Automated seizure detection with noninvasive wearable devices: A systematic review and meta-analysis.

Objective: This study was undertaken to review the reported performance of noninvasive wearable devices in detecting epileptic seizures and psychogenic nonepileptic seizures (PNES).

Methods: We conducted a systematic review and meta-analysis of studies reported up to November 15, 2021. We included studies that used video-electroencephalographic (EEG) monitoring as the gold standard to determine the sensitivity and false alarm rate (FAR) of noninvasive wearables for automated seizure detection.

Acute illness in patients with concomitant Addison's disease and type 1 diabetes mellitus: Increased incidence of hypoglycaemia and adrenal crises.

Background: Patients with Addison's disease (AD) and comorbid type 1 diabetes mellitus (T1DM) are at increased risk of certain acute metabolic disorders relative to patients with one of these conditions only. The reasons for this are unknown.

Methods: All attendances for acute illness by AD patients at the emergency department of a Sydney hospital between 2000 and 2017 were reviewed.

The utility of an automated and ambulatory device for detecting and differentiating epileptic and psychogenic non-epileptic seizures.

Objective: Accurate differentiation between epileptic seizures (ES) and psychogenic non-epileptic seizures (PNES) can be challenging based on history alone. Inpatient video EEG monitoring (VEM) is often needed for a definitive diagnosis. However, VEM is highly resource intensive, is of limited availability, and cannot be undertaken over long periods.