Utilizing risk-controlling prediction calibration to reduce false alarm rates in epileptic seizure prediction

IntroductionEpilepsy is a neurological disease characterized by sudden, unprovoked seizures. The unexpected nature of epileptic seizures is a major component of the disease burden. Predicting seizure onset and alarming patients may allow timely intervention, which would improve clinical outcomes and patient quality of life. Currently, algorithms aiming to predict seizures suffer from a high false alarm rate, rendering them unsuitable for clinical use.MethodsWe adopted here a risk-controllingprediction calibration method called Learn then Test to reduce false alarm rates of seizure prediction. This method calibrates the output of a “black-box” model to meet a specified false alarm rate requirement. The method was initially validated on synthetic data and subsequently tested on publicly available electroencephalogram (EEG) records from 15 patients with epilepsy by calibrating the outputs of a deep learning model.Results and discussionValidation showed that the calibration method rigorously controlled the false alarm rate at a user-desired level after our adaptation. Real data testing showed an average of 92% reduction in the false alarm rate, at the cost of missing four of nine seizures of six patients. Better-performing prediction models combined with the proposed method may facilitate the clinical use of real-time seizure prediction systems

DataSheet1_Ca2+ pushes and pulls energetics to maintain ATP balance in atrial cells: computational insights.docx

To maintain atrial function, ATP supply-to-demand matching must be tightly controlled. Ca2+ can modulate both energy consumption and production. In light of evidence suggesting that Ca2+ affects energetics through “push” (activating metabolite flux and enzymes in the Krebs cycle to push the redox flux) and “pull” (acting directly on ATP synthase and driving the redox flux through the electron transport chain and increasing ATP production) pathways, we investigated whether both pathways are necessary to maintain atrial ATP supply-to-demand matching. Rabbit right atrial cells were electrically stimulated at different rates, and oxygen consumption and flavoprotein fluorescence were measured. To gain mechanistic insight into the regulators of ATP supply-to-demand matching in atrial cells, models of atrial electrophysiology, Ca2+ cycling and force were integrated with a model of mitochondrial Ca2+ and a modified model of mitochondrial energy metabolism. The experimental results showed that oxygen consumption increased in response to increases in the electrical stimulation rate. The model reproduced these findings and predicted that the increase in oxygen consumption is associated with metabolic homeostasis. The model predicted that Ca2+ must act both in “push” and “pull” pathways to increase oxygen consumption. In contrast to ventricular trabeculae, no rapid time-dependent changes in mitochondrial flavoprotein fluorescence were measured upon an abrupt change in workload. The model reproduced these findings and predicted that the maintenance of metabolic homeostasis is due to the effects of Ca2+ on ATP production. Taken together, this work provides evidence of Ca2+ “push” and “pull” activity to maintain metabolic homeostasis in atrial cells.</p