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Objective Methods Results Significance The automated interpretation of clinical electroencephalograms (EEGs) using artificial intelligence (AI) holds the potential to bridge the treatment gap in resource‐limited settings and reduce the workload at specialized centers. However, to facilitate broad clinical implementation, it is essential to establish generalizability across diverse patient populations and equipment. We assessed whether SCORE‐AI demonstrates diagnostic accuracy comparable to that of experts when applied to a geographically different patient population, recorded with distinct EEG equipment and technical settings.We assessed the diagnostic accuracy of a “fixed‐and‐frozen” AI model, using an independent dataset and external gold standard, and benchmarked it against three experts blinded to all other data. The dataset comprised 50% normal and 50% abnormal routine EEGs, equally distributed among the four major classes of EEG abnormalities (focal epileptiform, generalized epileptiform, focal nonepileptiform, and diffuse nonepileptiform). To assess diagnostic accuracy, we computed sensitivity, specificity, and accuracy of the AI model and the experts against the external gold standard.We analyzed EEGs from 104 patients (64 females, median age = 38.6 [range = 16–91] years). SCORE‐AI performed equally well compared to the experts, with an overall accuracy of 92% (95% confidence interval [CI] = 90%–94%) versus 94% (95% CI = 92%–96%). There was no significant difference between SCORE‐AI and the experts for any metric or category. SCORE‐AI performed well independently of the vigilance state (false classification during awake: 5/41 [12.2%], false classification during sleep: 2/11 [18.2%]; p = .63) and normal variants (false classification in presence of normal variants: 4/14 [28.6%], false classification in absence of normal variants: 3/38 [7.9%]; p = .07).SCORE‐AI achieved diagnostic performance equal to human experts in an EEG dataset independent of the development dataset, in a geographically distinct patient population, recorded with different equipment and technical settings than the development dataset. [ABSTRACT FROM AUTHOR]

Our goal was to assess the interrater agreement (IRA) of photoparoxysmal response (PPR) using the classification proposed by a task force of the International League Against Epilepsy (ILAE), and a simplified classification system proposed by our group. In addition, we evaluated IRA of epileptiform discharges (EDs) and the diagnostic significance of the electroencephalographic (EEG) abnormalities. We used EEG recordings from the European Reference Network (EpiCARE) and Standardized Computer‐based Organized Reporting of EEG (SCORE). Six raters independently scored EEG recordings from 30 patients. We calculated the agreement coefficient (AC) for each feature. IRA of PPR using the classification proposed by the ILAE task force was only fair (AC = 0.38). This improved to a moderate agreement by using the simplified classification (AC = 0.56; P =.004). IRA of EDs was almost perfect (AC = 0.98), and IRA of scoring the diagnostic significance was moderate (AC = 0.51). Our results suggest that the simplified classification of the PPR is suitable for implementation in clinical practice. [ABSTRACT FROM AUTHOR]

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE are used to report the features of clinical relevance, extracted while assessing the EEGs. Selection of the terms is context sensitive: initial choices determine the subsequently presented sets of additional choices. This process automatically generates a report and feeds these features into a database. In the end, the diagnostic significance is scored, using a standardized list of terms. SCORE has specific modules for scoring seizures (including seizure semiology and ictal EEG patterns), neonatal recordings (including features specific for this age group), and for Critical Care EEG Terminology. SCORE is a useful clinical tool, with potential impact on clinical care, quality assurance, data-sharing, research and education. [ABSTRACT FROM AUTHOR]

The electroencephalography ( EEG) signal has a high complexity, and the process of extracting clinically relevant features is achieved by visual analysis of the recordings. The interobserver agreement in EEG interpretation is only moderate. This is partly due to the method of reporting the findings in free-text format. The purpose of our endeavor was to create a computer-based system for EEG assessment and reporting, where the physicians would construct the reports by choosing from predefined elements for each relevant EEG feature, as well as the clinical phenomena (for video- EEG recordings). A working group of EEG experts took part in consensus workshops in Dianalund, Denmark, in 2010 and 2011. The faculty was approved by the Commission on European Affairs of the International League Against Epilepsy (ILAE). The working group produced a consensus proposal that went through a pan- European review process, organized by the European Chapter of the International Federation of Clinical Neurophysiology. The Standardised Computer-based Organised Reporting of EEG ( SCORE) software was constructed based on the terms and features of the consensus statement and it was tested in the clinical practice. The main elements of SCORE are the following: personal data of the patient, referral data, recording conditions, modulators, background activity, drowsiness and sleep, interictal findings, 'episodes' (clinical or subclinical events), physiologic patterns, patterns of uncertain significance, artifacts, polygraphic channels, and diagnostic significance. The following specific aspects of the neonatal EEGs are scored: alertness, temporal organization, and spatial organization. For each EEG finding, relevant features are scored using predefined terms. Definitions are provided for all EEG terms and features. SCORE can potentially improve the quality of EEG assessment and reporting; it will help incorporate the results of computer-assisted analysis into the report, it will make possible the build-up of a multinational database, and it will help in training young neurophysiologists. [ABSTRACT FROM AUTHOR]

