Cardiac arrest & resuscitation
Personalized neuron-specific enolase level based on EEG pattern for prediction of poor outcome after cardiac arrest
Authors' conclusion
In comatose patients after AC, a personalized approach of NSE according to EEG pattern could improve the specificity and sensitivity of this biomarker for poor outcome prediction.
Study context
- Population
- Adults comatose 72 h after cardiac arrest, tertiary cardiac arrest (CA) center
- Participants
- 155 participants
- Exposure
- Neuron-specific enolase (NSE) thresholds for poor outcome by EEG pattern
- Outcome
- Poor neurological outcome (CPC 3-5)
- Follow-up
- 3 months
Methodological detailssingle-centre, prospective registry
- Single-centre
- Prospective registry
Main finding
As reported in the abstract
NSE threshold predicting poor outcome by EEG pattern
- Malignant EEG: NSE > 45.2 µg/L, specificity 100%, sensitivity 70.8% (recommended 60 µg/l cut-off: Se = 66%)
- Electrographic seizures: NSE > 53.5 µg/L, specificity 100%, sensitivity 77.7% (recommended cut-off: Se = 66.6%)
- Benign EEG: NSE > 78.2 µg/L, Sp = 100% (recommended cut-off: Sp = 94%)
Observational data: associations, not effects.
Further findings
Electrographic seizures
P = 0.50
| Outcome | Good outcome | Poor outcome | P value |
|---|---|---|---|
| NSE blood level by outcome | median 20 (IQR 15–30) µg/L | median 110 (IQR 49–308) µg/l | P < 0,001 |
NSE level by EEG pattern
- Benign EEG associated with lower NSE vs malignant and highly malignant patterns (p < 0.001)
- NSE not significantly increased with seizures vs malignant patterns (p = 0.15)
Original publication
Personalized neuron-specific enolase level based on EEG pattern for prediction of poor outcome after cardiac arrest. Ann Intensive Care. Published 17 January 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →