Do patients need to stay in bed all day in the Epilepsy Monitoring Unit? Safety data from a non-restrictive setting

Crăciun, Laura; Alving, Jørgen; Gardella, Elena; Terney, Daniella; Meritam, Pirgit; Hribljan, Melita Čačić; Beniczky, Sándor

doi:10.1016/j.seizure.2017.05.006

Cited by 19 publications

(17 citation statements)

References 22 publications

(32 reference statements)

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“…We have analyzed video-EEG recordings, including surface EMGs from deltoid and biceps muscles, from consecutive patients admitted to the Epilepsy Monitoring Unit at the Danish Epilepsy Centre. 23 Patients who had at least 1 CS during monitoring (defined as bilateral tonic or clonic jerks) that was documented with the video-EEG-EMG recordings were included. Exclusion criterion was age <1 year.…”

Section: Patients and Recordingsmentioning

confidence: 99%

Ictal quantitative surface electromyography correlates with postictal EEG suppression

et al. 2020

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ObjectiveTo test the hypothesis that neurophysiologic biomarkers of muscle activation during convulsive seizures reveal seizure severity and to determine whether automatically computed surface EMG parameters during seizures can predict postictal generalized EEG suppression (PGES), indicating increased risk for sudden unexpected death in epilepsy. Wearable EMG devices have been clinically validated for automated detection of generalized tonic-clonic seizures. Our goal was to use quantitative EMG measurements for seizure characterization and risk assessment.MethodsQuantitative parameters were computed from surface EMGs recorded during convulsive seizures from deltoid and brachial biceps muscles in patients admitted to long-term video-EEG monitoring. Parameters evaluated were the durations of the seizure phases (tonic, clonic), durations of the clonic bursts and silent periods, and the dynamics of their evolution (slope). We compared them with the duration of the PGES.ResultsWe found significant correlations between quantitative surface EMG parameters and the duration of PGES (p < 0.001). Stepwise multiple regression analysis identified as independent predictors in deltoid muscle the duration of the clonic phase and in biceps muscle the duration of the tonic-clonic phases, the average silent period, and the slopes of the silent period and clonic bursts. The surface EMG-based algorithm identified seizures at increased risk (PGES ≥20 seconds) with an accuracy of 85%.ConclusionsIctal quantitative surface EMG parameters correlate with PGES and may identify seizures at high risk.Classification of evidenceThis study provides Class II evidence that during convulsive seizures, surface EMG parameters are associated with prolonged postictal generalized EEG suppression.

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Section: Patients and Recordingsmentioning

confidence: 99%

Ictal quantitative surface electromyography correlates with postictal EEG suppression

et al. 2020

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“…However, mobility of the patients was not restricted during monitoring, and they were encouraged to perform indoors physical activities similar to their habitual lifestyle. 21 …”

Section: Discussionmentioning

confidence: 99%

“…The mobility of the patients was not restricted in the EMUs, where patients were free to perform their habitual physical activities and participate in activities such as using an exercise bicycle, preparing coffee or food, and playing home video games involving body motion (Nintendo [Kyoto, Japan] Wii). 21 Patients were under continuous surveillance and no injuries occurred during monitoring.…”

Section: Methodsmentioning

confidence: 99%

Automated real-time detection of tonic-clonic seizures using a wearable EMG device

et al. 2018

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ObjectiveTo determine the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) using a wearable surface EMG device.MethodsWe prospectively tested the technical performance and diagnostic accuracy of real-time seizure detection using a wearable surface EMG device. The seizure detection algorithm and the cutoff values were prespecified. A total of 71 patients, referred to long-term video-EEG monitoring, on suspicion of GTCS, were recruited in 3 centers. Seizure detection was real-time and fully automated. The reference standard was the evaluation of video-EEG recordings by trained experts, who were blinded to data from the device. Reading the seizure logs from the device was done blinded to all other data.ResultsThe mean recording time per patient was 53.18 hours. Total recording time was 3735.5 hours, and device deficiency time was 193 hours (4.9% of the total time the device was turned on). No adverse events occurred. The sensitivity of the wearable device was 93.8% (30 out of 32 GTCS were detected). Median seizure detection latency was 9 seconds (range −4 to 48 seconds). False alarm rate was 0.67/d.ConclusionsThe performance of the wearable EMG device fulfilled the requirements of patients: it detected GTCS with a sensitivity exceeding 90% and detection latency within 30 seconds.Classification of evidenceThis study provides Class II evidence that for people with a history of GTCS, a wearable EMG device accurately detects GTCS (sensitivity 93.8%, false alarm rate 0.67/d).

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“…Only very few multicenter, prospective, blinded phase 3 studies have provided compelling evidence of effective real‐time seizure detection . These studies are typically conducted in epilepsy monitoring units (EMUs), which differ from the natural home environment, in particular regarding patients’ mobility . Thus, it has been proposed that phase 3 validation studies are followed by field studies (phase 4) in the patients′ home environment, addressing issues of applicability and usability from patients’ and caregivers’ perspective …”

Section: Introductionmentioning

confidence: 99%

“…9 These studies are typically conducted in epilepsy monitoring units (EMUs), which differ from the natural home environment, in particular regarding patients' mobility. 11 Thus, it has been proposed that phase 3 validation studies are followed by field studies (phase 4) in the patients 0 home environment, addressing issues of applicability and usability from patients' and caregivers' perspective. 10 Here, we present a field study of a wrist-worn accelerometer-based seizure detection device (Epi-Care; Danish Care Technology, Sorø, Denmark).…”

Section: Introductionmentioning

confidence: 99%

User‐based evaluation of applicability and usability of a wearable accelerometer device for detecting bilateral tonic–clonic seizures: A field study

Meritam¹,

Ryvlin

Beniczky

2018

Epilepsia

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Clinical validation studies of seizure detection devices conducted in epilepsy monitoring units (EMUs) can be biased by the artificial environment. We report a field (phase 4) study of a wearable accelerometer device (Epi-Care) that has previously been validated in EMUs for detecting bilateral tonic-clonic seizures (BTCS). Seventy-one patients using the device (or their caregivers) completed the modified Post-Study System Usability Questionnaire. Median time patients had been using the device was 15 months (range = 24 days-6 years). In 10% of cases, patients stopped using the device due to reasons related to the device. The median sensitivity (90%) and false alarm rate (0.1/d) were similar to what had been determined in EMUs. Patients and caregivers were overall satisfied with the device (median = 5.5 on the 7-point Likert scale), considered the technical aspects satisfactory, and considered the device comfortable and efficient. Adverse effects occurred in 11%, but were only mild: skin irritation at the wrist and interference with home electronic appliances. In 55% the device influenced the number of seizures logged into the seizure diary, and in 40% it contributed to fewer seizure-related injuries. This field study demonstrates the applicability and usability of the wearable accelerometer device for detecting BTCS.

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Do patients need to stay in bed all day in the Epilepsy Monitoring Unit? Safety data from a non-restrictive setting

Abstract: In an EMU specially designed for this purpose, where patients are under continuous surveillance by personnel dedicated to the EMU, injuries can be avoided even when the mobility of the patients is not restricted.

Cited by 19 publications

References 22 publications

Ictal quantitative surface electromyography correlates with postictal EEG suppression

Ictal quantitative surface electromyography correlates with postictal EEG suppression

Automated real-time detection of tonic-clonic seizures using a wearable EMG device

User‐based evaluation of applicability and usability of a wearable accelerometer device for detecting bilateral tonic–clonic seizures: A field study

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