Objective: To determine the duration of epileptic seizure types in patients who did not undergo withdrawal of antiseizure medication. Methods: From a large, structured database of 11 919 consecutive, routine video‐electroencephalograpy (EEG) recordings, labeled using the SCORE (Standardized Computer‐Based Organized Reporting of EEG) system, we extracted and analyzed 2742 seizures. For each seizure type we determined median duration and range after removal of outliers (2.5–97.5 percentile). We used surface electromyography (EMG) for accurate measurement of short motor seizures. Results: Myoclonic seizures last <150 ms, epileptic spasms 0.4–2 s, tonic seizures 1.5–36 s, atonic seizures 0.1–12,5 s, when measured using surface EMG. Generalized clonic seizures last 1–24 s. Typical absence seizures are rarely longer than 30 s (2.75–26.5 s) and atypical absences last 2–100 s. In our patients, the duration of focal aware (median: 27 s; 1.25–166 s) and impaired awareness seizures (median: 42.5 s; 9.5–271 s) was shorter than reported previously in patients undergoing withdrawal of antiseizure medication. All focal seizures terminated within 10 min. Median duration of generalized tonic–clonic seizures was 79.5 s (57–102 s) and of focal‐to‐bilateral tonic–clonic seizures was 103.5 (77.5–237 s). All tonic–clonic seizures terminated within 5 min. Significance: This comprehensive list of seizure durations provides important information for characterizing seizures and diagnosing patients with epilepsy. The upper limits of seizure durations are helpful in early recognition of imminent status epilepticus. [ABSTRACT FROM AUTHOR]

• We characterized photoparoxysmal response (PPR) in a SCORE database of 10,671 EEG recordings. • Using standardized intermittent photic stimulation protocol and definitions, the prevalence of PPR was 4%. • The most common PPR type was activation of preexisting epileptogenic area. To characterize photoparoxysmal EEG response (PPR) using a standardized protocol of intermittent photic stimulation (IPS) and standardized definitions for PPR, classified into six types. Using the SCORE system (Standardized Computer-Based Organized Reporting of EEG) we prospectively built a large database of standardized EEG annotations. In this study, we extracted the features related to PPR from the structured dataset consisting of 10,671 EEG recordings with IPS, from 7,188 patients. The standardized IPS protocol elicited PPR in 375 recordings (3.5%), in 288 patients (4%), with a preponderance among young (11–20 years) and female patients (67%). PPR was persistent in patients with multiple recordings. The most frequent type of PPR was activation of preexisting epileptogenic area (58%), followed by generalized-PPR limited to the stimulus train (22%). We could not find any recording with self-sustained posterior response. Seizures were elicited in 27% of patients with PPR, most often myoclonic seizures and absences, in patients with self-sustained generalized PPR. The most common type of PPR was accentuation of preexisting epileptogenic area. Self-sustained posterior response could not be documented. Self-sustained generalized-PPR had the highest association with seizures. Using standardized stimulation protocol and definitions for PPR types, IPS provides high diagnostic yield. [ABSTRACT FROM AUTHOR]

OBJECTIVE -- To further define clinical features associated with the syndrome of diabetes and pancreatic exocrine dysfunction due to mutations in the carboxyl-ester lipase (CEL) gene and to assess the effects of pancreatic enzyme substitution therapy. RESEARCH DESIGN AND METHODS-- Nine patients with CEL gene mutation, exocrine deficiency, and diabetes were treated and followed for 30 months. RESULTS-- Treatment improved symptoms in seven of nine patients. Exocrine and endocrine function assessed by fecal elastase and A1C were not affected, although fecal lipid excretion was reduced. Vitamin E was low in all patients but increased with treatment (P < 0.001 at 30 months) and improved in five subjects. A predominantly demyelinating neuropathy was seen in a majority of patients, and carpal tunnel syndrome was common. CONCLUSIONS-- Pancreatic enzyme substitution alleviated symptoms and malabsorption and normalized vitamin E levels. Glycemic control was not significantly affected. The CEL syndrome seems associated with a demyelinating neuropathology. [ABSTRACT FROM AUTHOR]

The diagnosis of nonconvulsive status epilepticus ( NCSE) relies largely on electroencephalography ( EEG) findings. The lack of a unified EEG terminology, and of evidence-based EEG criteria, leads to varying criteria for and ability to diagnose NCSE. We propose a unified terminology and classification system for NCSE, using, as a template, the Standardised Computer-based Organised Reporting of EEG ( SCORE). This approach integrates the terminology recently proposed for the rhythmic and periodic patterns in critically ill patients, the electroclinical classification of NCSE (type of NCSE) and the context for the pathologic conditions and age-related epilepsy syndromes. We propose flexible EEG criteria that employ the SCORE system to assemble a database for determining evidence-based EEG criteria for NCSE. [ABSTRACT FROM AUTHOR]