ORIGINAL RESEARCH article
Front. Neurol.
Sec. Neurotechnology
This article is part of the Research TopicIntegrating Technology and Policy for Enhanced Neurological and Mental Health OutcomesView all 3 articles
An Exploratory Analysis of ACNS Electroencephalography Patterns in 34 Comatose Patients after In-Hospital Cardiopulmonary Resuscitation
Provisionally accepted
- Beijing Tongren Hospital CMU, Beijing, China
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Background: To evaluate the prognostic value of electroencephalogram (EEG) patterns in comatose patients after in-hospital adult cardiopulmonary resuscitation (CPR). Methods: Retrospectively, we collected clinical and EEG data from 34 patients following in-hospital CPR. The EEG data were classified into seven patterns defined in accordance with the 2021 American Clinical Neurophysiology Society (ACNS) terminology. All patients were further categorized into distinct groups based on their EEG characteristics: background frequency and EEG categorization. Outcome of patients at discharge was assessed using the Glasgow Outcome Score (GOS) as 1-2 (poor) or 3-5 (good). Baseline characteristics and EEG pattern were compared between outcome groups. Receiver operating characteristic (ROC) analysis evaluated the predictive performance of EEG background frequency and EEG categorization. Area under the curve (AUC) difference was compared using the DeLong test. Results: The study included 34 patients, all of whom underwent in-hospital CPR. Patients with poor outcomes had lower GCS scores (3.0 [interquartile range, 3.0-4.0] vs. 6.0 [interquartile range, 3.0-7.0], p = 0.006). Statistically significant differences were identified in CPR duration (p = 0.030) and time of ROSC establishment (p = 0.026). Our exploratory analyses indicated that increased slow wave pattern and theta dominant background were associated with good neurological outcomes (p < 0.001, p = 0.007, respectively), while a potential association was observed between the beta dominant background and poor prognosis (p < 0.001). For EEG categorization, the results revealed that Group (I) was more common among good-outcome patients and Group (III) was associated with an increased likelihood of clinical deterioration at discharge (p < 0.001, p = 0.003, respectively). The presence of the EEG background frequency yielded an AUC of 0.889 (95% CI: 0.734 - 0.971, sensitivity 69.6%, specificity 99.9%), while EEG categorization yielded an AUC of 0.913 (95% CI: 0.765 - 0.982, sensitivity 82.6%, specificity 99.9%), with no significant AUC difference between the two indicators. Conclusion: Applying the 2021 version ACNS standardized terminology to analyze EEG patterns is helpful for predicting the prognosis of comatose patients following CPR. Our preliminary findings suggest a potential association between EEG patterns and neurological outcomes, although this requires further validation in larger, prospective studies.
Keywords: Electroencephalography, Cardiopulmonary Resuscitation, Coma, American Clinical Neurophysiology Society, prognosis
Received: 22 Sep 2025; Accepted: 30 Nov 2025.
Copyright: © 2025 Bo, Yang, xin, juan and wei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Qinglin Yang
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