1
|
Tao T, Lu S, Hu N, Xu D, Xu C, Li F, Wang Q, Peng Y. Prognosis of comatose patients with reduced EEG montage by combining quantitative EEG features in various domains. Front Neurosci 2023; 17:1302318. [PMID: 38144206 PMCID: PMC10748426 DOI: 10.3389/fnins.2023.1302318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 11/20/2023] [Indexed: 12/26/2023] Open
Abstract
Objective As the frontoparietal network underlies recovery from coma, a limited frontoparietal montage was used, and the prognostic values of EEG features for comatose patients were assessed. Methods Collected with a limited frontoparietal EEG montage, continuous EEG recordings of 81 comatose patients in ICU were used retrospectively. By the 60-day Glasgow outcome scale (GOS), the patients were dichotomized into favorable and unfavorable outcome groups. Temporal-, frequency-, and spatial-domain features were automatically extracted for comparison. Partial correlation analysis was applied to eliminate redundant factors, and multiple correspondence analysis was used to explore discrimination between groups. Prognostic characteristics were calculated to assess the performance of EEG feature-based predictors established by logistic regression. Analyses were performed on all-patients group, strokes subgroup, and traumatic brain injury (TBI) subgroup. Results By analysis of all patients, raised burst suppression ratio (BSR), suppressed root mean square (RMS), raised power ratio of β to α rhythm (β/α), and suppressed phase-lag index between F3 and P4 (PLI [F3, P4]) were associated with unfavorable outcome, and yielded AUC of 0.790, 0.811, 0.722, and 0.844, respectively. For the strokes subgroup, the significant variables were BSR, RMS, θ/total, θ/δ, and PLI (F3, P4), while for the TBI subgroup, only PLI (F3, P4) was significant. BSR combined with PLI (F3, P4) gave the best predictor by cross-validation analysis in the all-patients group (AUC = 0.889, 95% CI: 0.819-0.960). Conclusion Features extracted from limited frontoparietal montage EEG served as valuable coma prognostic tools, where PLI (F3, P4) was always significant. Combining PLI (F3, P4) with features in other domains may achieve better performance. Significance A limited-montage EEG coupled with an automated algorithm is valuable for coma prognosis.
Collapse
Affiliation(s)
- Tao Tao
- Intensive Care Unit, The First People’s Hospital of Kunshan, Kunshan Affiliated Hospital of Jiangsu University, Kunshan, Jiangsu, China
| | - Shiqi Lu
- Emergency Department, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Nan Hu
- School of Electronics and Information Engineering, Soochow University, Suzhou, Jiangsu, China
| | - Dongyang Xu
- Center for Intelligent Acoustics and Signal Processing, Huzhou Institute of Zhejiang University, Huzhou, China
| | - Chenyang Xu
- Intensive Care Unit, The First People’s Hospital of Kunshan, Kunshan Affiliated Hospital of Jiangsu University, Kunshan, Jiangsu, China
| | - Fajun Li
- Intensive Care Unit, The First People’s Hospital of Kunshan, Kunshan Affiliated Hospital of Jiangsu University, Kunshan, Jiangsu, China
| | - Qin Wang
- Intensive Care Unit, The First People’s Hospital of Kunshan, Kunshan Affiliated Hospital of Jiangsu University, Kunshan, Jiangsu, China
| | - Yuan Peng
- Intensive Care Unit, The First People’s Hospital of Kunshan, Kunshan Affiliated Hospital of Jiangsu University, Kunshan, Jiangsu, China
| |
Collapse
|
2
|
Ding X, Shen Z. Electroencephalography Prediction of Neurological Outcomes After Hypoxic-Ischemic Brain Injury: A Systematic Review and Meta-Analysis. Clin EEG Neurosci 2023:15500594231211105. [PMID: 37941351 DOI: 10.1177/15500594231211105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Background. Predicting neurological outcomes after hypoxic-ischemic brain injury (HIBI) is difficult. Objective. Electroencephalography (EEG) can identify acute and subacute brain abnormalities after hypoxic brain injury and predict HIBI recovery. We examined EEG's ability to predict neurologic outcomes following HIBI. Method. A PRISMA-compliant search was conducted in the Medline, Embase, Cochrane, and Central databases until January 2023. EEG-predicted neurological outcomes in HIBI patients were selected from relevant perspective and retrospective cohort studies. RevMan did meta-analysis, while QDAS2 assessed research quality. Results. Eleven studies with 3761 HIBI patients met the inclusion and exclusion criteria. We aggregated study-level estimates of sensitivity and specificity for EEG patterns determined a priori using random effect bivariate and univariate meta-analysis when appropriate. Positive indicators and anatomical area heterogeneity impacted prognosis accuracy. Funnel plots analyzed publication bias. Significant heterogeneity of greater than 80% was among the included studies with P < 0.001. The area under the curve was 0.94, the threshold effect was P < 0.001, and the sensitivity and specificity, with 95% confidence intervals, were 0.91 (0.84-0.99) and 0.86 (0.75-0.97). EEG detects status epilepticus and burst suppression with good sensitivity, specificity, and little probability of false-negative impairment result attribution. Study quality varied by domain, but patient flow and timing were well conducted in all. Conclusion. EEG can predict the outcome of HIBI with good prognostic accuracy, but more standardized cross-study protocols and descriptions of EEG patterns are needed to better evaluate its prognostic use for patients with HIBI.
Collapse
Affiliation(s)
- Xina Ding
- Department of Brain Function, Hospital of Nantong University, No. 20 Xisi Road, Chongchuan District, Nantong City, Jiangsu Province, 226001, China
| | - Zhixiao Shen
- Department of Brain Function, Hospital of Nantong University, No. 20 Xisi Road, Chongchuan District, Nantong City, Jiangsu Province, 226001, China
| |
Collapse
|
3
|
Elmashala A, Busl KM, Maciel CB. Will shifting the lens let us see more clearly when prognosticating after cardiac arrest, or do we need new glasses? Resuscitation 2023; 182:109667. [PMID: 36565947 DOI: 10.1016/j.resuscitation.2022.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 12/11/2022] [Indexed: 12/24/2022]
Affiliation(s)
- Amjad Elmashala
- Department of Neurology, Division of Neurocritical Care, University of Florida College of Medicine, Gainesville, FL 32611, USA
| | - Katharina M Busl
- Department of Neurology, Division of Neurocritical Care, University of Florida College of Medicine, Gainesville, FL 32611, USA; Department of Neurosurgery, University of Florida College of Medicine, Gainesville, FL 32611, USA
| | - Carolina B Maciel
- Department of Neurology, Division of Neurocritical Care, University of Florida College of Medicine, Gainesville, FL 32611, USA; Department of Neurosurgery, University of Florida College of Medicine, Gainesville, FL 32611, USA; Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Neurology, University of Utah, Salt Lake City, UT 84132, USA.
| |
Collapse
|
4
|
Application of a standardized EEG pattern classification in the assessment of neurological prognosis after cardiac arrest: A retrospective analysis. Resuscitation 2021; 165:38-44. [PMID: 34119554 DOI: 10.1016/j.resuscitation.2021.05.037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 05/15/2021] [Accepted: 05/30/2021] [Indexed: 11/22/2022]
Abstract
INTRODUCTION Electroencephalogram (EEG) is used in the neurological prognostication after cardiac arrest. "Highly malignant" EEG patterns classified according to Westhall have a high specificity for poor neurological outcome when applied within protocols of recent studies. However, their predictive performance when applied in everyday clinical practice has not been investigated. We studied the prognostic accuracy and the interrater agreement when standardized EEG patterns were analysed and compared to neurological outcome in a patient cohort at a tertiary centre not involved in the original study of the standardized EEG pattern classification. METHODS Comatose patients treated for out-of-hospital cardiac arrest were included. Poor outcome was defined as Cerebral Performance Category 3-5. Two senior consultants and one resident in clinical neurophysiology, blinded to clinical data and outcome, independently reviewed their EEG registrations and categorised the pattern as "highly malignant", "malignant" or "benign". These categories were compared to neurological outcome at hospital discharge. Interrater agreement was assessed using Cohen's Kappa. RESULTS In total, 62 patients were included. The median (IQR) time to EEG was 59 (42-91) h after return of spontaneous circulation. Poor outcome was found in 52 (84%) patients. In 21 patients at least one of the raters considered the EEG to contain a "highly malignant" pattern, all with poor outcome (42% sensitivity, 100% specificity). The interrater agreement varied from kappa 0.62 to 0.29. CONCLUSION "Highly malignant" patterns predict poor neurological outcome with a high specificity in everyday practice. However, interrater agreement may vary substantially even between experienced EEG interpreters.
Collapse
|
5
|
Touchard C, Cartailler J, Vellieux G, de Montmollin E, Jaquet P, Wanono R, Reuter J, Para M, Bouadma L, Timsit JF, d'Ortho MP, Kubis N, Rouvel Tallec A, Sonneville R. Simplified frontal EEG in adults under veno-arterial extracorporeal membrane oxygenation. Ann Intensive Care 2021; 11:76. [PMID: 33987690 PMCID: PMC8119573 DOI: 10.1186/s13613-021-00854-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 04/12/2021] [Indexed: 12/04/2022] Open
Abstract
Background EEG-based prognostication studies in intensive care units often rely on a standard 21-electrode montage (stdEEG) requiring substantial human, technical, and financial resources. We here evaluate whether a simplified 4-frontal electrode montage (4-frontEEG) can detect EEG patterns associated with poor outcomes in adult patients under veno-arterial extracorporeal membrane oxygenation (VA-ECMO). Methods We conducted a reanalysis of EEG data from a prospective cohort on 118 adult patients under VA-ECMO, in whom EEG was performed on admission to intensive care. EEG patterns of interest included background rhythm, discontinuity, reactivity, and the Synek’s score. They were all reassessed by an intensivist on a 4-frontEEG montage, whose analysis was then compared to an expert’s interpretation made on stdEEG recordings. The main outcome measure was the degree of correlation between 4-frontEEG and stdEEG montages to identify EEG patterns of interest. The performance of the Synek scores calculated on 4-frontEEG and stdEEG montage to predict outcomes (i.e., 28-day mortality and 90-day Rankin score \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\ge {4}}$$\end{document}≥4) was investigated in a secondary exploratory analysis. Results The detection of EEG patterns using 4-frontEEG was statistically similar to that of stdEEG for background rhythm (Spearman rank test, ρ = 0.66, p < 0.001), discontinuity (Cohen’s kappa, \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\kappa$$\end{document}κ = 0.955), reactivity (\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\kappa$$\end{document}κ = 0.739) and the Synek’s score (ρ = 0.794, p < 0.001). Using the Synek classification, we found similar performances between 4-frontEEG and stdEEG montages in predicting 28-day mortality (AUC 4-frontEEG 0.71, AUC stdEEG 0.68) and for 90-day poor neurologic outcome (AUC 4-frontEEG 0.71, AUC stdEEG 0.66). An exploratory analysis confirmed that the Synek scores determined by 4 or 21 electrodes were independently associated with 28-day mortality and poor 90-day functional outcome. Conclusion In adult patients under VA-ECMO, a simplified 4-frontal electrode EEG montage interpreted by an intensivist, detected common EEG patterns associated with poor outcomes, with a performance similar to that of a standard EEG montage interpreted by expert neurophysiologists. This simplified montage could be implemented as part of a multimodal evaluation for bedside prognostication. Supplementary Information The online version contains supplementary material available at 10.1186/s13613-021-00854-0.
Collapse
Affiliation(s)
- Cyril Touchard
- Department of Anesthesiology and Intensive Care, APHP, Lariboisière-Saint Louis Hospitals, 75010, Paris, France
| | - Jérôme Cartailler
- Department of Anesthesiology and Intensive Care, APHP, Lariboisière-Saint Louis Hospitals, 75010, Paris, France.,Inserm, UMRS-942, Paris Diderot University, Paris, France
| | - Geoffroy Vellieux
- Université de Paris, NeuroDiderot, Inserm, 75019, Paris, France.,Department of Clinical Physiology, AP-HP, Bichat-Claude Bernard Hospital, 75018, Paris, France
| | - Etienne de Montmollin
- Department of Intensive Care Medicine and Infectious Diseases, AP-HP, Bichat-Claude Bernard Hospital, 75018, Paris, France
| | - Pierre Jaquet
- Department of Intensive Care Medicine and Infectious Diseases, AP-HP, Bichat-Claude Bernard Hospital, 75018, Paris, France
| | - Ruben Wanono
- Université de Paris, NeuroDiderot, Inserm, 75019, Paris, France.,Department of Clinical Physiology, AP-HP, Bichat-Claude Bernard Hospital, 75018, Paris, France
| | - Jean Reuter
- Department of Intensive Care Medicine and Infectious Diseases, AP-HP, Bichat-Claude Bernard Hospital, 75018, Paris, France
| | - Marylou Para
- Department of Cardiac Surgery, Bichat-Claude Bernard Hospital, 75018, Paris, France
| | - Lila Bouadma
- Department of Intensive Care Medicine and Infectious Diseases, AP-HP, Bichat-Claude Bernard Hospital, 75018, Paris, France
| | - Jean-François Timsit
- Department of Intensive Care Medicine and Infectious Diseases, AP-HP, Bichat-Claude Bernard Hospital, 75018, Paris, France
| | - Marie-Pia d'Ortho
- Department of Clinical Physiology, AP-HP, Bichat-Claude Bernard Hospital, 75018, Paris, France
| | - Nathalie Kubis
- Laboratory for Vascular Translational Science, INSERM UMR1148, Team 6, Université de Paris, 75018, Paris, France.,Department of Clinical Physiology, APHP, Lariboisière - Saint Louis hospitals, DMU DREAM, 75010, Paris, France
| | - Anny Rouvel Tallec
- Université de Paris, NeuroDiderot, Inserm, 75019, Paris, France.,Department of Clinical Physiology, AP-HP, Bichat-Claude Bernard Hospital, 75018, Paris, France
| | - Romain Sonneville
- Laboratory for Vascular Translational Science, INSERM UMR1148, Team 6, Université de Paris, 75018, Paris, France. .,Department of Intensive Care Medicine and Infectious Diseases, AP-HP, Bichat-Claude Bernard Hospital, 75018, Paris, France.
| | | |
Collapse
|