors (asytolic/PEA arrest, long downtime before ROSC) and with more rapid deterioration before death.

Conclusion: Serial measurement of NSE levels (at 0 and 48 h after admission) provides a useful tool to aid prognostication following out-of-hospital cardiac arrest.