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 (ΔNSE) 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 ΔNSE > 31.3 ng/ml gave a specificity of 1.00 and sensitivity of 0.54. In patients who did not survive to hospital discharge, ΔNSE > 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.
Keywords: NSE; OHCA; Prognostication.
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