Abstracts

Rationale: To help identify patients at greatest risk for sudden unexpected death in epilepsy (SUDEP), screening inventories can be useful. One such tool is the SUDEP-7 Inventory. Scores have previously been shown to correlate with reduced RMSSD, a measure of high frequency heart rate variability and a biomarker of vagus-mediated autonomic control of the heart. Some studies have raised concerns that one of the SUDEP-7 risk factors (>=3 AEDs) should not be considered an independent marker of SUDEP risk. In this study, we examined the strength of association between each of the 7 individual risk factors and postictal generalized electroencephalogram suppression (PGES), an electrophysiological biomarker of SUDEP risk.Methods: We performed a reanalysis of clinical and electrophysiologic data obtained from an epilepsy monitoring unit study of 37 children with focal dyscognitive and primary/secondarily generalized tonic clonic seizures (GTCS). In that study, the medical records of all children were reviewed to calculate SUDEP-7 Inventory scores (see Figure 1). We performed a 2 by 2 contingency table analysis to determine the strength of association between “yes” responses on each of the inventory questions and the presence of PGES of various durations (any, 30, 45, and 60 seconds) following at least one seizure. Pearson chi-square and Cramer’s V values were calculated.Results: Having a history of >3 GTCS in the past year had the strongest association with the recording of PGES (Pearson chi-square p<0.001, Cramer’s V=0.75). Having >=1 GTCS in the past year was also strongly associated with PGES of any duration (Pearson chi-square p<0.001, Cramer’s V=0.636). Histories of >50 seizures of any type per month (Pearson chi-square p=0.14, Cramer’s V=0.241) and intellectual disability (Pearson chi-square p=0.04, Cramer’s V=0.337) were not as robustly associated with PGES of any duration. Current use of >=3 AEDs had the weakest association with PGES of any duration (Pearson chi-square p=0.66, Cramer’s V=0.072, see Table 2). Given that all study patients had at least 1 seizure per year, the strength of association with this question and PGES could not be analyzed. Given that all study subjects were <=18 years of age, we could not analyze data regarding epilepsy duration >=30 years. When we excluded the question about current use of >=3 AEDs, the difference between inventory scores of those with PGES versus those without PGES became more significant (independent samples T test p=0.006 versus p=0.007).Conclusions: The inventory questions involving GTCS had the highest strength of association with PGES. This argues that historical risk factor inventories for SUDEP should take GTCS frequency and intractability into account. Conversely, the low strength of association between use of >=3 AEDs and PGES argues that this question may be of limited value in estimating SUDEP risk. Our results suggest the SUDEP risk inventory might benefit from eliminating the risk factor of >=3 AEDs. We believe changing the original SUDEP-7 inventory to a new inventory (the SUDEP Risk Inventory Version 2.0) is indicated.