Academic Journal
A continuous convolutional neural network: very early EEG most predictive for poor neurological outcome in postanoxic coma.
| Τίτλος: | A continuous convolutional neural network: very early EEG most predictive for poor neurological outcome in postanoxic coma. |
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| Συγγραφείς: | Hodžić I; Amsterdam UMC, University of Amsterdam, Department of Neurology/Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, the Netherlands., Doelkahar B; Amsterdam UMC, University of Amsterdam, Department of Neurology/Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, the Netherlands., Horn J; Amsterdam UMC, University of Amsterdam, Department of Intensive Care, Amsterdam Neuroscience, Amsterdam, the Netherlands., van Rootselaar AF; Amsterdam UMC, University of Amsterdam, Department of Neurology/Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, the Netherlands. Electronic address: a.f.vanrootselaar@amsterdamumc.nl. |
| Πηγή: | Resuscitation [Resuscitation] 2026 Feb; Vol. 219, pp. 110943. Date of Electronic Publication: 2025 Dec 24. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier/north-Holland Biomedical Press Country of Publication: Ireland NLM ID: 0332173 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-1570 (Electronic) Linking ISSN: 03009572 NLM ISO Abbreviation: Resuscitation Subsets: MEDLINE |
| Imprint Name(s): | Publication: Limerick : Elsevier/north-Holland Biomedical Press Original Publication: London, Middlesex Pub. Co. |
| Ιατρικοί όροι (MeSH): | Electroencephalography*/methods , Coma*/etiology , Coma*/diagnosis , Coma*/physiopathology , Heart Arrest*/complications , Neural Networks, Computer*, Humans ; Male ; Female ; Middle Aged ; Aged ; Predictive Value of Tests ; Prognosis ; ROC Curve ; Convolutional Neural Networks |
| Περίληψη: | Objective: Our first objective was to characterize the predictive power of electroencephalography (EEG) over time after cardiac arrest (CA) using a continuous, convolutional neural network (CNN). Our second objective was to investigate the performance difference between a 9 and a 4-electrode-model in predicting poor neurological outcome. Methods: We trained a CNN model using hourly 5-min EEG epochs from 366 postanoxic coma patients from the start of recording up to 72 h after CA. Primary outcome was best Cerebral Performance Category (CPC) within 6 months after CA, classified as good (CPC score 1-2) or poor (CPC score 3-5). Prediction was based on the average of predictions over all available hours, both independently and cumulatively. We report (1) model discrimination of poor neurological outcome up to 72 h after CA and (2) model performance difference between a 9 and 4-electrode configuration. Results: The 9-electrode cumulative CNN model reached an area under the receiver operating characteristic curve (AUC) of 82 % and a sensitivity of 71 % at 0 % false-positive rate (FPR) over all available hours. Highest predictive performance was observed before 14 h after CA, peaking at 8 h (AUC = 0.93, sensitivity at 0 % FPR = 0.81). Performance differences over hours were negligible between the 9 and 4-electrode model. Conclusion: The CNN seems valuable for poor neurological outcome prediction in postanoxic coma patients, especially for very early (6-14 h after CA) EEG. A reduced electrode configuration is equally sufficient as the full set. Future studies could explore capturing nuanced temporal dependencies in EEG signals for prognostication. (Copyright © 2025 The Author(s). Published by Elsevier B.V. All rights reserved.) |
| Competing Interests: | Declaration of competing interest The authors have no competing interests to declare. |
| Σχόλια: | Comment in: Resuscitation. 2026 Jun;223:110975. doi: 10.1016/j.resuscitation.2026.110975.. (PMID: 41558586) |
| Contributed Indexing: | Keywords: Brain injury; Cardiac arrest; Continuous outcome prediction; Few electrodes; Postanoxic coma; Prognostication |
| Entry Date(s): | Date Created: 20251226 Date Completed: 20260218 Latest Revision: 20260514 |
| Update Code: | 20260515 |
| DOI: | 10.1016/j.resuscitation.2025.110943 |
| PMID: | 41453650 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1873-1570 |
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| DOI: | 10.1016/j.resuscitation.2025.110943 |