The growing number of genes identified in relation to epilepsy represents a major breakthrough in diagnosis and treatment, but experts face the challenge of efficiently accessing and consolidating the vast amount of genetic data available. Therefore, we present the process of transforming data from different sources and formats into an Entity-Attribute-Value (EAV) model database. Combined with the use of standard coding systems, this approach will provide a scalable and adaptable database to present the data in a comprehensive way to experts via a dashboard.

INTRODUCTION:The configuration of electronic data capture (EDC) systems has a relevant impact on data quality in studies and patient registries. The objective was to develop a method to visualise the configuration of an EDC system to check the completeness and correctness of the data definition and rules. METHODS:Step 1: transformation of the EDC data model into a graphical model, step 2: Checking the completeness and consistency of the data model, step 3: correction of identified findings. This process model was evaluated on the patient registry EpiReg. RESULTS:Using the graphical visualisation as a basis, 21 problems in the EDC configuration were identified, discussed with an interdisciplinary team, and corrected. CONCLUSION:The tested methodological approach enables an improvement in data quality by optimising the underlying EDC configuration.

IntroductionParoxysmal seizure-like events can be a diagnostic challenge. Inpatient video-electroencephalography (EEG) monitoring (VEM) can be a valuable diagnostic tool, but recommendations for the minimal duration of VEM to confirm or rule out epilepsy are inconsistent. In this study, we aim to determine whether VEM of 48 or 72 h was superior to 24 h.MethodsIn this monocentric, retrospective study, we included 111 patients with paroxysmal, seizure-like events who underwent at least 72 h of VEM. Inclusion criteria were as follows: (1) Preliminary workup was inconclusive; (2) VEM admission occurred to confirm a diagnosis; (3) At discharge, the diagnosis of epilepsy was conclusively established. We analyzed the VEM recordings to determine the exact time point of the first occurrence of epileptic abnormalities (EAs; defined as interictal epileptiform discharges or electrographic seizures). Subgroup analyses were performed for epilepsy types and treatment status.ResultsIn our study population, 69.4% (77/111) of patients displayed EAs during VEM. In this group, the first occurrence of EAs was observed within 24 h in 92.2% (71/77) of patients and within 24–72 h in 7.8% (6/77). There was no statistically significant difference in the incidence of EA between medicated and non-medicated patients or between focal, generalized epilepsies and epilepsies of unknown type. Of the 19 recorded spontaneous electroclinical seizures, 6 (31.6%) occurred after 24 h.DiscussionA VEM of 24 h may be sufficient in the diagnostic workup of paroxysmal seizure-like events under most circumstances. Considering the few cases of first EA in the timeframe between 24 and 72 h, a prolonged VEM may be useful in cases with a high probability of epilepsy or where other strategies like sleep-EEG or ambulatory EEG show inconclusive results. Prolonged VEM increases the chance of recording spontaneous seizures. Our study also highlights a high share of subjects with epilepsy that do not exhibit EAs during 72 h of VEM.

Objective: Establishing the diagnosis of epilepsy can be challenging if interictal epileptic discharges (IEDs) or seizures are undetectable. Many individuals with epilepsy experience sleep disturbances. A reduced percentage of REM sleep (REM%) has been observed following seizures. We aimed to assess differences of REM% in individuals with epilepsy in comparison with differential diagnoses. Methods: We performed a retrospective, monocentric, two-armed case-control study with 128 age-matched individuals who underwent >= 72 hours of continuous video-EEG monitoring at our epilepsy monitoring unit (EMU) for diagnostic evaluation. We assessed REM% on the first and last night of EMU admission. Logistic regressions models were used to evaluate the predictive value of REM%. Results: We included 64 individuals diagnosed with epilepsy and 64 with a differential diagnosis. REM% in the epilepsy group was significantly lower [12.2% (+4.7) vs. 17.2% (+5.2), p<0.0011. We found no significant influence of sex, age, anti-seizure, or other medications. A REM%-based and an IED and seizure-based regression model were not significantly different [area under the curve (AUC) 0.791 (95% confidence interval (CI): 0.7130.870) vs. 0.853 (95% CI: 0.788-0.919), p=0.231. A combined model, based on IEDs, seizures, and REM%, was superior to the IED model alone [0.933 (0.891-0.975), p<0.01]. Interpretation: Our study shows significantly reduced REM% in individuals with epilepsy. REM%-based models show a good predictive performance. REM% assessment could improve diagnostic accuracy - especially for challenging cases, e.g., when IEDs or seizures are absent and patient history and semiology appear ambiguous. REM% as a biomarker should be evaluated in prospective, multicentric trials.

Dysphagia is one of the most common and important complications in Huntington disease (HD), frequently leading to aspiration pneumonia and mortality. Objective estimates of prevalence using instrumental diagnostics and data on neural correlates of dysphagia in HD are scarce or lacking entirely. Similarly, its correlation with other clinical markers is still not fully known. We aimed at defining clinical risk factors and neural correlates for compromised swallowing safety in HD more precisely.

Purpose: Disruptive behavior disorders (DBD) and attention-deficit/hyperactivity disorder (ADHD) are externalizing disorders that frequently co-occur but also have distinct clinical characteristics. Identifying distinct neurocognitive phenotypes may help optimizing individual diagnosis and treatment of both disorders. Methods: Using data from 6,517 children and adolescents from the Philadelphia Neurodevelopmental Cohort, we investigated diagnostic group (i.e., typically developing, DBD, ADHD, DBD & thorn; ADHD) and sex differences across various neurocognitive functions, as well as co-occurring psychiatric symptoms, while adjusting for various confounding factors. Results: Neurocognitive deficits were associated with ADHD but not DBD. Co-occurring DBD in both girls and boys with ADHD did not appear to have an additive deteriorating effect on neurocognitive functioning. Task-specific sex differences were observed but did not interact with diagnostic group. Conclusions: The findings of this study suggest that neurocognitive deficits in DBD seem to be largely driven by co-occurring ADHD and this applies equally to both sexes. (c) 2020 Society for Adolescent Health and Medicine. All rights reserved.

Background Dysphagia is a common problem in HD, frequently leading to aspiration pneumonia and consecutive mortality. Objective estimates of prevalence using instrumental diagnostics and data on neuronal correlates of dysphagia in HD are scarce. Similarly, its correlation with other clinical markers is unknown. Thus, we aimed at defining clinical risk factors and neural correlated for HD-associated dysphagia more precisely. Methods/techniques 21 subjects (12 w, 9 m, Shoulson-Fahn stadium I-IV) underwent a full clinical-neurological exam including the UHDRS motor score and cognitive data from neuropsychological tests. A clinical swallowing examination was performed by a trained SLT, as well as videoendoscopic swallow examination (FEES). Patients additionally underwent an MRI scan (T1, 3 Tesla MRI Siemens Prisma). We then correlated validated scores of dysphagia with motor and cognitive scores as well as measures of atrophy from MRI. Results/outcome Mean UHDRS motor score was 33.6 (SD 15.3), mean UHDRS cognition score 158.6 (SD 64.3). In 20 patients, FEES showed penetration or aspiration in 80%. No significant correlations were found between dysphagia severity and any of the clinical markers (motor score, cognition, functional assessment, age, CAG). Voxel based morphometry confirmed atrophy patterns in known swallowing-network areas rather than motor function, e.g. striatum, when comparing patients with no/mild vs. moderate/severe dysphagia. Conclusions Our results so far suggest that dysphagia is not predicted sufficiently well by clinical markers, as aspiration can occur even in early stage of HD, thus necessitating early instrumental assessments in the course of the disease. Arguably, dysphagia should not be referred to as a ‘prevalent motor symptom’, but rather as a distinct entity.

Suicide is a leading cause of death in Huntington’s disease (HD), following pneumonia. Up to one-fifth of individuals with HD report suicidal ideation. Identifying the risk factors of suicidal ideation in this clinical population is thus pivotal. Here, we review the literature on prevalence rates and risk factors of suicidal ideation in premanifest and manifest patients and re-evaluate them using the largest currently existing clinical dataset from the ongoing observational study “Enroll-HD” (N = 5709). Large scale studies yielded important insights regarding suicidal ideation in HD. However, estimated prevalence rates vary among studies and risk factors are still poorly understood. According to the Enroll-HD data, pre- and manifest disease stages are associated with current (5.8–10%) and a history of suicidal ideation (18.6–30.9%). Throughout the course of HD, a history of suicidal ideation and the presence of depressive symptoms were strongly associated with current suicidal ideation. However, while for premanifest individuals, socio-demographics and activities of daily living appear to be important, in manifest patients, suicidal ideation is more closely linked to anxiety, irritability, psychosis, and apathy. These results highlight the importance of treating depressive symptoms in patients with HD and addressing potential suicidal ideation during clinical monitoring. The relevance of risk factors may differ among premanifest and manifest patients.