Epilepsia最新文献_第6页

SzCORE: Seizure Community Open‐Source Research Evaluation framework for the validation of electroencephalography‐based automated seizure detection algorithms SzCORE：癫痫发作社区开源研究评估框架，用于验证基于脑电图的癫痫发作自动检测算法

IF 5.6 1区医学 Q1 CLINICAL NEUROLOGY

Epilepsia

Pub Date : 2024-09-18 DOI: 10.1111/epi.18113

Jonathan Dan, Una Pale, Alireza Amirshahi, William Cappelletti, Thorir Mar Ingolfsson, Xiaying Wang, Andrea Cossettini, Adriano Bernini, Luca Benini, Sándor Beniczky, David Atienza, Philippe Ryvlin

The need for high‐quality automated seizure detection algorithms based on electroencephalography (EEG) becomes ever more pressing with the increasing use of ambulatory and long‐term EEG monitoring. Heterogeneity in validation methods of these algorithms influences the reported results and makes comprehensive evaluation and comparison challenging. This heterogeneity concerns in particular the choice of datasets, evaluation methodologies, and performance metrics. In this paper, we propose a unified framework designed to establish standardization in the validation of EEG‐based seizure detection algorithms. Based on existing guidelines and recommendations, the framework introduces a set of recommendations and standards related to datasets, file formats, EEG data input content, seizure annotation input and output, cross‐validation strategies, and performance metrics. We also propose the EEG 10–20 seizure detection benchmark, a machine‐learning benchmark based on public datasets converted to a standardized format. This benchmark defines the machine‐learning task as well as reporting metrics. We illustrate the use of the benchmark by evaluating a set of existing seizure detection algorithms. The SzCORE (Seizure Community Open‐Source Research Evaluation) framework and benchmark are made publicly available along with an open‐source software library to facilitate research use, while enabling rigorous evaluation of the clinical significance of the algorithms, fostering a collective effort to more optimally detect seizures to improve the lives of people with epilepsy.

随着非卧床和长期脑电图（EEG）监测应用的不断增加，对基于脑电图（EEG）的高质量癫痫发作自动检测算法的需求日益迫切。这些算法验证方法的不一致性影响了报告结果，并使全面评估和比较具有挑战性。这种异质性尤其涉及数据集、评估方法和性能指标的选择。在本文中，我们提出了一个统一的框架，旨在建立基于脑电图的癫痫发作检测算法验证的标准化。在现有指南和建议的基础上，该框架引入了一套与数据集、文件格式、脑电图数据输入内容、癫痫发作注释输入和输出、交叉验证策略和性能指标相关的建议和标准。我们还提出了 EEG 10-20 癫痫发作检测基准，这是一个基于转换为标准化格式的公共数据集的机器学习基准。该基准定义了机器学习任务以及报告指标。我们通过评估一组现有的癫痫发作检测算法来说明基准的使用。SzCORE（癫痫发作社区开源研究评估）框架和基准与一个开源软件库一起公开发布，以方便研究使用，同时对算法的临床意义进行严格评估，促进集体努力，以更优化的方式检测癫痫发作，改善癫痫患者的生活。

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引用次数: 0

Patients carrying pathogenic SCN8A variants with loss‐ and gain‐of‐function effects can be classified into five subgroups exhibiting varying developmental and epileptic components of encephalopathy 携带具有功能缺失和功能增益效应的致病性 SCN8A 变体的患者可分为五个亚组，表现出不同的脑病发育和癫痫成分

IF 5.6 1区医学 Q1 CLINICAL NEUROLOGY

Epilepsia

Pub Date : 2024-09-18 DOI: 10.1111/epi.18118

Joshua B. Hack, Joseph C. Watkins, John M. Schreiber, Michael F. Hammer

ObjectivePhenotypic heterogeneity presents challenges in providing clinical care to patients with pathogenic SCN8A variants, which underly a wide disease spectrum ranging from neurodevelopmental delays without seizures to a continuum of mild to severe developmental and epileptic encephalopathies (DEEs). An important unanswered question is whether there are clinically important subgroups within this wide spectrum. Using both supervised and unsupervised machine learning (ML) approaches, we previously found statistical support for two and three subgroups associated with loss‐ and gain‐ of‐ function vari‐ants, respectively. Here, we test the hypothesis that the unsupervised subgroups (U1–U3) are distinguished by differential contributions of developmental and epileptic components.MethodsWe predicted that patients in the U1 and U2 subgroups would differ in timing of developmental delay and seizure onset, with earlier and concurrent onset of both features for the U3 subgroup. Standard statistical procedures were used to test these predictions, as well as to investigate clinically relevant associations among all five subgroups.ResultsTwo‐population proportion and Kruskal–Wallis tests supported the hypothesis of a reversed order of developmental delay and seizure onset for patients in U1 and U2, and nearly synchronous developmental delay/seizure onset for the U3 (termed DEE) subgroup. Association testing identified subgroup variation in treatment response, frequency of initial seizure type, and comorbidities, as well as different median ages of developmental delay onset for all five subgroups.SignificanceUnsupervised ML approaches discern differential developmental and epileptic components among patients with SCN8A‐related epilepsy. Patients in U1 (termed developmental encephalopathy) typically gain seizure control yet rarely experience improvements in development, whereas those in U2 (termed epileptic encephalopathy) have fewer if any developmental impairments despite difficulty in achieving seizure control. This understanding improves prognosis and clinical management and provides a framework to discover mechanisms underlying variability in clinical outcome of patients with SCN8A‐related disorders.

目的表型异质性给致病性 SCN8A 变体患者的临床治疗带来了挑战，这些变体导致了广泛的疾病谱，从无癫痫发作的神经发育迟缓到从轻度到重度的发育性和癫痫性脑病（DEEs）。一个尚未解答的重要问题是，在这一广泛的疾病谱中是否存在临床上重要的亚群。利用监督和无监督机器学习（ML）方法，我们之前发现分别有两个和三个亚组与功能损失和功能增益变异相关。我们预测 U1 和 U2 亚组的患者在发育迟缓和癫痫发作的时间上会有所不同，而 U3 亚组的这两个特征会更早且同时出现。结果两组人口比例检验和 Kruskal-Wallis 检验支持以下假设：U1 和 U2 组患者的发育迟缓和癫痫发作顺序相反，而 U3（称为 DEE）亚组患者的发育迟缓/癫痫发作几乎同步。关联测试确定了治疗反应、初始发作类型频率和合并症方面的亚组差异，以及所有五个亚组发育迟缓发病年龄的中位数差异。U1（称为发育性脑病）患者通常能控制癫痫发作，但发育很少得到改善，而U2（称为癫痫性脑病）患者尽管难以控制癫痫发作，但发育障碍较少。这种认识有助于改善预后和临床管理，并为发现 SCN8A 相关疾病患者临床结局差异的内在机制提供了一个框架。

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引用次数: 0

Effects of antiseizure medication withdrawal during the first trimester of pregnancy on seizure control and offspring outcomes. 妊娠头三个月停用抗癫痫药物对癫痫发作控制和后代结局的影响。

IF 6.6 1区医学 Q1 CLINICAL NEUROLOGY

Epilepsia

Pub Date : 2024-09-17 DOI: 10.1111/epi.18125

Yutong Fu, Fanfan Shi, Leihao Sha, Ximeng Yang, Rui Li, Lei Chen

Objective: To explore seizure control and offspring outcomes associated with antiseizure medication (ASM) withdrawal during the first trimester of pregnancy.

Methods: Based on a prospective multicenter study in China, pregnancies followed up between 2009 and 2023 at the neurology outpatient clinic of 50 hospitals were included in this study. Information on demographics, epileptic characteristics, treatment during pregnancy, and offspring outcomes was collected. Pregnancies were categorized into an ASM withdrawal group and an ASM continuation group. Balance tests and univariate log-binomial regression analysis were conducted to identify imbalanced factors between groups and potential risk factors for seizure deterioration during pregnancy. Multivariate log-binomial regression was then used to estimate the adjusted effects of ASM withdrawal on seizure deterioration during pregnancy and fetal outcomes. In addition, exploratory subgroup analysis was conducted to identify high-risk patients who should avoid ASM withdrawal.

Results: Of the 695 pregnancies enrolled, 14.2% withdrew ASMs in the first trimester of pregnancy. ASM withdrawal during this period was associated with a risk of seizure deterioration during pregnancy (adjusted risk ratio [aRR] 1.405, 95% confidence interval [CI] 1.009-1.876). Subgroup analysis revealed a significant risk of seizure deterioration in pregnancies with seizures in 9 months (aRR 1.590, 95% CI 1.079-2.344). After adjusting the folic acid dose, no evidence of protective effects on fetus after ASM withdrawal was observed compared to patients with continued treatment, whereas seizure deterioration during pregnancy increased the risk of fetal death (aRR 3.577, 95% CI 1.086-11.651).

Significance: ASM withdrawal in the first trimester of pregnancy did not show a protective effect on fetal outcomes but rather resulted in increased seizure frequency during pregnancy. However, this finding requires a larger sample for validation. Furthermore, seizure deterioration during pregnancy was associated with an increased risk of fetal death.

目的探讨与妊娠头三个月停用抗癫痫药物（ASM）相关的癫痫发作控制和后代结局：本研究基于一项中国前瞻性多中心研究，纳入了 2009 年至 2023 年期间在 50 家医院神经科门诊随访的孕妇。研究收集了有关人口统计学、癫痫特征、孕期治疗和后代结局的信息。妊娠分为停用 ASM 组和继续 ASM 组。进行平衡测试和单变量对数二项式回归分析，以确定各组之间的不平衡因素以及孕期癫痫发作恶化的潜在风险因素。然后使用多变量对数二叉回归估算停用 ASM 对孕期癫痫发作恶化和胎儿结局的调整效应。此外，还进行了探索性亚组分析，以确定应避免停用 ASM 的高风险患者：结果：在入选的 695 例孕妇中，14.2% 的孕妇在妊娠头三个月停用了 ASM。在此期间停用 ASM 与孕期癫痫发作恶化的风险有关（调整风险比 [aRR] 1.405，95% 置信区间 [CI] 1.009-1.876）。亚组分析显示，妊娠 9 个月内有癫痫发作的孕妇有显著的癫痫发作恶化风险（aRR 1.590，95% CI 1.079-2.344）。调整叶酸剂量后，与继续接受治疗的患者相比，没有观察到停用 ASM 后对胎儿有保护作用的证据，而孕期癫痫发作恶化会增加胎儿死亡的风险（aRR 3.577，95% CI 1.086-11.651）：在妊娠头三个月停用 ASM 对胎儿的预后并无保护作用，反而会导致妊娠期癫痫发作频率增加。然而，这一发现需要更多的样本来验证。此外，孕期癫痫发作恶化与胎儿死亡风险增加有关。

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引用次数: 0

Unveiling the disease progression in developmental and epileptic encephalopathies: Insights from EEG and neuropsychology 揭示发育性和癫痫性脑病的疾病进展：脑电图和神经心理学的启示

IF 5.6 1区医学 Q1 CLINICAL NEUROLOGY

Epilepsia

Pub Date : 2024-09-17 DOI: 10.1111/epi.18127

Paolo Surdi, Marina Trivisano, Angela De Dominicis, Mattia Mercier, Ludovica Maria Piscitello, Giusy Carfì Pavia, Costanza Calabrese, Simona Cappelletti, Cinzia Correale, Luigi Mazzone, Federico Vigevano, Nicola Specchio

ObjectiveDevelopmental and epileptic encephalopathies (DEEs) are neurological disorders characterized by developmental impairment and epilepsy. Our study aims to assess disease progression by comparing clinical findings, electroencephalography (EEG), and neuropsychological data from seizure onset to the last follow‐up evaluation.MethodsWe retrospectively reviewed patients with genetic DEEs who were followed‐up at the epilepsy unit of Bambino Gesù Children's Hospital, Rome. We collected information regarding gender, family history, genetic variant, age at onset and at last follow‐up, neurological examination, type of seizure, drug resistance, occurrence of status epilepticus, and movement and cognitive and behavioral disorders. We compared EEG background activity, epileptiform abnormalities, and cognitive functions between seizure onset and the last follow‐up evaluation using the McNemar‐Bowker test (α = 5%).ResultsA total of 160 patients (94 female) were included. Genetic analysis revealed a spectrum of pathogenic variants, with SCN1A being the most prevalent (25%). The median age at seizure onset and at the last follow‐up was 0.37 (interquartile range [IQR]: 0.09–0.75) and 8.54 years (IQR: 4.32–14.55), respectively. We documented a statistically significant difference in EEG background activity (p = .017) and cognitive impairment (p = .01) from seizure onset to the last follow‐up evaluation. No significant differences were detected for epileptiform abnormalities (p = .2). In addition, high prevalence rates were observed for drug resistance (81.9%), movement disorders (60.6%), behavioral and autism spectrum disorders (45%), neurological deficits (31.3%), and occurrence of status epilepticus (23.1%).SignificanceOur study provides evidence that a clinical progression may appear in genetic DEEs, manifesting as development or worsening of cognitive impairment and disruption of EEG background activity. These results highlight the challenging clinical course and the importance of early intervention and personalized care in the management of patients with DEEs.

目的发育性和癫痫性脑病（DEEs）是一种以发育障碍和癫痫为特征的神经系统疾病。我们的研究旨在通过比较从癫痫发作开始到最后一次随访评估期间的临床结果、脑电图（EEG）和神经心理学数据来评估疾病的进展。我们收集了有关性别、家族史、基因变异、发病年龄和最后一次随访时的年龄、神经系统检查、癫痫发作类型、耐药性、癫痫状态的发生以及运动、认知和行为障碍等方面的信息。我们使用 McNemar-Bowker 检验（α = 5%）比较了发作开始与最后一次随访评估之间的脑电图背景活动、癫痫样异常和认知功能。基因分析显示了一系列致病变异，其中以SCN1A最为常见（25%）。癫痫发作时和最后一次随访时的中位年龄分别为 0.37 岁（四分位间距 [IQR]：0.09-0.75）和 8.54 岁（IQR：4.32-14.55）。我们发现，从癫痫发作到最后一次随访评估期间，脑电图背景活动（p = .017）和认知障碍（p = .01）的差异具有统计学意义。在癫痫样异常方面未发现明显差异（p = .2）。此外，还观察到耐药性（81.9%）、运动障碍（60.6%）、行为障碍和自闭症谱系障碍（45%）、神经功能缺损（31.3%）和癫痫状态（23.1%）的高患病率。这些结果突显了具有挑战性的临床过程，以及早期干预和个性化护理在DEEs患者管理中的重要性。

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引用次数: 0

Statistical characteristics of large‐scale objective tonic–clonic seizure records from medical smartwatches used in daily life 来自日常生活中使用的医疗智能手表的大规模客观强直阵挛发作记录的统计特征

IF 5.6 1区医学 Q1 CLINICAL NEUROLOGY

Epilepsia

Pub Date : 2024-09-17 DOI: 10.1111/epi.18109

Boyu Zhang, Weixuan V. Chen, Giulia Regalia, Daniel M. Goldenholz, Rosalind W. Picard

ObjectiveThis study aimed to assess whether population‐level patterns in seizure occurrence previously observed in self‐reported diaries, medical records, and electroencephalographic recordings were also present in tonic–clonic seizure (TCS) diaries produced via the combined input of a US Food and Drug Administration‐cleared wristband with an artificial intelligence detection algorithm and patient self‐reports. We also investigated the characteristics of patient interactions with wearable seizure alerts.MethodsWe analyzed wristband data from patients with TCSs who had at least three reported TCSs over a minimum of 90 days. We quantified TCS frequency and cycles, and the relationship between the mean and variability of monthly TCS counts. We also assessed interaction metrics such as false alarm dismissal and seizure confirmation rates.ResultsApplying strict criteria for usable data, we reviewed 137 490 TCSs from 3012 patients, with a median length of TCS alert records of 445 days (range = 90–1806). Analyses showed consistency between prior diary studies and the present data concerning (1) the distribution of monthly TCS frequency (median = 3.1, range = .08–26); (2) the linear relationship (slope = .79, R2 = .83) between the logarithm of the mean and the logarithm of the SD of monthly TCS frequency (L‐relationship); and (iii) the prevalence of multiple coexisting seizure cycles, including circadian (84.0%), weekly (24.6%), and long‐term cycles (31.1%).SignificanceKey population‐level patterns in seizure occurrence are recapitulated in wrist‐worn device recordings, supporting their validity for tracking TCS burden. Compared to other approaches, wearables can provide noninvasive, objective, long‐term data, revealing cycles in seizure risk. However, improved patient engagement with wristband alerts and further validation of detection accuracy in ambulatory settings are needed. Together, these findings suggest that data from smart wristbands may be used to derive features of TCS records and, ultimately, facilitate remote monitoring and the development of personalized forecasting tools for TCS management. Our findings may not generalize to other types of seizures.

目的本研究旨在评估以前在自我报告日记、医疗记录和脑电图记录中观察到的人群水平的癫痫发作模式是否也存在于强直阵挛发作（TCS）日记中，该日记是通过美国食品药品管理局批准的腕带与人工智能检测算法和患者自我报告联合输入而生成的。我们还调查了患者与可穿戴癫痫发作警报互动的特点。方法我们分析了至少在 90 天内报告过三次 TCS 的 TCS 患者的腕带数据。我们量化了 TCS 频率和周期，以及每月 TCS 计数的平均值和变异性之间的关系。我们还评估了交互指标，如误报排除率和发作确认率。结果应用严格的可用数据标准，我们审查了来自 3012 名患者的 137 490 次 TCS，TCS 警报记录的中位长度为 445 天（范围 = 90-1806）。分析表明，先前的日记研究与本数据在以下方面具有一致性：(1) 每月 TCS 频率的分布（中位数 = 3.1，范围 = .08-26）；(2) 每月 TCS 频率的平均值对数与 SD 对数之间的线性关系（斜率 = .79，R2 = .83）（L-关系）；(iii) 多种并存发作周期的普遍性，包括昼夜节律（84.意义腕戴式设备记录再现了癫痫发作的主要人群水平模式，支持其追踪 TCS 负担的有效性。与其他方法相比，可穿戴设备可以提供无创、客观、长期的数据，揭示癫痫发作风险的周期。不过，还需要提高患者对腕带警报的参与度，并进一步验证在非卧床环境中的检测准确性。总之，这些研究结果表明，智能腕带的数据可用于推导 TCS 记录的特征，并最终促进远程监控和 TCS 管理个性化预测工具的开发。我们的研究结果可能不适用于其他类型的癫痫发作。

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引用次数: 0

Role of comorbidities in epilepsy surgery outcomes of older adults. 合并症对老年人癫痫手术疗效的影响。

IF 6.6 1区医学 Q1 CLINICAL NEUROLOGY

Epilepsia

Pub Date : 2024-09-16 DOI: 10.1111/epi.18103

Carolyn Tsai, Sara Taylor, Nicolas Thompson, Deborah Vegh, William Bingaman, Lara Jehi, Vineet Punia

We lack knowledge about prognostic factors of resective epilepsy surgery (RES) in older adults (≥60 years), especially the role of comorbidities, which are a major consideration in managing the care of people with epilepsy (PWE). We analyzed a single-center cohort of 94 older adults (median age = 63.5 years, 52% females) who underwent RES between 2000 and 2021 with at least 6 months of postsurgical follow-up. Three fourths of the study cohort had lesional magnetic resonance imaging and underwent temporal lobectomy. Fifty-four (57%) PWE remained seizure-free during a median follow-up of 3.5 years. Cox proportional hazard multivariable analysis showed that aura (hazard ratio [HR] = .52, 95% confidence interval [CI] = .27-1.00), single ictal electroencephalographic pattern (HR = .33, 95% CI = .17-.660), and Elixhauser Comorbidity Index (HR = 1.05, 95% CI = 1.00-1.10) were independently associated with seizure recurrence at last follow-up. A sensitivity analysis using the Charlson Combined Score (HR = 1.38, 95% CI = 1.03-1.84, p = .027) confirmed the association of comorbidities with worse seizure outcome. Our findings provide a framework for a better informed discussion about RES prognosis in older adults. More extensive, multicenter cohort studies are needed to validate our findings and reduce hesitancy in pursuing RES in suitable older adults.

我们对老年人（≥60 岁）癫痫切除手术（RES）的预后因素缺乏了解，尤其是合并症的作用，而合并症是癫痫患者（PWE）护理管理中的一个主要考虑因素。我们分析了单中心队列中的 94 名老年人（中位年龄 = 63.5 岁，52% 为女性），他们在 2000 年至 2021 年期间接受了 RES 手术，术后随访至少 6 个月。研究队列中有四分之三的人有病变磁共振成像，并接受了颞叶切除术。54名（57%）PWE患者在中位随访3.5年期间没有癫痫发作。Cox 比例危险多变量分析显示，先兆（危险比 [HR] = .52，95% 置信区间 [CI] = .27-1.00）、单一发作性脑电图模式（HR = .33，95% CI = .17-.660）和 Elixhauser 合并症指数（HR = 1.05，95% CI = 1.00-1.10）与最后一次随访时的癫痫复发独立相关。使用 Charlson 综合评分进行的敏感性分析（HR = 1.38，95% CI = 1.03-1.84，p = .027）证实了合并症与较差的癫痫发作预后相关。我们的研究结果为更好地讨论老年人的 RES 预后提供了一个框架。需要更广泛的多中心队列研究来验证我们的发现，并减少合适的老年人在寻求 RES 时的犹豫不决。

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引用次数: 0

Centromedian thalamic deep brain stimulation for idiopathic generalized epilepsy: Connectivity and target optimization 中枢丘脑深部脑刺激治疗特发性全身性癫痫：连接性和目标优化

IF 5.6 1区医学 Q1 CLINICAL NEUROLOGY

Epilepsia

Pub Date : 2024-09-14 DOI: 10.1111/epi.18122

Sihyeong Park, Fiona Permezel, Shruti Agashe, Gamaleldin Osman, Hugh D. Simpson, Kai J. Miller, Jamie J. Van Gompel, Keith Starnes, Brian N. Lundstrom, Gregory A. Worrell, Nicholas M. Gregg

There are limited treatment options for individuals with drug‐resistant idiopathic generalized epilepsy (IGE). Small, limited case series suggest that centromedian thalamus deep brain stimulation (CM‐DBS) may be an effective treatment option. The optimal CM‐DBS target for IGE is underexamined. Here, we present a retrospective analysis of CM‐DBS targeting and efficacy for five patients with drug‐resistant IGE. Volume of tissue activated (VTA) overlap with CM nucleus was performed using an open‐source toolbox. Median follow‐up time was 13 months. Median convulsive seizure frequency reduction was 66%. One patient had only absence seizures, with >99% reduction in absence seizure frequency. Four patients had electrode contacts positioned within the CM nucleus target, all of whom had >50% reduction in primary semiology seizure, with 85% median seizure reduction (p = .004, paired‐sample t test). Volumetric “sweet‐spot” mapping revealed that best outcomes were correlated with stimulation of the middle ventral CM nucleus. Connectivity strength between the sweet‐spot region and central peri‐Rolandic cortex was increased significantly relative to other cortical regions (p = 8.6 × 10−4, Mann–Whitney U test). Our findings indicate that CM‐DBS can be an effective treatment for patients with IGE, highlight the importance of accurate targeting and targeting analysis, and within the context of prior work, suggest that ideal CM‐DBS targets may be syndrome specific.

目前，针对耐药性特发性全身性癫痫（IGE）患者的治疗方案十分有限。小型、有限的病例系列表明，丘脑中央深部脑刺激（CM-DBS）可能是一种有效的治疗方法。目前对 IGE 的最佳 CM-DBS 靶点研究不足。在此，我们对五名耐药 IGE 患者的 CM-DBS 靶点和疗效进行了回顾性分析。使用开源工具箱进行了组织激活体积（VTA）与 CM 核的重叠分析。中位随访时间为 13 个月。抽搐发作频率减少的中位数为66%。一名患者只有失神发作，失神发作频率减少了99%。四名患者的电极触点位于 CM 核靶点内，他们的原发性半规管癫痫发作次数减少了 50%，中位癫痫发作次数减少了 85%（p = .004，配对样本 t 检验）。容积 "甜点 "绘图显示，最佳疗效与刺激 CM 中腹核相关。与其他皮质区域相比，甜点区域与中央周围罗兰皮质之间的连接强度显著增加（p = 8.6 × 10-4，曼-惠特尼 U 检验）。我们的研究结果表明，CM-DBS 对 IGE 患者是一种有效的治疗方法，强调了准确定位和定位分析的重要性，并结合之前的研究表明，理想的 CM-DBS 靶点可能具有综合征特异性。

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引用次数: 0

Association of baseline sleep duration and sleep quality with seizure recurrence in newly treated patients with epilepsy 新近接受治疗的癫痫患者的基线睡眠时间和睡眠质量与癫痫复发的关系

IF 5.6 1区医学 Q1 CLINICAL NEUROLOGY

Epilepsia

Pub Date : 2024-09-11 DOI: 10.1111/epi.18106

Rui Zhong, Guangjian Li, Teng Zhao, Hanyu Zhang, Xinyue Zhang, Weihong Lin

ObjectiveAlthough sleep duration and sleep quality are considered to be significant factors associated with epilepsy and seizure risk, findings are inconsistent, and their joint association remains uncertain. This study aimed to determine independent and joint associations of these two modifiable sleep features with seizure recurrence risk in newly treated patients with epilepsy (PWE).MethodsThis is a prospective cohort study of newly treated PWE at a comprehensive epilepsy center in northeast China between June 2020 and December 2023. Self‐reported sleep duration and sleep quality were collected at baseline. All patients were followed for 12 months for recurrent seizures. Cox proportional hazard regression models were used to estimate the hazard ratios (HRs) of seizure recurrence. Models fitted with restricted cubic spline were conducted to test for linear and nonlinear shapes of each association.ResultsA total of 209 patients were included, and 103 experienced seizure recurrence during follow‐up. Baseline short sleep was significantly associated with greater risk of seizure recurrence (adjusted HR = 2.282, 95% confidence interval [CI] = 1.436–3.628, p < .001). Sleep duration (h/day) and recurrent seizure risk showed a significant nonlinear U‐shaped association, with a nadir at 8 h/day. Baseline poor sleep quality was significantly associated with greater risk of seizure recurrence (adjusted HR = 1.985, 95% CI = 1.321–2.984, p < .001). Pittsburgh Sleep Quality Index score and seizure recurrence risk exhibited a positive linear association. Participants with a combination of poor quality–short sleep showed the highest risk of seizure recurrence (adjusted HR = 3.13, 95% CI = 1.779–5.507, p < .001) compared to the referent good quality–intermediate sleep group.SignificanceBaseline sleep duration and sleep quality were independently and jointly associated with risk of seizure recurrence in newly treated PWE. Our results point to an important potential role of baseline sleep duration and sleep quality in shaping seizure risk.

目的虽然睡眠时间和睡眠质量被认为是与癫痫和癫痫发作风险相关的重要因素，但研究结果并不一致，而且它们之间的联合关系仍不确定。本研究旨在确定这两种可改变的睡眠特征与新近接受治疗的癫痫患者（PWE）癫痫复发风险的独立和联合关系。方法这是一项前瞻性队列研究，研究对象为2020年6月至2023年12月期间在中国东北地区一家综合性癫痫中心接受治疗的新近接受治疗的癫痫患者。基线研究收集了患者自我报告的睡眠时间和睡眠质量。对所有患者进行为期 12 个月的复发性癫痫发作随访。Cox比例危险回归模型用于估计癫痫复发的危险比（HRs）。结果共纳入 209 名患者，其中 103 名患者在随访期间癫痫复发。基线睡眠时间较短与癫痫复发风险较高明显相关（调整后 HR = 2.282，95% 置信区间 [CI] = 1.436-3.628，p <.001）。睡眠持续时间（小时/天）与癫痫复发风险呈显著的非线性 U 型关系，最低点为 8 小时/天。基线睡眠质量差与更高的癫痫复发风险显著相关（调整后 HR = 1.985，95% CI = 1.321-2.984，p < .001）。匹兹堡睡眠质量指数得分与癫痫复发风险呈正线性关系。与参考的良好睡眠质量-中等睡眠组相比，睡眠质量差-睡眠时间短组合的参与者癫痫复发风险最高（调整后 HR = 3.13，95% CI = 1.779-5.507，p <.001）。我们的研究结果表明，基线睡眠时间和睡眠质量在影响癫痫发作风险方面具有重要的潜在作用。

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引用次数: 0

Factors associated with poor sleep in children with drug‐resistant epilepsy 耐药性癫痫患儿睡眠质量差的相关因素

IF 5.6 1区医学 Q1 CLINICAL NEUROLOGY

Epilepsia

Pub Date : 2024-09-10 DOI: 10.1111/epi.18112

Renee Proost, Evy Cleeren, Bastiaan Jansen, Lieven Lagae, Wim Van Paesschen, Katrien Jansen

ObjectiveWe aimed to investigate sleep in children with drug‐resistant epilepsy (DRE), including developmental and epileptic encephalopathies (DEEs). Next, we examined differences in sleep macrostructure and microstructure and questionnaire outcomes between children with well‐controlled epilepsy (WCE) and children with DRE. Furthermore, we wanted to identify factors associated with poor sleep outcome in these children, as some factors might be targets to improve epilepsy and neurodevelopmental outcomes.MethodsA cross‐sectional study was conducted in children 4 to 18‐years‐old. Children without epilepsy, with WCE, and with DRE were included. Overnight electroencephalography (EEG), including chin electromyography and electrooculography, to allow sleep staging, was performed. Parents were asked to fill out a sleep questionnaire. Classical five‐stage sleep scoring was performed manually, spindles were automatically counted, and slow wave activity (SWA) in the first and last hour of slow wave sleep was calculated.ResultsOne hundred eighty‐two patients were included: 48 without epilepsy, 75 with WCE, and 59 with DRE. We found that children with DRE have significantly lower sleep efficiency (SE%), less time spent in rapid eye movement (REM) sleep, fewer sleep spindles, and a lower SWA decline over the night compared to children with WCE. Subjectively more severe sleep problems were reported by the caregivers and more daytime sleepiness was present in children with DRE. Least absolute shrinkage and selection operator (LASSO) regression showed that multifocal interictal epileptiform discharges (IEDs), benzodiazepine treatment, and longer duration of epilepsy were associated with lower SE% and lower REM sleep time. The presence of multifocal discharges and cerebral palsy was associated with fewer spindles. Benzodiazepine treatment, drug resistance, seizures during sleep, intellectual disability, and older age were associated with lower SWA decline.SignificanceBoth sleep macrostructure and microstructure are severely impacted in children with DRE, including those with DEEs. Epilepsy parameters play a distinct role in the disruption REM sleep, spindle count, and SWA decline.

目的我们旨在调查耐药性癫痫（DRE）儿童（包括发育性癫痫和癫痫性脑病（DEE））的睡眠情况。其次，我们研究了癫痫控制良好的儿童（WCE）与抗药性癫痫儿童在睡眠宏观和微观结构以及问卷调查结果方面的差异。此外，我们还希望找出与这些儿童睡眠质量差相关的因素，因为有些因素可能是改善癫痫和神经发育结果的目标。研究对象为 4 至 18 岁的儿童，包括无癫痫儿童、WCE 患儿和 DRE 患儿。研究人员进行了一夜的脑电图（EEG）检查，包括下巴肌电图和脑电图，以便对睡眠进行分期。要求家长填写睡眠问卷。手动进行经典的五阶段睡眠评分，自动计算棘波，并计算慢波睡眠第一小时和最后一小时的慢波活动（SWA）：其中 48 名无癫痫，75 名有 WCE，59 名有 DRE。我们发现，与 WCE 患儿相比，DRE 患儿的睡眠效率（SE%）明显较低、快速眼动睡眠（REM）时间较短、睡眠棘波较少，而且整夜的 SWA 下降幅度也较低。护理人员报告的主观睡眠问题更为严重，罹患嗜睡症的儿童白天嗜睡现象更为严重。最小绝对收缩和选择算子（LASSO）回归显示，多灶性发作间期癫痫样放电（IED）、苯二氮卓类药物治疗和癫痫持续时间较长与较低的SE%和较低的快速眼动睡眠时间有关。多灶性放电和脑瘫的存在与较少的棘波有关。苯二氮卓治疗、耐药性、睡眠中癫痫发作、智力障碍和年龄较大与SWA下降较低有关。癫痫参数在干扰快速眼动睡眠、纺锤体数量和SWA下降方面起着独特的作用。

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引用次数: 0

Nonictal electroencephalographic measures for the diagnosis of functional seizures 诊断功能性癫痫发作的非发作性脑电测量方法

IF 5.6 1区医学 Q1 CLINICAL NEUROLOGY

Epilepsia

Pub Date : 2024-09-10 DOI: 10.1111/epi.18110

Chloe H. L. Hinchliffe, Mahinda Yogarajah, Samia Elkommos, Hongying Tang, Daniel Abasolo

ObjectiveFunctional seizures (FS) look like epileptic seizures but are characterized by a lack of epileptic activity in the brain. Approximately one in five referrals to epilepsy clinics are diagnosed with this condition. FS are diagnosed by recording a seizure using video‐electroencephalography (EEG), from which an expert inspects the semiology and the EEG. However, this method can be expensive and inaccessible and can present significant patient burden. No single biomarker has been found to diagnose FS. However, the current limitations in FS diagnosis could be improved with machine learning to classify signal features extracted from EEG, thus providing a potentially very useful aid to clinicians.MethodsThe current study has investigated the use of seizure‐free EEG signals with machine learning to identify subjects with FS from those with epilepsy. The dataset included interictal and preictal EEG recordings from 48 subjects with FS (mean age = 34.76 ± 10.55 years, 14 males) and 29 subjects with epilepsy (mean age = 38.95 ± 13.93 years, 18 males) from which various statistical, temporal, and spectral features from the five EEG frequency bands were extracted then analyzed with threshold accuracy, five machine learning classifiers, and two feature importance approaches.ResultsThe highest classification accuracy reported from thresholding was 60.67%. However, the temporal features were the best performing, with the highest balanced accuracy reported by the machine learning models: 95.71% with all frequency bands combined and a support vector machine classifier.SignificanceMachine learning was much more effective than using individual features and could be a powerful aid in FS diagnosis. Furthermore, combining the frequency bands improved the accuracy of the classifiers in most cases, and the lowest performing EEG bands were consistently delta and gamma.

目的功能性癫痫发作（FS）看起来像癫痫发作，但其特点是大脑中缺乏癫痫活动。约有五分之一的癫痫诊所转诊患者被诊断出患有这种疾病。诊断 FS 的方法是使用视频脑电图（EEG）记录癫痫发作，然后由专家检查半身像和脑电图。然而，这种方法既昂贵又难以使用，而且会给患者带来沉重负担。目前还没有发现可以诊断 FS 的单一生物标志物。然而，通过机器学习对从脑电图中提取的信号特征进行分类，可以改善目前 FS 诊断的局限性，从而为临床医生提供潜在的非常有用的帮助。数据集包括 48 名 FS 患者（平均年龄 = 34.76 ± 10.55 岁，14 名男性）和 29 名癫痫患者（平均年龄 = 38.95 ± 13.93 岁，18 名男性）的发作间期和发作前脑电图记录，从中提取了五个脑电图频带的各种统计、时间和频谱特征，然后用阈值准确率、五个机器学习分类器和两种特征重要性方法进行了分析。然而，时间特征的表现最好，机器学习模型报告的平衡准确率最高：重要意义机器学习比使用单个特征更有效，可作为 FS 诊断的有力辅助工具。此外，在大多数情况下，合并频段提高了分类器的准确性，表现最低的脑电图频段一直是 delta 和 gamma。

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引用次数: 0