Postictal EEG changes following focal seizures: Interrater agreement and comparison to frequency analysis

ObjectivesTo compare frequency analysis to human raters and determine the interrater agreement of postictal EEG changes after focal seizures.Methods24 focal seizures with and without impaired awareness recorded with scalp-EEG in the epilepsy monitoring unit were selected. Five board-certified neurophysiologists annotated seizure termination and end of postictal changes for all seizures. We assessed agreement using intraclass correlation, described the band-power changes by time-frequency analysis, and correlated these measures with the rater annotations.ResultsInterrater agreement on the duration of the postictal changes was moderate (0.64, 95% confidence interval: 0.36–0.82). The interrater agreement for seizure termination was excellent (1.00). Median duration of the postictal interval of seizures with impaired awareness was significantly shorter than for seizures with retained awareness (p = 0.0004). Mean postictal duration was 16.4 min. Seizure duration did not predict duration of the postictal changes. We found a strong correlation of 0.8 between the median human rater and the duration of the decrease in spectral edge frequency.ConclusionsThe agreement of neurophysiologists is moderate for duration of postictal changes and high for seizure termination. Rater determination of postictal duration is correlated with measures of EEG slowing.SignificanceDisagreement between neurophysiologists on postictal duration need to be considered.     

The effect of reducing EEG electrode number on the visual interpretation of the human expert for neonatal seizure detection

Objectives

To measure changes in the visual interpretation of the EEG by the human expert for neonatal seizure detection when reducing the number of recording electrodes.

Detecting temporal lobe seizures from scalp EEG recordings: a comparison of various features.

OBJECTIVE: Sixteen different features are evaluated in their potential ability to detect seizures from scalp EEG recordings containing temporal lobe (TL) seizures. Features include spectral measures, non-linear methods (e.g. zero-crossings), phase synchronization and the recently introduced Brain Symmetry Index (BSI). Besides an individual comparison, several combinations of features are evaluated as well in their potential ability to detect TL seizures. METHODS: Sixteen long-term scalp EEG recordings, containing TL seizures from patients suffering from temporal lobe epilepsy (TLE), were analyzed. For each EEG, all 16 features were determined for successive 10s epochs of the recording. All epochs were labeled by experts for the presence or absence of seizure activity. In addition, triplet combinations of various features were evaluated using pattern recognition tools. Final performance was evaluated by the sensitivity and specificity (False Alarm Rate (FAR)), using ROC curves. RESULTS: In those TL seizures characterized by unilateral epileptiform discharges, the BSI was the best single feature. Except for one low-voltage EEG with many artifacts, the sensitivity found ranged from 0.55 to 0.90 at a FAR of approximately 1/h. Using three features increased the sensitivity to 0.77-0.97. In patients with bilateral electroencephalographic changes, the single best feature most often found was a measure for the number of minima and maxima (mmax) in the recording, yielding sensitivities of approximately 0.30-0.96 at FAR approximately 1/h. Using three features increased the sensitivity to 0.38-0.99, at the same FAR. In various recordings, it was even possible to obtain sensitivities of 0.70-0.95 at a FAR = 0. CONCLUSIONS: The Brain Symmetry Index is the most relevant individual feature to detect electroencephalographic seizure activity in TLE with unilateral epileptiform discharges. In patients with bilateral discharges, mmax performs best. Using a triplet of features significantly improves the performance of the detector. SIGNIFICANCE: Improved seizure detection can improve patient care in both the epilepsy monitoring unit and the intensive care unit.     

新生期反复惊厥对大鼠皮质区糖皮质激素受体表达的影响

背景：糖皮质激素（GC）作为一种重要的抗炎物质对发育中脑损伤本应具有良好的治疗作用,但随着相关病例增加,人们发现在围产期接受GC治疗的早产儿发生脑瘫危险性明显增高。因此,是否在发育期应用GC治疗疾病颇多争议。本实验通过研究脑内糖皮质激素受体（GR）表达变化来进一步阐明GC对发育中脑损伤的影响。 目的：研究新生期反复惊厥对大鼠大脑皮层内GR表达的影响。 设计：动物实验研究。 时间和地点：本实验于2008年2月至2009年3月在中南大学湘雅二医院儿科完成。 材料：应用提供自中南大学湘雅二医院实验动物中心的生后7天的SD大鼠用于实验,所有实验过程都遵循实验动物伦理学标准。 方法：生后（postnatal,PN）7d的Sprague-Dawley大鼠48只,随机分成两组,惊厥组每日吸入三氟乙醚诱导惊厥发作1次,每次持续30min,连续6d;对照组同样操作但不吸入三氟乙醚。 主要观察指标：分别于惊厥后第13d、15d和19d每组各处死8只大鼠,用Western-blots法和免疫组织化学法观察大鼠大脑皮层GR表达的变化。 结果：GR在生后早期大脑皮层即有广泛表达,主要表达于胞浆,随着日龄的增加GR的表达增加,在胞浆和胞核中GR均有表达。与对照组相比, 在PN－15d时惊厥组大鼠大脑皮层胞浆中GR的表达明显下调（P<0.05）,在PN-15d、PN-19d时胞核中GR表达水平明显下调（P<0.05）。与对照组相比较,PN-13d时,惊厥组大鼠顶叶区GR免疫化学累积光密度（AOD）明显降低（P<0.05）;PN-15d时,惊厥组大鼠皮层顶叶、颞叶区GR免疫化学AOD明显降低（P<0.05）;PN-19d时,惊厥组大鼠皮层顶叶、颞叶、额叶区GR免疫化学AOD明显降低（P<0.05）。 结论：皮质区GR随脑发育成熟表达不断增高,呈现一定规律及分布特点,可能与脑发育过程密切相关;新生大鼠反复惊厥造成皮质GR表达的异常,可能参与发育期脑损伤。     

Influence of etiology on treatment choices for neonatal seizures: A survey among pediatric neurologists

BackgroundA targeted treatment approach is increasingly promoted in epilepsy management.AimTo investigate if etiology (both established or initially presumed) influences antiepileptic drug choice of experts in neonatal seizures.MethodsAn invitation to participate to a web-based questionnaire was sent to Italian pediatric neurologists affiliated to the Italian Society of Pediatric Neurology (SINP).Results19 pediatric neurologists from different centers, all consultants of third level Neonatal Intensive Care Units (NICUs) answered. As first-line drug phenobarbital was the most common choice, it was used in 79% of cases of acute symptomatic seizures, in 63% of structural epilepsy, in 42% of genetic epilepsies. As second-line drug phenytoin was used by 58% in acute symptomatic seizures, 37% in structural epilepsy, 5% in genetic epilepsy. Pyridoxine/pyridoxalphosphate was much more used in genetic epilepsy (as first-line in 26%, as second-line in 37%) than in the other two conditions.Long-term conventional EEG monitoring was suggested as important to verify efficacy of drugs in controlling seizures by 84% of interviewed neurologists, but EEG was available around the clock in only 53% of their centers. 1 to 3-channel aEEG/EEG (commonly named CFM) was often used instead of conventional EEG monitoring.ConclusionThis is the first survey looking at a targeted approach in treatment of neonatal seizures by pediatric neurologists consulted by NICUs. The treatment approach is similar to previous surveys in case of acute symptomatic seizures, but in case of other etiologies the choices are different, especially for the second-line option. Larger studies should address this topic.     

The effects of vagus nerve stimulation on sleep EEG in depression: a preliminary report

OBJECTIVE: The present study evaluated the effects of vagus nerve stimulation (VNS) on sleep in seven treatment-resistant depressed outpatients. METHODS: Sleep studies were conducted in the laboratory at baseline and 10-12 weeks after VNS implantation while the concomitant psychotropic medication regimen was unchanged. Standard sleep macroarchitecture based on visual stage and assessment of ultradian sleep electroencephalographic (EEG) rhythms were measured on all nights. RESULTS: An overall significant treatment effect on sleep macroarchitecture was obtained by MANOVA. Decreased awake time, decreased Stage 1 sleep and increased Stage 2 sleep were evident post-VNS, although univariate analyses did not reach significance. In addition, the strength or amplitude of ultradian sleep EEG rhythms more than doubled on VNS and was restored to within normal range. CONCLUSION: VNS improved the clinical symptoms of depression and sleep architecture. Results suggest that treatment-resistant depressed patients have dampened sleep EEG rhythms that are restored to near-normal amplitudes with VNS treatment.     

Applicability of NeuroTrend as a bedside monitor in the neuro ICU

Objective

To assess whether ICU caregivers can correctly read and interpret continuous EEG (cEEG) data displayed with the computer algorithm NeuroTrend (NT) with the main attention on seizure detection and determination of sedation depth.