1
|
Kuchenbuch M, Lo Barco T, Chemaly N, Chiron C, Nabbout R. Fifteen years of real-world data on the use of vigabatrin in individuals with infantile epileptic spasms syndrome. Epilepsia 2024; 65:430-444. [PMID: 37872396 DOI: 10.1111/epi.17808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 10/14/2023] [Accepted: 10/19/2023] [Indexed: 10/25/2023]
Abstract
OBJECTIVE This study was undertaken to evaluate our treatment algorithm for infantile epileptic spasms syndrome (IESS) used between 2000 and 2018. We initiated vigabatrin (VGB), and steroids were added if the electroclinical response (spasms and electroencephalogram [EEG]) to VGB was not obtained or incomplete. METHODS Individuals with IESS treated with VGB were recruited from our hospital clinical data warehouse based on electronic health records (EHRs) generated since 2009 and containing relevant keywords. We confirmed the diagnosis of IESS. Clinical, EEG, imaging, and biological data were extracted from the EHRs. We analyzed factors associated with short-term response, time to response, relapse, time to relapse of spasms, and the presence of spasms at last follow-up. RESULTS We collected data from 198 individuals (female: 46.5%, IESS onset: 6 [4.5-10.3] months, follow-up: 4.6 [2.5-7.6] years, median [Q1-Q3]) including 129 (65.2%) with identifiable etiology. VGB was started 17 (5-57.5) days after IESS diagnosis. A total of 113 individuals were responders (57.1% of the cohort), 64 with VGB alone and 38 with VGB further combined with steroids (56.6% and 33.6% of responders, respectively). Among responders, 33 (29%) experienced relapses of spasms, mostly those with later onset of spasms (p = .002) and those who received VGB for <24 months after spasms cessation compared to a longer duration on VGB (45% vs. 12.8%, p = .003). At follow-up, 92 individuals were seizure-free (46.5% of the whole cohort), including 26 free of therapy (13.1%). One hundred twelve individuals (56.6%) were still receiving VGB, with a duration of 3.2 (1.75-5.7) years. SIGNIFICANCE Our sequential protocol introducing VGB then adding steroids is an effective alternative to a combined VGB-steroids approach in IESS. It avoids steroid-related adverse events, as well as those from VGB-steroid combination. According to our data, a period of 7 days seems sufficient to assess VGB response and enables the addition of steroids rapidly if needed. Continuing VGB for 2 years may balance the risk of relapse and treatment-induced adverse events.
Collapse
Affiliation(s)
- Mathieu Kuchenbuch
- Department of Pediatric Neurology, Reference Center for Rare Epilepsies, Hôpital Necker-Enfants Malades, member of ERN EpiCARE, Paris, France
- Laboratory of Translational Research for Neurological Disorders, INSERM MR1163, Imagine Institute, Paris, France
- Service de Pédiatrie, Reference Center for Rare Epilepsies, member of ERN EpiCARE, Université de Lorraine, CHRU-Nancy, Nancy, France
| | - Tommaso Lo Barco
- Department of Pediatric Neurology, Reference Center for Rare Epilepsies, Hôpital Necker-Enfants Malades, member of ERN EpiCARE, Paris, France
| | - Nicole Chemaly
- Department of Pediatric Neurology, Reference Center for Rare Epilepsies, Hôpital Necker-Enfants Malades, member of ERN EpiCARE, Paris, France
- Laboratory of Translational Research for Neurological Disorders, INSERM MR1163, Imagine Institute, Paris, France
| | - Catherine Chiron
- Department of Pediatric Neurology, Reference Center for Rare Epilepsies, Hôpital Necker-Enfants Malades, member of ERN EpiCARE, Paris, France
| | - Rima Nabbout
- Department of Pediatric Neurology, Reference Center for Rare Epilepsies, Hôpital Necker-Enfants Malades, member of ERN EpiCARE, Paris, France
- Laboratory of Translational Research for Neurological Disorders, INSERM MR1163, Imagine Institute, Paris, France
- Université de Paris Cité, Paris, France
| |
Collapse
|
2
|
Brain Complexity Predicts Response to Adrenocorticotropic Hormone in Infantile Epileptic Spasms Syndrome: A Retrospective Study. Neurol Ther 2022; 12:129-144. [PMID: 36327095 PMCID: PMC9837343 DOI: 10.1007/s40120-022-00412-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 10/10/2022] [Indexed: 11/06/2022] Open
Abstract
INTRODUCTION Infantile epileptic spasms syndrome (IESS) is an age-specific and severe epileptic encephalopathy. Although adrenocorticotropic hormone (ACTH) is currently considered the preferred first-line treatment, it is not always effective and may cause side effects. Therefore, seeking a reliable biomarker to predict the treatment response could benefit clinicians in modifying treatment options. METHODS In this study, the complexities of electroencephalogram (EEG) recordings from 15 control subjects and 40 patients with IESS before and after ACTH therapy were retrospectively reviewed using multiscale entropy (MSE). These 40 patients were divided into responders and nonresponders according to their responses to ACTH. RESULTS The EEG complexities of the patients with IESS were significantly lower than those of the healthy controls. A favorable response to treatment showed increasing complexity in the γ band but exhibited a reduction in the β/α-frequency band, and again significantly elevated in the δ band, wherein the latter was prominent in the parieto-occipital regions in particular. Greater reduction in complexity was significantly linked with poorer prognosis in general. Occipital EEG complexities in the γ band revealed optimized performance in recognizing response to the treatment, corresponding to the area under the receiver operating characteristic curves as 0.8621, while complexities of the δ band served as a fair predictor of unfavorable outcomes globally. CONCLUSION We suggest that optimizing frequency-specific complexities over critical brain regions may be a promising strategy to facilitate predicting treatment response in IESS.
Collapse
|
3
|
Fan Y, Chen D, Wang H, Pan Y, Peng X, Liu X, Liu Y. Automatic BASED scoring on scalp EEG in children with infantile spasms using convolutional neural network. Front Mol Biosci 2022; 9:931688. [PMID: 36032671 PMCID: PMC9399419 DOI: 10.3389/fmolb.2022.931688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 07/08/2022] [Indexed: 11/13/2022] Open
Abstract
In recent years, the Burden of Amplitudes and Epileptiform Discharges (BASED) score has been used as a reliable, accurate, and feasible electroencephalogram (EEG) grading scale for infantile spasms. However, manual EEG annotation is, in general, very time-consuming, and BASED scoring is no exception. Convolutional neural networks (CNNs) have proven their great potential in many EEG classification problems. However, very few research studies have focused on the use of CNNs for BASED scoring, a challenging but vital task in the diagnosis and treatment of infantile spasms. This study proposes an automatic BASED scoring framework using EEG and a deep CNN. The feasibility of using CNN for automatic BASED scoring was investigated in 36 patients with infantile spasms by annotating their long-term EEG data with four levels of the BASED score (scores 5, 4, 3, and ≤2). In the validation set, the accuracy was 96.9% by applying a multi-layer CNN to classify the EEG data as a 4-label problem. The extensive experiments have demonstrated that our proposed approach offers high accuracy and, hence, is an important step toward an automatic BASED scoring algorithm. To the best of our knowledge, this is the first attempt to use a CNN to construct a BASED-based scoring model.
