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Value of Isolated vs Multiple Malignant EEG Criteria to Reduce Prognostic Uncertainty in Comatose Patients After
Sarah Benghanem1,2,3,4, Jan Novy1, Alain Cariou2,4
1Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Switzerland.
Insights
Combining malignant electroencephalogram (EEG) criteria improves prediction of poor neurologic outcomes in comatose cardiac arrest survivors. This approach significantly reduces prognostic uncertainty, aiding clinical decision-making.
Area of Science:
- Neurology
- Critical Care Medicine
- Neurophysiology
Background:
- Comatose patients post-cardiac arrest (CA) often have uncertain prognoses based on electroencephalogram (EEG) patterns.
- Current guidelines recognize only
- highly malignant
- or
- benign
- EEG patterns as definitive outcome markers.
- A significant number of patients with
- malignant
- EEG patterns fall into a prognostic gray zone.
Purpose of the Study:
- To evaluate the prognostic value of combined malignant EEG criteria for predicting poor neurologic outcome in comatose CA survivors.
- To assess the impact of these combined criteria on reducing prognostic uncertainty.
- To refine outcome prediction beyond current binary classifications.
Main Methods:
- A bicentric cohort study included 1,076 comatose adults undergoing EEG after CA.
- EEGs were classified using Westhall et al. criteria: highly malignant, malignant, or benign.
- Prognostic performance of isolated and combined malignant EEG criteria was assessed for predicting poor neurologic outcome (Cerebral Performance Category 3-5 at 3 months).
Main Results:
- Among 1,076 patients, 633 died and 317 had good outcomes; EEG patterns varied, with 39.1% classified as malignant.
- While single malignant EEG features had low sensitivity for poor outcome, combinations of 2, 3, or 4 criteria demonstrated high specificity (up to 100%).
- In patients with indeterminate prognosis, applying combined malignant EEG criteria reclassified 31.3% into a
- likely poor outcome
- category, reducing uncertainty.
Conclusions:
- The combination of multiple malignant EEG criteria offers high specificity for predicting poor neurologic outcomes.
- This approach significantly reduces prognostic uncertainty in comatose cardiac arrest survivors.
- It provides a more nuanced tool for prognostication beyond current EEG classifications.
Background And Objectives:
In comatose patients after cardiac arrest (CA), only "highly malignant" or "benign" EEG patterns are recognized as robust markers of poor and good outcomes, respectively, whereas many patients with "malignant" EEG remain in prognostic uncertainty. We aimed to assess the prognostic value of combined malignant EEG criteria for poor neurologic outcome in this clinical setting and to evaluate their effect on reduction of prognostic uncertainty.
Methods:
We conducted a bicentric cohort study using institutional registries (CHUV, Switzerland; Cochin Hospital, France), including comatose adults who underwent EEG >24 hours after CA. EEGs were categorized according to Westhall et al.: highly malignant, malignant, or benign. We assessed the prognostic performance of isolated and combined malignant EEG criteria (recorded on a single EEG after targeted temperature management) and their ability to reduce prognostic uncertainty in patients with an "indeterminate prognosis" according to current European recommendations. Poor neurologic outcome was defined as a Cerebral Performance Category 3-5 at 3 months.
Results:
Between 2017 and 2024, 1,076 patients were included (CHUV: 655; Cochin: 421). The mean age was 61.7 (SD ± 15.2) years, and 291 (27.2%) were female; 633 (59.5%) died while 317 (29.5%) had a good outcome. EEG was highly malignant in 23.6%, malignant in 39.1%, and benign in 36.8%. One malignant EEG feature predicted poor outcome (specificity 81.4% [95% CI 77.10-85.67]), sensitivity 24.2% ([95% CI 21.19-27.29]). Two, 3, or 4 malignant EEG criteria were highly specific (98.1% ([95% CI 96.61-99.61], 100% [95% CI 100.00-100.00], and 100% [95% CI 100.00-100.00], respectively), with limited sensitivity (16.9% [95% CI 14.20-19.53], 4.6% [95% CI 3.12-6.10], and 0.4% [95% CI 0.00-0.84]). Among the 725 lacking 2 criteria for poor outcome according to recommendations, 386 had a benign EEG, leaving 339 in the indeterminate outcome group. Among these, multiple malignant EEG features reclassified 106 patients into the "likely poor outcome" category, reducing prognostic uncertainty by 31.3%.
Discussion:
The combination of multiple malignant EEG criteria seems to be as specific as a highly malignant EEG in predicting poor neurologic outcome. Using these criteria significantly reduces prognostic uncertainty.
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