使用表皮肌电监测来检测全面强直-阵挛发作_Journal of Epilepsy

Authors：

 Jonathan JHalford , Michael RSperling , Dileep RNair , 童馨　译 , 高慧　慕洁　审

Corresponding author：

Jonathan JHalford, Email: halfordj@musc.edu

Keywords：

临床试验; 癫痫监测; 全面性癫痫发作; 痉挛; 大发作; 可穿戴

DOI：

10.7507/2096-0247.20180044

Video：

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该前瞻性多中心Ⅲ期临床试验的目的在于评估在癫痫监测单元（Epilepsy monitoring unit，EMU）中使用可穿戴的表皮肌电图（surface electromyographic，sEMG）监测系统来检测全面强直-阵挛发作（Generalized tonic–clonic seizures，GTCS）的性能和耐受性。199 例有 GTCS 病史的患者被收入 11 个Ⅳ级癫痫中心的 EMU 中，在进行临床视频脑电图（VEEG）监测的同时，也通过在肱二头肌上佩戴可穿戴设备接受了 sEMG 监测。所有 sEMG 数据记录都使用先前开发的检测算法在中心站点处理。将 sEMG 检测到的 GTCS 与 3 名评审专家验证的发作事件进行比较。在所有受试者中，检测算法共检测到了 46 次 GTCS 中的 35 次［76%，95%CI（0.61，0.87）］，阳性预测值（Positive predictive value，PPV）为 0.03，平均误报率（False alarm rate，FAR）为 2.52/24 h。对于在肱二头肌中线上方记录到的数据，系统检测到了全部的 29 例 GTCS［100%，95%CI（0.88，1.00）］，检测时间平均延迟 7.70 s，PPV 为 6.2%，平均 FAR 为 1.44/24 h。28%（55/199）报告了轻至中度的不良事件，并导致 9% 的研究中止（17/199）。这些不良事件主要是电极贴片引起的皮肤刺激反应，这种情况未经治疗即可缓解。研究中无严重不良事件报告。在肱二头肌上使用 sEMG 监测装置来检测 GTCS 是可行的。正确放置该装置对于检测准确性至关重要，但是对于一些患者而言，减少误报数仍有一定难度。

Citation： Jonathan JHalford, Michael RSperling, Dileep RNair, 童馨　译, 高慧　慕洁　审. 使用表皮肌电监测来检测全面强直-阵挛发作. Journal of Epilepsy, 2018, 4(3): 249-256. doi: 10.7507/2096-0247.20180044 Copy

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3.	Friedman DE, Tobias RS, Akman CI, et al. Recurrent seizure-related injuries in people with epilepsy at a tertiary epilepsy center: a 2-year longitudinal study. Epilepsy Behav, 2010, 19(3): 400-404.
4.	Hesdorffer DC, Tomson T, Benn E, et al. Do antiepileptic drugs or generalized tonic-clonic seizure frequency increase SUDEP risk? A combined analysis. Epilepsia, 2012, 53(2): 249-252.
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6.	DeLorenzo RJ, Hauser WA, Towne AR, et al. A prospective, population-based epidemiologic study of status epilepticus in richmond, virginia. Neurology, 1996, 46(4): 1029-1035.
7.	Chen JW, Wasterlain CG. Status epilepticus: pathophysiology and management in adults. Lancet Neurol, 2006, 5(3): 246-256.
8.	Lamberts RJ, Thijs RD, Laffan A, et al. Sudden unexpected death in epilepsy: people with nocturnal seizures may be at highest risk. Epilepsia, 2012, 53(2): 253-257.
9.	Conradsen I, Wolf P, Sams T, et al. Patterns of muscle activation during generalized tonic and tonic-clonic epileptic seizures. Epilepsia, 2011, 52(11): 2125-2132.
10.	Szabo CA, Morgan LC, Karkar KM, et al. Electromyography-based seizure detector: preliminary results comparing a generalized tonic-clonic seizure detection algorithm to video-EEG recordings. Epilepsia, 2015, 56(9): 1432-1437.
11.	National Association of Epilepsy Centers. Overview of the NAEC. Available at: http://www.naec-epilepsy.org/about-naec/overview/2007. Accessed February 28, 2017.
12.	Bossuyt PM, Reitsma JB, Bruns DE, et al. STARD2015: an updated list of essential items for reporting diagnostic accuracy studies. Radiology, 2015, 277(3): 826-832.
13.	Team RDC. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available at: http://www.R-project.org. Accessed September 19, 2017.
14.	Berg AT, Berkovic SF, Brodie MJ, et al. Revised terminology and concepts for organization of seizures and epilepsies: report of the ILAE commission on classification and terminology, 2005-2009. Epilepsia, 2010, 51(4): 676-685.
15.	Gwet KL. Computing inter-rater reliability and its variance in the presence of high agreement. Br J Math Stat Psychol, 2008, 61(Pt 1): 29-48.
16.	Beniczky S, Polster T, Kjaer TW, et al. Detection of generalized tonic-clonic seizures by a wireless wrist accelerometer: a prospective, multicenter study. Epilepsia, 2013, 54(4): e58-e61.
17.	Velez M, Fisher RS, Bartlett V, et al. Tracking generalized tonic-clonic seizures with a wrist accelerometer linked to an online database. Seizure, 2016, 39: 13-18.
18.	Patterson AL, Mudigoudar B, Fulton S, et al. SmartWatch by SmartMonitor: assessment of seizure detection efficacy for various seizure types in children, a large prospective single-center study. Pediatr Neurol, 2015, 53(4): 309-311.
19.	Hoppe C, Feldmann M, Blachut B, et al. Novel techniques for automated seizure registration: patients’ wants and needs. Epilepsy Behav, 2015, 52(Pt A): 1-7.
20.	Van de Vel A, Smets K, Wouters K, et al. Automated non-EEG based seizure detection: do users have a say?. Epilepsy Behav, 2016, 62: 121-128.
21.	Study conducted by User View. Raleigh, NC.

1. Picot MC, Baldy-Moulinier M, Daurès JP, et al. The prevalence of epilepsy and pharmacoresistant epilepsy in adults: a population-based study in a western european country. Epilepsia, 2008, 49(7): 1230-1238.
2. Tomson T, Beghi E, Sundqvist A, et al. Medical risks in epilepsy: a review with focus on physical injuries, mortality, traffic accidents and their prevention. Epilepsy Res, 2004, 60(1): 1-16.
3. Friedman DE, Tobias RS, Akman CI, et al. Recurrent seizure-related injuries in people with epilepsy at a tertiary epilepsy center: a 2-year longitudinal study. Epilepsy Behav, 2010, 19(3): 400-404.
4. Hesdorffer DC, Tomson T, Benn E, et al. Do antiepileptic drugs or generalized tonic-clonic seizure frequency increase SUDEP risk? A combined analysis. Epilepsia, 2012, 53(2): 249-252.
5. Lhatoo SD, Johnson AL, Goodridge DM, et al. Mortality in epilepsy in the first 11 to 14 years after diagnosis: multivariate analysis of a long-term, prospective, population based cohort. Ann Neurol, 2001, 49(3): 336-344.
6. DeLorenzo RJ, Hauser WA, Towne AR, et al. A prospective, population-based epidemiologic study of status epilepticus in richmond, virginia. Neurology, 1996, 46(4): 1029-1035.
7. Chen JW, Wasterlain CG. Status epilepticus: pathophysiology and management in adults. Lancet Neurol, 2006, 5(3): 246-256.
8. Lamberts RJ, Thijs RD, Laffan A, et al. Sudden unexpected death in epilepsy: people with nocturnal seizures may be at highest risk. Epilepsia, 2012, 53(2): 253-257.
9. Conradsen I, Wolf P, Sams T, et al. Patterns of muscle activation during generalized tonic and tonic-clonic epileptic seizures. Epilepsia, 2011, 52(11): 2125-2132.
10. Szabo CA, Morgan LC, Karkar KM, et al. Electromyography-based seizure detector: preliminary results comparing a generalized tonic-clonic seizure detection algorithm to video-EEG recordings. Epilepsia, 2015, 56(9): 1432-1437.
11. National Association of Epilepsy Centers. Overview of the NAEC. Available at: http://www.naec-epilepsy.org/about-naec/overview/2007. Accessed February 28, 2017.
12. Bossuyt PM, Reitsma JB, Bruns DE, et al. STARD2015: an updated list of essential items for reporting diagnostic accuracy studies. Radiology, 2015, 277(3): 826-832.
13. Team RDC. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available at: http://www.R-project.org. Accessed September 19, 2017.
14. Berg AT, Berkovic SF, Brodie MJ, et al. Revised terminology and concepts for organization of seizures and epilepsies: report of the ILAE commission on classification and terminology, 2005-2009. Epilepsia, 2010, 51(4): 676-685.
15. Gwet KL. Computing inter-rater reliability and its variance in the presence of high agreement. Br J Math Stat Psychol, 2008, 61(Pt 1): 29-48.
16. Beniczky S, Polster T, Kjaer TW, et al. Detection of generalized tonic-clonic seizures by a wireless wrist accelerometer: a prospective, multicenter study. Epilepsia, 2013, 54(4): e58-e61.
17. Velez M, Fisher RS, Bartlett V, et al. Tracking generalized tonic-clonic seizures with a wrist accelerometer linked to an online database. Seizure, 2016, 39: 13-18.
18. Patterson AL, Mudigoudar B, Fulton S, et al. SmartWatch by SmartMonitor: assessment of seizure detection efficacy for various seizure types in children, a large prospective single-center study. Pediatr Neurol, 2015, 53(4): 309-311.
19. Hoppe C, Feldmann M, Blachut B, et al. Novel techniques for automated seizure registration: patients’ wants and needs. Epilepsy Behav, 2015, 52(Pt A): 1-7.
20. Van de Vel A, Smets K, Wouters K, et al. Automated non-EEG based seizure detection: do users have a say?. Epilepsy Behav, 2016, 62: 121-128.
21. Study conducted by User View. Raleigh, NC.

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使用表皮肌电监测来检测全面强直-阵挛发作

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