Assessing both early and late EEG patterns improves prediction of outcome after cardiac arrest
(2025) In Resuscitation 215.- Abstract
Objective: Previously proposed “synchronous EEG patterns” predict poor outcome within 24 h after cardiac arrest (CA). We investigate the prognostic performance of these early EEG predictors in addition to the late EEG predictors (>24 h) recommended in the European post-resuscitation guidelines. Methods: Observational substudy of the TTM2-trial including consecutive comatose resuscitated patients. Continuous EEG-monitoring (cEEG) was blindly assessed using the American Clinical Neurophysiology Societýs standardised EEG terminology and categorised into early EEG predictors (burst-suppression with identical or highly epileptiform bursts, or suppression with generalised periodic discharges) and late EEG predictors (heterogenous... (More)
Objective: Previously proposed “synchronous EEG patterns” predict poor outcome within 24 h after cardiac arrest (CA). We investigate the prognostic performance of these early EEG predictors in addition to the late EEG predictors (>24 h) recommended in the European post-resuscitation guidelines. Methods: Observational substudy of the TTM2-trial including consecutive comatose resuscitated patients. Continuous EEG-monitoring (cEEG) was blindly assessed using the American Clinical Neurophysiology Societýs standardised EEG terminology and categorised into early EEG predictors (burst-suppression with identical or highly epileptiform bursts, or suppression with generalised periodic discharges) and late EEG predictors (heterogenous burst-suppression or suppression). Poor outcome was defined as modified Rankin Scale 4–6 at six months. Results: Of 191 included patients, 53 % had poor outcome. Early EEG predictors had 100 %[CI 96–100] specificity at all time-points and maximal sensitivity 30 %[CI 21–40] before 24 h. Late EEG predictors had 100 %[CI 96–100] specificity beyond 24 h with maximal sensitivity 32 %[CI 21–43]. Using both early and late EEG predictors, and gradually adding cEEG-information from consecutive time-epochs, sensitivity increased to 49 %[CI 39–59] up to 36 h after CA (p = 0.001). A continuous background within 12 h predicted good outcome (sensitivity 61 %[CI 50–71]; specificity 87 %[CI 79–93]). Conclusion: Searching for both early EEG predictors (e.g. identical burst-suppression) and late EEG predictors (e.g. heterogenous burst-suppression > 24 h) significantly improved sensitivity of poor outcome prediction without false positive survivors in this cohort. A self-fulfilling prophecy may have affected our results. cEEG during the first two days after CA identified half of the patients with a long-term poor outcome and half of the patients with a good outcome.
(Less)
- author
- organization
-
- Neurosurgery
- Brain Injury After Cardiac Arrest (research group)
- Center for cardiac arrest (research group)
- Clinical Sciences, Helsingborg
- Anesthesiology and Intensive Care
- Clinical Research in Anaesthesia and Intensive Care Medicine (research group)
- Cardiology
- Neurology, Lund
- Neurological injury in acute type A aortic dissection (research group)
- SEBRA Sepsis and Bacterial Resistance Alliance (research group)
- Anaesthesiology and Intensive Care Medicine (research group)
- Clinical Neurophysiology
- publishing date
- 2025-10
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Cardiac arrest, continuous EEG monitoring, Prognostication
- in
- Resuscitation
- volume
- 215
- article number
- 110762
- publisher
- Elsevier
- external identifiers
-
- scopus:105013772852
- pmid:40783100
- ISSN
- 0300-9572
- DOI
- 10.1016/j.resuscitation.2025.110762
- language
- English
- LU publication?
- yes
- id
- 34539a9a-9c14-44b7-8e3a-96917338bd7d
- date added to LUP
- 2025-10-13 10:16:57
- date last changed
- 2025-10-14 11:04:11
@article{34539a9a-9c14-44b7-8e3a-96917338bd7d, abstract = {{<p>Objective: Previously proposed “synchronous EEG patterns” predict poor outcome within 24 h after cardiac arrest (CA). We investigate the prognostic performance of these early EEG predictors in addition to the late EEG predictors (>24 h) recommended in the European post-resuscitation guidelines. Methods: Observational substudy of the TTM2-trial including consecutive comatose resuscitated patients. Continuous EEG-monitoring (cEEG) was blindly assessed using the American Clinical Neurophysiology Societýs standardised EEG terminology and categorised into early EEG predictors (burst-suppression with identical or highly epileptiform bursts, or suppression with generalised periodic discharges) and late EEG predictors (heterogenous burst-suppression or suppression). Poor outcome was defined as modified Rankin Scale 4–6 at six months. Results: Of 191 included patients, 53 % had poor outcome. Early EEG predictors had 100 %[CI 96–100] specificity at all time-points and maximal sensitivity 30 %[CI 21–40] before 24 h. Late EEG predictors had 100 %[CI 96–100] specificity beyond 24 h with maximal sensitivity 32 %[CI 21–43]. Using both early and late EEG predictors, and gradually adding cEEG-information from consecutive time-epochs, sensitivity increased to 49 %[CI 39–59] up to 36 h after CA (p = 0.001). A continuous background within 12 h predicted good outcome (sensitivity 61 %[CI 50–71]; specificity 87 %[CI 79–93]). Conclusion: Searching for both early EEG predictors (e.g. identical burst-suppression) and late EEG predictors (e.g. heterogenous burst-suppression > 24 h) significantly improved sensitivity of poor outcome prediction without false positive survivors in this cohort. A self-fulfilling prophecy may have affected our results. cEEG during the first two days after CA identified half of the patients with a long-term poor outcome and half of the patients with a good outcome.</p>}}, author = {{Admiraal, Marjolein and Backman, Sofia and Annborn, Martin and Borgquist, Ola and Dankiewicz, Josef and Düring, Joachim and Moseby-Knappe, Marion and Legriel, Stéphane and Lindehammar, Hans and Lybeck, Anna and Nielsen, Niklas and Rossetti, Andrea O. and Undén, Johan and Cronberg, Tobias and Westhall, Erik}}, issn = {{0300-9572}}, keywords = {{Cardiac arrest; continuous EEG monitoring; Prognostication}}, language = {{eng}}, publisher = {{Elsevier}}, series = {{Resuscitation}}, title = {{Assessing both early and late EEG patterns improves prediction of outcome after cardiac arrest}}, url = {{http://dx.doi.org/10.1016/j.resuscitation.2025.110762}}, doi = {{10.1016/j.resuscitation.2025.110762}}, volume = {{215}}, year = {{2025}}, }