Collapse
Affiliation(s)
- Yuying Fan
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Duo Chen
- School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing, China
- *Correspondence: Yunhui Liu, ; Duo Chen,
| | - Hua Wang
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yijie Pan
- Department of Computer Science and Technology, School of Information Science and Technology, Tsinghua University, Beijing, China
- Ningbo Institute of Information Technology Application, CAS, Ningbo, China
| | - Xueping Peng
- Australian AI Institute, FEIT, University of Technology Sydney, Sydney, NSW, Australia
| | - Xueyan Liu
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yunhui Liu
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, China
- *Correspondence: Yunhui Liu, ; Duo Chen,
| |
Collapse
|
4
|
Romero Milà B, Remakanthakurup Sindhu K, Mytinger JR, Shrey DW, Lopour BA. EEG biomarkers for the diagnosis and treatment of infantile spasms. Front Neurol 2022; 13:960454. [PMID: 35968272 PMCID: PMC9366674 DOI: 10.3389/fneur.2022.960454] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Early diagnosis and treatment are critical for young children with infantile spasms (IS), as this maximizes the possibility of the best possible child-specific outcome. However, there are major barriers to achieving this, including high rates of misdiagnosis or failure to recognize the seizures, medication failure, and relapse. There are currently no validated tools to aid clinicians in assessing objective diagnostic criteria, predicting or measuring medication response, or predicting the likelihood of relapse. However, the pivotal role of EEG in the clinical management of IS has prompted many recent studies of potential EEG biomarkers of the disease. These include both visual EEG biomarkers based on human visual interpretation of the EEG and computational EEG biomarkers in which computers calculate quantitative features of the EEG. Here, we review the literature on both types of biomarkers, organized based on the application (diagnosis, treatment response, prediction, etc.). Visual biomarkers include the assessment of hypsarrhythmia, epileptiform discharges, fast oscillations, and the Burden of AmplitudeS and Epileptiform Discharges (BASED) score. Computational markers include EEG amplitude and power spectrum, entropy, functional connectivity, high frequency oscillations (HFOs), long-range temporal correlations, and phase-amplitude coupling. We also introduce each of the computational measures and provide representative examples. Finally, we highlight remaining gaps in the literature, describe practical guidelines for future biomarker discovery and validation studies, and discuss remaining roadblocks to clinical implementation, with the goal of facilitating future work in this critical area.
Collapse
Affiliation(s)
- Blanca Romero Milà
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- Department of Electronics and Biomedical Engineering, Universitat de Barcelona, Barcelona, Spain
| | | | - John R. Mytinger
- Division of Pediatric Neurology, Department of Pediatrics, Nationwide Children's Hospital, The Ohio State University, Columbus, OH, United States
| | - Daniel W. Shrey
- Division of Neurology, Children's Hospital Orange County, Orange, CA, United States
- Department of Pediatrics, University of California, Irvine, Irvine, CA, United States
| | - Beth A. Lopour
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- *Correspondence: Beth A. Lopour
| |
Collapse
|
5
|
Liu X, Chen J, Wan L, Li Z, Liang Y, Yan H, Zhu G, Zhang B, Yang G. Interrater and Intrarater Agreement of Epileptic Encephalopathy Among Electroencephalographers for Children with Infantile Spasms Using the Burden of Amplitudes and Epileptiform Discharges (BASED) EEG Grading Scale: Study Design and Statistical Considerations. Neurol Ther 2022; 11:1427-1437. [PMID: 35809161 PMCID: PMC9338191 DOI: 10.1007/s40120-022-00382-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 06/17/2022] [Indexed: 11/26/2022] Open
Abstract
Background Infantile spasms are a serious epilepsy syndrome with a poor prognosis. Electroencephalography (EEG) has been a key component in the prognosis and treatment of infantile spasms. This multi-center study protocol is developed to investigate interrater and intrarater agreement of an electroencephalographic grading scale—the Burden of Amplitudes and Epileptiform Discharges (BASED) score among electroencephalographers. Methods Thirty children, aged 0–2 years, with infantile spasms who were hospitalized in the Chinese PLA General Hospital will be recruited into this study by stratified sampling. Seven electroencephalographers from different Class A tertiary hospitals will select a 5-min epoch with the most severe epileptiform discharge, score the EEG reports, and provide the basis for the scoring. The 420 (30 × 7 × 2) scoring results provided by electroencephalographers in two rounds can be analyzed statistically using weighted kappa (weighted \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) statstic, Fless’ kappa (Fless’ \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) statistic, and intraclass correlation coefficient (ICC) to calculate the interrater and intrarater agreement. Discussion We will recruit more electroencephalographers than were included in previous studies to assess the interrater and intrarater agreement in the selection of 5-min EEG epochs, the BASED scores, and the basis for scoring. If the BASED score has an adequate interrater and intrarater agreement, the score will have more significance for guiding the clinical management and for predicting the prognosis of patients with infantile spasms. Supplementary Information The online version contains supplementary material available at 10.1007/s40120-022-00382-4.
Collapse
Affiliation(s)
- Xinting Liu
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Jian Chen
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Lin Wan
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Zhichao Li
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Yan Liang
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Huimin Yan
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Guangyu Zhu
- Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI, USA
| | - Bo Zhang
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
- Biostatistics and Research Design Center, Institutional Centers for Clinical and Translational Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Guang Yang
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China.
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China.
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
| |
Collapse
|