Cyclical underreporting of seizures in patient‐based seizure documentation

Abstract

ObjectiveCircadian and multidien cycles of seizure occurrence are increasingly discussed as to their biological underpinnings and in the context of seizure forecasting. This study analyzes if patient reported seizures provide valid data on such cyclical occurrence.MethodsWe retrospectively studied if circadian cycles derived from patient‐based reporting reflect the objective seizure documentation in 2003 patients undergoing in‐patient video‐EEG monitoring.ResultsOnly 24.1% of more than 29000 seizures documented were accompanied by patient notifications. There was cyclical underreporting of seizures with a maximum during nighttime, leading to significant deviations in the circadian distribution of seizures. Significant cyclical deviations were found for focal epilepsies originating from both, frontal and temporal lobes, and for different seizure types (in particular, focal unaware and focal to bilateral tonic–clonic seizures).InterpretationPatient seizure diaries may reflect a cyclical reporting bias rather than the true circadian seizure distributions. Cyclical underreporting of seizures derived from patient‐based reports alone may lead to suboptimal treatment schemes, to an underestimation of seizure‐associated risks, and may pose problems for valid seizure forecasting. This finding strongly supports the use of objective measures to monitor cyclical distributions of seizures and for studies and treatment decisions based thereon.

High precision in epileptic seizure self-reporting with an app diary

“…Poor documentation sensitivity, indicating underreporting, is primarily attributed to seizure-induced lack of awareness and nocturnal seizures 7 . Schulze-Bonhage et al 8 recently confirmed circadian effects of underreporting seizures, aligning with our findings. Furthermore, Kerling et al 31 had already shown that seizures during sleep are significantly less reported compared to awake seizures.…”

“…Despite this significant role of seizure diaries, previous research has shown that about 50% of seizures are not documented 6 , 7 . This phenomenon of underreporting may be caused by seizure-induced lack of awareness, postictal inability to recall seizures, particularly during nighttime 8 , or by adverse drug effects 7 . Meanwhile, seizure overreporting is less commonly reported 6 , yet may additionally have a negative impact on the precision and validity of patient-based seizure documentation.…”

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“…However, evidence has been accumulated that reported seizure frequencies are often invalid, as patients underreport even severe seizure types and seizures occurring at night, when they bear the highest SUDEP risk. [1][2][3] For objective seizure documentation, in-hospital monitoring using video-EEG surveillance is considered the gold standard when a discrepancy between patient-based documentation and actual seizure load is suspected. The duration of such in-patient video-EEG monitoring is mostly limited to a period of 1-2 weeks, which again may lead to an undersampling of seizures 4,5 and may not represent the situation under real life conditions.…”

The present and future of seizure detection, prediction, and forecasting with machine learning, including the future impact on clinical trials

“…Those circadian cycles also are present in seizures observed in continuous video-EEG monitoring units and critical care ( 40 , 103 , 104 , 108 , 109 ). However, these circadian cycles may not be as prominent as suggested by the data, because there may be a confound of circadian under-reporting of seizures (e.g., nocturnal focal aware seizures are missed because patients are sleeping, causing the data to suggest that focal aware seizures only occur during the day) ( 110 ).…”