Alcohol for seizure induction in the epilepsy monitoring unit.

RATIONALE: Seizure induction techniques are used in the epilepsy monitoring unit (EMU) to increase diagnostic yield and reduce length of stay. There are insufficient data on the efficacy of alcohol as an induction technique. METHODS: We performed a retrospective cohort study using six years of EMU data at our institution. We compared cases who received alcohol for seizure induction to matched controls who did not. The groups were matched on the following variables: age, reason for admission, length of stay, number of antiseizure medications (ASM) at admission, whether ASMs were tapered during admission, and presence of interictal epileptiform discharges. We used both propensity score and exact matching strategies. We compared the likelihood of epileptic seizures and nonepileptic events in cases versus controls using Kaplan-Meier time-to-event analysis, as well as odds ratios for these outcomes occurring at any time during the admission. RESULTS: We analyzed 256 cases who received alcohol (median dose 2.5 standard drinks) and 256 propensity score-matched controls. Cases who received alcohol were no more likely than controls to have an epileptic seizure (X2(1) = 0.01, p = 0.93) or nonepileptic event (X2(1) = 2.1, p = 0.14) in the first 48 h after alcohol administration. For the admission overall, cases were no more likely to have an epileptic seizure (OR 0.89, 95 % CI 0.61-1.28, p = 0.58), nonepileptic event (OR 0.97, CI 0.62-1.53, p = 1.00), nor require rescue benzodiazepine (OR 0.63, CI 0.35-1.12, p = 0.15). Stratified analyses revealed no increased risk of epileptic seizure in any subgroups. Sensitivity analysis using exact matching showed that results were robust to matching strategy. CONCLUSIONS: Alcohol was not an effective induction technique in the EMU. This finding has implications for counseling patients with epilepsy about the risks of drinking alcohol in moderation in their daily lives.

Minor Phenomena in Parkinson's Disease-Prevalence, Associations, and Risk of Developing Psychosis.

BACKGROUND: Minor phenomena, including passage phenomena, feeling of presence, and illusions, are common and may represent a prodromal form of psychosis in Parkinson's disease (PD). We examined the prevalence and clinical correlates of minor phenomena, and their potential role as a risk factor for PD psychosis. METHODS: A novel questionnaire, the Psychosis and Mild Perceptual Disturbances Questionnaire for PD (PMPDQ), was completed by Fox Insight cohort participants with and without PD. Additional assessments included the Non-Motor Symptoms Questionnaire (NMSQuest), REM Sleep Behavior Disorder Single Question Screen (RBD1Q), Movement Disorder Society-Unified Parkinson Disease Rating Scale Part II, demographic features, and medication usage. For participants with PD, we used regression models to identify clinical associations and predictors of incident psychosis over one year of follow-up. RESULTS: Among participants with PD (n = 5950) and without PD (n = 1879), the prevalence of minor phenomena was 43.1% and 31.7% (P < .001). Of the 3760 participants with PD and no baseline psychosis, independent correlates of minor phenomena included positive responses on the NMSQuest apathy/attention/memory (OR 1.7, 95% CI 1.3-2.1, P < .001) or sexual function domain (OR 1.3, 95% CI 1.1-1.6, P = .01) and positive RBD1Q (OR 1.3, 95% CI 1.05-1.5, P = .01). Independent risk factors for incident PD psychosis included the presence of minor phenomena (HR 3.0, 95% CI 2.4-3.9, P < .001), positive response on the NMSQuest apathy/attention/memory domain (HR 1.8, 95% CI 1.3-2.6, P < .001), and positive RBD1Q (HR 1.5, 95% CI 1.1-1.9, P = .004). CONCLUSIONS: Minor phenomena are common, associated with specific non-motor symptoms, and an independent predictor of incident psychosis in PD.

Characterizing the treatment gap in the United States among adult patients with a new diagnosis of epilepsy.

OBJECTIVE: Epilepsy is largely a treatable condition with antiseizure medication (ASM). Recent national administrative claims data suggest one third of newly diagnosed adult epilepsy patients remain untreated 3 years after diagnosis. We aimed to quantify and characterize this treatment gap within a large US academic health system leveraging the electronic health record for enriched clinical detail. METHODS: This retrospective cohort study evaluated the proportion of adult patients in the health system from 2012 to 2020 who remained untreated 3 years after initial epilepsy diagnosis. To identify incident epilepsy, we applied validated administrative health data criteria of two encounters for epilepsy/seizures and/or convulsions, and we required no ASM prescription preceding the first encounter. Engagement with the health system at least 2 years before and at least 3 years after diagnosis was required. Among subjects who met administrative data diagnosis criteria, we manually reviewed medical records for a subset of 240 subjects to verify epilepsy diagnosis, confirm treatment status, and elucidate reason for nontreatment. These results were applied to estimate the proportion of the full cohort with untreated epilepsy. RESULTS: Of 831 patients who were automatically classified as having incident epilepsy by inclusion criteria, 80 (10%) remained untreated 3 years after incident epilepsy diagnosis. Manual chart review of incident epilepsy classification revealed only 33% (78/240) had true incident epilepsy. We found untreated patients were more frequently misclassified (p < .001). Using corrected counts, we extrapolated to the full cohort (831) and estimated <1%-3% had true untreated epilepsy. SIGNIFICANCE: We found a substantially lower proportion of patients with newly diagnosed epilepsy remained untreated compared to previous estimates from administrative data analysis. Manual chart review revealed patients were frequently misclassified as having incident epilepsy, particularly patients who were not treated with an ASM. Administrative data analyses utilizing only diagnosis codes may misclassify patients as having incident epilepsy.

Quantitative artifact reduction and pharmacologic paralysis improve detection of EEG epileptiform activity in critically ill patients.

OBJECTIVE: Epileptiform activity is common in critically ill patients, but movement-related artifacts-including electromyography (EMG) and myoclonus-can obscure EEG, limiting detection of epileptiform activity. We sought to determine the ability of pharmacologic paralysis and quantitative artifact reduction (AR) to improve epileptiform discharge detection. METHODS: Retrospective analysis of patients who underwent continuous EEG monitoring with pharmacologic paralysis. Four reviewers read each patient's EEG pre- and post- both paralysis and AR, and indicated the presence of epileptiform discharges. We compared the interrater reliability (IRR) of identifying discharges at baseline, post-AR, and post-paralysis, and compared the performance of AR and paralysis according to artifact type. RESULTS: IRR of identifying epileptiform discharges at baseline was slight (N = 30; κ = 0.10) with a trend toward increase post-AR (κ = 0.26, p = 0.053) and a significant increase post-paralysis (κ = 0.51, p = 0.001). AR was as effective as paralysis at improving IRR of identifying discharges in those with high EMG artifact (N = 15; post-AR κ = 0.63, p = 0.009; post-paralysis κ = 0.62, p = 0.006) but not with primarily myoclonus artifact (N = 15). CONCLUSIONS: Paralysis improves detection of epileptiform activity in critically ill patients when movement-related artifact obscures EEG features. AR improves detection as much as paralysis when EMG artifact is high, but is ineffective when the primary source of artifact is myoclonus. SIGNIFICANCE: In the appropriate setting, both AR and paralysis facilitate identification of epileptiform activity in critically ill patients.

Extracting seizure frequency from epilepsy clinic notes: a machine reading approach to natural language processing.

OBJECTIVE: Seizure frequency and seizure freedom are among the most important outcome measures for patients with epilepsy. In this study, we aimed to automatically extract this clinical information from unstructured text in clinical notes. If successful, this could improve clinical decision-making in epilepsy patients and allow for rapid, large-scale retrospective research. MATERIALS AND METHODS: We developed a finetuning pipeline for pretrained neural models to classify patients as being seizure-free and to extract text containing their seizure frequency and date of last seizure from clinical notes. We annotated 1000 notes for use as training and testing data and determined how well 3 pretrained neural models, BERT, RoBERTa, and Bio_ClinicalBERT, could identify and extract the desired information after finetuning. RESULTS: The finetuned models (BERTFT, Bio_ClinicalBERTFT, and RoBERTaFT) achieved near-human performance when classifying patients as seizure free, with BERTFT and Bio_ClinicalBERTFT achieving accuracy scores over 80%. All 3 models also achieved human performance when extracting seizure frequency and date of last seizure, with overall F1 scores over 0.80. The best combination of models was Bio_ClinicalBERTFT for classification, and RoBERTaFT for text extraction. Most of the gains in performance due to finetuning required roughly 70 annotated notes. DISCUSSION AND CONCLUSION: Our novel machine reading approach to extracting important clinical outcomes performed at or near human performance on several tasks. This approach opens new possibilities to support clinical practice and conduct large-scale retrospective clinical research. Future studies can use our finetuning pipeline with minimal training annotations to answer new clinical questions.

Developing and Implementing a Standardized Ictal Examination in the Epilepsy Monitoring Unit.

BACKGROUND: The ictal examination is crucial for neuroanatomic localization of seizure onset, which informs medical and neurosurgical treatment of epilepsy. Substantial variation exists in ictal examination performance in epilepsy monitoring units (EMUs). We developed and implemented a standardized examination to facilitate rapid, reliable execution of all testing domains and adherence to patient safety maneuvers. METHODS: Following observation of examination performance, root cause analysis of barriers, and review of consensus guidelines, an ictal examination was developed and disseminated. In accordance with quality improvement methodology, revisions were enacted following the initial intervention, including differentiation between pathways for convulsive and nonconvulsive seizures. We evaluated ictal examination fidelity, efficiency, and EMU staff satisfaction before and after the intervention. RESULTS: We identified barriers to ictal examination performance as confusion regarding ictal examination protocol, inadequate education of the rationale for the examination and its components, and lack of awareness of patient-specific goals. Over an 18-month period, 100 ictal examinations were reviewed, 50 convulsive and 50 nonconvulsive. Ictal examination performance varied during the study period without sustained improvement for convulsive or nonconvulsive seizure examination. The new examination was faster to perform (0.8 vs 1.5 minutes). Postintervention, EMU staff expressed satisfaction with the examination, but many still did not understand why certain components were performed. CONCLUSION: We identified key barriers to EMU ictal assessment and completed real-world testing of a standardized, streamlined ictal examination. We found it challenging to reliably change ictal examination performance in our EMU; further study of implementation is warranted.

Descending projections from the substantia nigra pars reticulata differentially control seizures.

Three decades of studies have shown that inhibition of the substantia nigra pars reticulata (SNpr) attenuates seizures, yet the circuits mediating this effect remain obscure. SNpr projects to the deep and intermediate layers of the superior colliculus (DLSC) and the pedunculopontine nucleus (PPN), but the contributions of these projections are unknown. To address this gap, we optogenetically silenced cell bodies within SNpr, nigrotectal terminals within DLSC, and nigrotegmental terminals within PPN. Inhibition of cell bodies in SNpr suppressed generalized seizures evoked by pentylenetetrazole (PTZ), partial seizures evoked from the forebrain, absence seizures evoked by gamma-butyrolactone (GBL), and audiogenic seizures in genetically epilepsy-prone rats. Strikingly, these effects were fully recapitulated by silencing nigrotectal projections. By contrast, silencing nigrotegmental terminals reduced only absence seizures and exacerbated seizures evoked by PTZ. These data underscore the broad-spectrum anticonvulsant efficacy of this circuit, and demonstrate that specific efferent projection pathways differentially control different seizure types.