Dataset Information

Electroencephalogram discharges in atypical cognitive development.

ABSTRACT: To investigate the significance of electroencephalogram (EEG) discharges and their treatment, we retrospectively reviewed the charts of 22 children with atypical cognitive development that did not respond to standard educational therapy and demonstrated discharges on EEG. Most children demonstrated no obvious symptoms of seizures, and developmental regression and/or fluctuations were uncommon. The majority of children demonstrated a language and attention disorder and autism symptomatology and had multifocal discharges on EEGs. Of the 20 patients treated with antiepileptic medications, 70% demonstrated definite improvement within 1 clinic visit. This study suggests that children with EEG discharges and developmental cognitive disorders demonstrate a unique pattern of symptomatology and discharges on EEG. This study suggests that children with developmental cognitive disorders that do not respond to standard therapy may benefit from screening with an EEG and a trial of antiepileptic mediation if discharges are detected.

SUBMITTER: Frye RE

PROVIDER: S-EPMC2896832 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Electroencephalogram discharges in atypical cognitive development.

Frye Richard E RE Butler Ian I Strickland David D Castillo Edwardo E Papanicolaou Andrew A

Journal of child neurology 20100318 5

To investigate the significance of electroencephalogram (EEG) discharges and their treatment, we retrospectively reviewed the charts of 22 children with atypical cognitive development that did not respond to standard educational therapy and demonstrated discharges on EEG. Most children demonstrated no obvious symptoms of seizures, and developmental regression and/or fluctuations were uncommon. The majority of children demonstrated a language and attention disorder and autism symptomatology and h ...[more]

PMID: 20299700

Similar Datasets

Project description:ImportanceInterictal epileptiform discharges (IEDs) in electroencephalograms (EEGs) are a biomarker of epilepsy, seizure risk, and clinical decline. However, there is a scarcity of experts qualified to interpret EEG results. Prior attempts to automate IED detection have been limited by small samples and have not demonstrated expert-level performance. There is a need for a validated automated method to detect IEDs with expert-level reliability.ObjectiveTo develop and validate a computer algorithm with the ability to identify IEDs as reliably as experts and classify an EEG recording as containing IEDs vs no IEDs.Design, setting, and participantsA total of 9571 scalp EEG records with and without IEDs were used to train a deep neural network (SpikeNet) to perform IED detection. Independent training and testing data sets were generated from 13 262 IED candidates, independently annotated by 8 fellowship-trained clinical neurophysiologists, and 8520 EEG records containing no IEDs based on clinical EEG reports. Using the estimated spike probability, a classifier designating the whole EEG recording as positive or negative was also built.Main outcomes and measuresSpikeNet accuracy, sensitivity, and specificity compared with fellowship-trained neurophysiology experts for identifying IEDs and classifying EEGs as positive or negative or negative for IEDs. Statistical performance was assessed via calibration error and area under the receiver operating characteristic curve (AUC). All performance statistics were estimated using 10-fold cross-validation.ResultsSpikeNet surpassed both expert interpretation and an industry standard commercial IED detector, based on calibration error (SpikeNet, 0.041; 95% CI, 0.033-0.049; vs industry standard, 0.066; 95% CI, 0.060-0.078; vs experts, mean, 0.183; range, 0.081-0.364) and binary classification performance based on AUC (SpikeNet, 0.980; 95% CI, 0.977-0.984; vs industry standard, 0.882; 95% CI, 0.872-0.893). Whole EEG classification had a mean calibration error of 0.126 (range, 0.109-0.1444) vs experts (mean, 0.197; range, 0.099-0.372) and AUC of 0.847 (95% CI, 0.830-0.865).Conclusions and relevanceIn this study, SpikeNet automatically detected IEDs and classified whole EEGs as IED-positive or IED-negative. This may be the first time an algorithm has been shown to exceed expert performance for IED detection in a representative sample of EEGs and may thus be a valuable tool for expedited review of EEGs.

Project description:ObjectiveCognitive impairment occurs frequently in Parkinson's disease (PD) and negatively impacts the patient's quality of life. However, its pathophysiological mechanism remains unclear, hindering the development of new therapies. Changes in brain connectivity are related to cognitive impairment in patients with PD, with the dorsolateral prefrontal cortex (DLPFC) being considered the essential region related to PD cognitive impairment. Nevertheless, few studies have focused on the global connectivity responsible for communication with the DLPFC node, the posterior division of the middle frontal gyrus (PMFG) in patients with PD; this was the focus of this study.MethodsWe applied resting-state electroencephalography (EEG) and calculated a reliable functional connectivity measurement, the debiased weighted phase lag index (dWPLI), to examine inter-regional functional connectivity in 68 patients with PD who were classified into two groups according to their cognitive condition.ResultsWe observed that altered left and right PMFG-based functional connectivity associated with cognitive impairment in patients with PD in the theta frequency bands under the eyes closed condition (r = -0.426, p < 0.001 and r = -0.437, p < 0.001, respectively). Exploratory results based on the MoCA subdomains indicated that poorer visuospatial function was associated with higher right PMFG-based functional connectivity (r = -0.335, p = 0.005), and poorer attention function was associated with higher left and right PMFG-based functional connectivity (r = -0.380, p = 0.001 and r = -0.256, p = 0.035, respectively). Further analysis using logistic regression and receiver operating characteristic (ROC) curves found that this abnormal functional connectivity was an independent risk factor for cognitive impairment [odds ratio (OR): 2.949, 95% confidence interval (CI): 1.294-6.725, p = 0.01 for left PMFG; OR: 11.278, 95% CI: 2.578-49.335, p = 0.001 for right PMFG, per 0.1 U], and provided moderate classification power to discriminate between cognitive abilities in patients with PD [area under the ROC curve (AUC) = 0.770 for left PMFG; AUC = 0.809 for right PMFG].ConclusionThese preliminary findings indicate that abnormal PMFG-based functional connectivity patterns associated with cognitive impairment in the theta frequency bands under the eyes closed condition and altered functional connectivity patterns have the potential to act as reliable biomarkers for identifying cognitive impairment in patients with PD.

