Cardiac arrest & resuscitation
The predictive value of highly malignant EEG patterns after cardiac arrest: evaluation of the ERC-ESICM recommendations
Authors' conclusion
The specificity of the ERC-ESICM-recommended EEG patterns for predicting poor outcome after CA exceeds 90% but is lower than in previous studies, suggesting that large-scale implementation may reduce their accuracy.
Study context
- Population
- Patients after cardiac arrest (CA) in the Targeted Temperature Management trial 2, 59 sites
- Participants
- 845 patients · 59 sites
- Comparison
- HMEP (suppression or burst-suppression) on EEG > 24 h after CA, alone and combined with unreactive background, to predict poor outcome
- Primary endpoint
- Prognostic accuracy of HMEP for poor outcome (modified Rankin Scale 4-6)
- Follow-up
- 6 months
Methodological detailspre-planned prognostic substudy, multicentre, prospective EEG reporting, Multimodal prognostication; Withdrawal of life-sustaining therapy (WLST) not allowed before 96 h after CA
- Pre-planned prognostic substudy
- Multicentre
- Prospective EEG reporting
- Multimodal prognostication; WLST not allowed before 96 h after CA
Primary result
As reported in the abstract
Prediction of poor outcome
| Group | Sensitivity | Specificity |
|---|---|---|
| HMEP | 50% [95% CI 46-54] | 93% [90-96] |
HMEP
Sensitivity50% [95% CI 46-54]
Specificity93% [90-96]
Further findings
| Outcome | Unreactive HMEP | P value |
|---|---|---|
| Specificity of unreactive HMEP | P = 0.008 | |
| Specificity | 97% [94-99] |
- Specificity of HMEP in patients without WLST (subgroup)
- 93% · specificity
- Specificity of HMEP in patients without WLST (subgroup): 541 patients without WLST
Poor outcome · 6 months
- Poor outcome
- 579 (69%)
- WLST due to poor neurological prognosis
- 304 (36%)
- Timing of EEG after CA, median (IQR)
- 71 h (52-93)
Original publication
The predictive value of highly malignant EEG patterns after cardiac arrest: evaluation of the ERC-ESICM recommendations. Intensive Care Med. Published 3 January 2024. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →