Incorporating cardiac, EEG, and other variables
Various other factors may warrant inclusion in a seizure forecasting system. A new vagus nerve stimulation system responds to heart rate changes that occur at seizure onset. And for decades, researchers have studied the potential for EEG readings to predict seizures. A 2008 analysis of 47 reports concluded that limited progress had been made in predicting a seizure from interictal EEG (Epilepsy Behav. 2008 Jan;12[1]:128-35). Now, however, long-term intracranial recordings are providing new and important information about EEG patterns.
Whereas early studies examined EEG recordings from epilepsy monitoring units – when patients may have been sleep deprived, had medications removed, or recently undergone surgery – chronic intracranial recordings from devices such as the RNS (responsive neurostimulation) System have allowed researchers to look long term at EEG changes that are more representative of patients’ typical EEG patterns.
The RNS System detects interictal spikes and seizure discharges and then provides an electrical stimulation to stop seizures. “When you look at these recordings, there are a lot more electrographic seizures than clinical seizures that trigger these stimulations,” said Dr. Privitera. “If you look at somebody with a typical RNS, they may have 100 stimulations in a day and no clinical seizures. There are lots and lots of subclinical electrographic bursts – and not just spikes, but things that look like short electrographic seizures – that occur throughout the day.”
A handheld device
Researchers in Melbourne designed a system that uses implanted electrodes to provide chronic recordings (Lancet Neurol. 2013 Jun;12[6]:563-71). An algorithm then learned to predict the likelihood of a seizure from the patient’s data as the system recorded over time. The system could indicate when a seizure was likely by displaying a light on a handheld device. Patients were recorded for between 6 months and 3 years.
“There was a statistically significant ability to predict when seizures were happening,” Dr. Privitera said. “There is information in long-term intracranial recordings in many of these people that will help allow us to do a better prediction than what we are able to do right now, which is essentially not much.”
This research suggests that pooling data across patients may not be an effective seizure prediction strategy because different epilepsy types have different patterns. In addition, an individual’s patterns may differ from a group’s patterns. Complicating matters, individual patients may have multiple seizure types with different onset mechanisms.
“Another important lesson is that false positives in a deterministic sense may not represent false positives in a probabilistic sense,” Dr. Privitera said. “That is, when the seizure prediction program – whether it is the diary or the intracranial EEG or anything else – says the threshold changed, but you did not have a seizure, it does not mean that your prediction system was wrong. If the seizure tendency is going up … and your system says the seizure tendency went up, but all you are measuring is actual seizures, it looks like it is a false positive prediction of seizures. But in fact it is a true positive prediction of the seizure tendency changing but not necessarily reaching seizure threshold.”