Project description:BackgroundPostoperative delirium is a common complication that hinders recovery after surgery. Intraoperative electroencephalogram suppression has been linked to postoperative delirium, but it is unknown if this relationship is causal or if electroencephalogram suppression is merely a marker of underlying cognitive abnormalities. The hypothesis of this study was that intraoperative electroencephalogram suppression mediates a nonzero portion of the effect between preoperative abnormal cognition and postoperative delirium.MethodsThis is a prespecified secondary analysis of the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES) randomized trial, which enrolled patients age 60 yr or older undergoing surgery with general anesthesia at a single academic medical center between January 2015 and May 2018. Patients were randomized to electroencephalogram-guided anesthesia or usual care. Preoperative abnormal cognition was defined as a composite of previous delirium, Short Blessed Test cognitive score greater than 4 points, or Eight Item Interview to Differentiate Aging and Dementia score greater than 1 point. Duration of intraoperative electroencephalogram suppression was defined as number of minutes with suppression ratio greater than 1%. Postoperative delirium was detected via Confusion Assessment Method or chart review on postoperative days 1 to 5.ResultsAmong 1,113 patients, 430 patients showed evidence of preoperative abnormal cognition. These patients had an increased incidence of postoperative delirium (151 of 430 [35%] vs.123 of 683 [18%], P < 0.001). Of this 17.2% total effect size (99.5% CI, 9.3 to 25.1%), an absolute 2.4% (99.5% CI, 0.6 to 4.8%) was an indirect effect mediated by electroencephalogram suppression, while an absolute 14.8% (99.5% CI, 7.2 to 22.5%) was a direct effect of preoperative abnormal cognition. Randomization to electroencephalogram-guided anesthesia did not change the mediated effect size (P = 0.078 for moderation).ConclusionsA small portion of the total effect of preoperative abnormal cognition on postoperative delirium was mediated by electroencephalogram suppression. Study precision was too low to determine if the intervention changed the mediated effect.

Project description:ObjectiveCognitive impairment often impacts quality of life in epilepsy even if seizures are controlled. Word-finding difficulty is particularly prevalent and often attributed to etiological (static, baseline) circuit alterations. We sought to determine whether interictal discharges convey significant superimposed contributions to word-finding difficulty in patients, and if so, through which cognitive mechanism(s).MethodsTwenty-three patients undergoing intracranial monitoring for drug-resistant epilepsy participated in multiple tasks involving word production (auditory naming, short-term verbal free recall, repetition) to probe word-finding difficulty across different cognitive domains. We compared behavioral performance between trials with versus without interictal discharges across six major brain areas and adjusted for intersubject differences using mixed-effects models. We also evaluated for subjective word-finding difficulties through retrospective chart review.ResultsSubjective word-finding difficulty was reported by the majority (79%) of studied patients preoperatively. During intracranial recordings, interictal epileptiform discharges (IEDs) in the medial temporal lobe were associated with long-term lexicosemantic memory impairments as indexed by auditory naming (p = .009), in addition to their established impact on short-term verbal memory as indexed by free recall (p = .004). Interictal discharges involving the lateral temporal cortex and lateral frontal cortex were associated with delayed reaction time in the auditory naming task (p = .016 and p = .018), as well as phonological working memory impairments as indexed by repetition reaction time (p = .002). Effects of IEDs across anatomical regions were strongly dependent on their precise timing within the task.SignificanceIEDs appear to act through multiple cognitive mechanisms to form a convergent basis for the debilitating clinical word-finding difficulty reported by patients with epilepsy. This was particularly notable for medial temporal spikes, which are quite common in adult focal epilepsy. In parallel with the treatment of seizures, the modulation of interictal discharges through emerging pharmacological means and neurostimulation approaches may be an opportunity to help address devastating memory and language impairments in epilepsy.

Dataset Information

Electroencephalogram discharges in atypical cognitive development.

Publications

Electroencephalogram discharges in atypical cognitive development.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets