Length of stay linked to neurodiagnostic workup for seizures presenting to the pediatric emergency department

Point-of-care electroencephalography enables rapid evaluation and management of non-convulsive seizures and status epilepticus in the emergency department

Objectives

To describe our institutional experience with point-of-care electroencephalography (pocEEG) and its impact on the evaluation/management of suspected non-convulsive seizures in the emergency department (ED).

Methods

We retrospectively identified 157 adults who underwent pocEEG monitoring in our community hospital ED in 1 year. We calculated the time to obtain pocEEG in the ED (door-to-EEG time) and examined the impact of pocEEG findings (categorized as seizure, highly epileptiform patterns, slowing, or normal activity) on antiseizure medication treatment.

Results

PocEEG revealed seizures (14%, n = 22), highly epileptiform patterns (22%, n = 34), slowing (44%, n = 69), and normal activity (20%, n = 32). The median door-to-EEG time (from initial ED evaluation to pocEEG monitoring) was only 1.2 hours (interquartile range 0.1-2.1) even though 55% of studies were performed after-hours (5 pm-9 am). Most patients were admitted (54% to the intensive care unit, 41% to floor). Antiseizure medication treatment occurred pre-pocEEG in 93 patients (59%) and post-pocEEG in 88 patients (56%). By reviewing the relationship between pocEEG monitoring and antiseizure medication management, we found a significant association between pocEEG findings and changes in management (P < 0.001). Treatment escalation occurred more frequently in patients with epileptiform activity (seizures or highly epileptiform patterns, 52%) than patients with non-epileptiform activity (normal or slow, 25%, P < 0.001), and avoidance of treatment escalation occurred more frequently in patients with normal or slow activity (27%) than patients with seizures or highly epileptiform patterns (2%, P < 0.001).

Conclusion

Our study, the largest to date describing the real-world use of pocEEG in emergency medicine, found that rapid EEG acquisition in the ED was feasible in a community hospital and significantly affected the management of suspected non-convulsive seizures.

ES-RED (Early Seizure Recurrence in the Emergency Department) Calculator: A Triage Tool for Seizure Patients

Seizure is a common neurological presentation in patients visiting the emergency department (ED) that requires time for evaluation and observation. Timely decision and disposition standards for seizure patients need to be established to prevent overcrowding in the ED and achieve patients’ safety. Here, we conducted a retrospective cohort study to predict early seizure recurrence in the ED (ES-RED). We randomly assigned 688 patients to the derivation and validation cohorts (2:1 ratio). Prediction equations extracted routine clinical and laboratory information from EDs using logistic regression (Model 1) and machine learning (Model 2) methods. The prediction equations showed good predictive performance, the area under the receiver operating characteristics curve showing 0.808 in Model 1 [95% confidential interval (CI): 0.761–0.853] and 0.805 in Model 2 [95% CI: 0.747–0.857] in the derivation cohort. In the external validation, the models showed strong prediction performance of 0.739 [95% CI: 0.640–0.824] in Model 1 and 0.738 [95% CI: 0.645–0.819] in Model 2. Intriguingly, the lowest quartile group showed no ES-RED after 6 h. The ES-RED calculator, our proposed prediction equation, would provide strong evidence for safe and appropriate disposition of adult resolved seizure patients from EDs, reducing overcrowding and delays and improving patient safety.

Multiscale pore contained carbon nanofiber-based field-effect transistor biosensors for nesfatin-1 detection

Nesfatin-1 (NES1) is a potential biomarker found in serum and saliva that indicates hyperpolarization and depolarization in the hypothalamic ventricle nucleus as well as an increase in epileptic conditions. However, real-time investigations have not been carried out to detect changes in the concentration of NES1. In this study, we develop a multiscale pore contained carbon nanofiber-based field-effect transistor (FET) biosensor to detect NES1. The activated multiscale pore contained carbon nanofiber (a-MPCNF) is generated using a single-nozzle co-electrospinning method and a subsequent steam-activation process to obtain a signal transducer and template for immobilization of bioreceptors. The prepared biosensor exhibits a high sensitivity to NES1. It can detect levels as low as 0.1 fM of NES1, even in the presence of other interfering biomolecules. Furthermore, the a-MPCNF-based FET sensor has significant potential for practical applications in non-invasive real-time diagnosis, as indicated by its sensing performance in artificial saliva.