EEG trong chẩn đoán và điều trị động kinh - Bs Mã Lệ Quân.pptx

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dien nao do
điện não
động kinh

1. TRONG CHẨN ĐOÁN VÀ THEO DÕI ĐIỀU TRỊ ĐỘNG KINH Bs Mã Lệ Quân

2. NỘI DUNG Vai trò của EEG EEG trong chẩn đoán động kinh EEG trong theo dõi điều trị động kinh

3. Vai trò Chẩn đoán cơn co giật lần đầu, định khu và phân loại ĐK Theo dõi ĐK và trạng thái ĐK Chẩn đoán trong hôn mê

4. Focal interictal epileptiform discharges - IEDs

5. Gai <70ms Nhọn 70-200ms Sóng chậm >200ms Hoạt động nhanh kịch phát

6. Dạng nhọn Thời gian 70-200ms Không đối xứng, dốc h ơ n ở pha đầu và lài h ơ n ở pha sau Theo sau bởi sóng chậm Điện thế cao h ơ n so với hoạt động nền xung quanh Sóng âm có điện thế đối pha theo vị trí giải phẫu. Nick Kane et col, Clinical Neurophysiology Practice, 2017 Aug 4;2:170-185

7. Mustafa Aykut Kural et al. Neurology 2020;94:e2139-e2147

8. Figure 3 Receiver operating characteristic (ROC) curve Mustafa Aykut Kural et al. Neurology 2020;94:e2139-e2147 Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

9. We evaluated the accuracy of 63 combinations of the IFCN criteria. We found that using any of the three specific combinations of the IFCN-criteria for defining spikes resulted in high specificity (97%). One set had four criteria (1–2–4–6) and two sets had three criteria (1–2–4 and 1–4–6). However, two sets of criteria had significantly lower sensitivity compared to unrestricted expert scorings. The set that yielded both high specificity (97%) and sensitivity (89%) was 1–4–6 : waves with spiky morphology, followed by a slow-afterwave and voltage map suggesting a source in the brain. Mustafa Aykut   Kura et col, Clinical Neurophysiology, Volume 131, Issue 9, September 2020, Pages 2250-2254 Optimized set of criteria for defining IEDs

10. Vertex sharp transients Lambda waves Wicket spikes Positive occipital sharp transients of sleep 6 Hz spike - slow wave (WHAM, FOLD)

11. 1. Nhọn Vertex Tần số: thoáng qua, có thể thành chuỗi, kéo dài đến 3s. Biên độ: thấp – 90 microvolt, nhủ nhi có thể cao đến 250microV Hình thái: sóng nhọn 1 pha âm, thời khoảng 100ms . Phân bố: chủ yếu trung tâm - Cz, có thể lan ra 2 bên (trung tâm, trán, TD, đính), có thể không đối x ứng. Hoàn cảnh xuất hiện: giai đoạn ngủ NREM

12. Tần số: thoáng qua Biên độ: thấp Hình thái: sóng nhọn 2 hoặc 3 pha, thời khoảng 0.2s - 0.5s. Phân bố: chủ yếu vùng chẩm, có thể vùng thái dương sau và đính. Phản ứng: chỉ xuất hiện khi mở mắt, nhìn chằm chằm vào 1 vật thể, mất khi nhắm mắt. Hoàn cảnh xuất hiện: 3-12 tuổi (80%) 15 2. Sóng lambda

13. 16

14. Tần số: 6-11Hz Biên độ: 60-200 microvolt Hình thái: đợt sóng đơn pha hình cung hoặc các nhọn đơn độc giống hoạt động Mu. Phân bố: ưu thế vùng thái dương, có thể có 2 bên. Đáp ứng: không phản ứng với các kích thích. Hoàn cảnh xuất hiện: > 50 tuổi; khi bắt đầu ngủ. 3. Các nhọn hình hàng rào (Wicket spikes)

15. 18

16. Biên độ: 20-75 microvolt Hình thái: một/hai pha . Phân bố: vùng chẩm 1 hoặc 2 bên, không đối x ứng, có lan ra vùng lân cận. Hoàn cảnh xuất hiện: NREM-1, hiếm trong REM. Đáp ứng: mất trong giai đoạn ngủ sâu. Hiếm ở ng ư ời >70 tuổi. 4. Positive occipital sharp transients of sleep - POSTs

17. Tần số: 4-7Hz Biên độ: < 50microvolt Hình thái: đặc trưng là các thành phần nhọn biên độ thấp lúc có lúc không  phantom. T heo sau bằng 1 sóng chậm. WHAM (Waking, High amplitude spike (>45 V) Anterior in Male ) FOLD (Female Occipital Low amplitude spike in Drowsy) Giới Phân bố Hoàn cảnh xuất hiện Nam giới Vùng trán Lúc thức Nữ giới Phía sau, 2 bên. Giai đoạn buồn ngủ, mất khi ngủ sâu. 21 5. Gai sóng 6Hz (Phantom spike)

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20. Hoạt động nhanh kịch phát Paroxymal fast activity - PFA Là 1 dạng của hoạt động tần số  , có thể khu trú / toàn thể. Đặc trưng: Kịch phát Tần số nhanh (15-25Hz) Theo nhịp hay không Thay đổi điện thế so với hoạt động nền (thường > 100 V, hiếm  40 V ) Kéo dài: 0.25s-2s (khu trú); 3-18s (toàn thể). Kết thúc đột ngột, có thể theo sau bởi sóng chậm. Ý nghĩa: PFA càng kéo dài càng có ý nghĩa trong cơn ĐK.

21. 21yo chậm PT tâm thần, ĐK Focal PFA – T4

22. 11mo boy Infantile Spasm

23. PFA kéo dài, tiến triển thành cơn ĐK

24. Generalized IEDs 3 per second spike (and slow) wave complexes Slow spike and waves Fast spike and waves Polyspike and (slow) wave complexes Hypsarrhythmia

25. Đặc điểm chung Gồm phức hợp: gai + sóng chậm (hình vòm) Giữa các phức hợp có khoảng võng xuống, 30-60ms Trong lúc ngủ: biên độ cao h ơ n nh ư ng tần số xuất hiện ít h ơ n, thu hẹp vùng phân bố. Tần số: lấy 3Hz làm chuẩn; cao h ơ n  nhanh, chậm h ơ n  chậm.

26. A 7-year old with absence seizures and rare myoclonus. Generalized Interictal Epileptiform Discharge Spike and slow wave complexes occur at 3 Hz during hyperventilation, which is evident in the hypersynchronous slow background activity. The discharges follow a high-amplitude spike and have maximal amplitude and clearest waveform in the midline frontocentral region.

27. A 16-year old who is seizure free and has a history of absence seizures. Generalized Interictal Epileptiform Discharges Polyspikes precede the first spike and slow wave complex and some of the subsequent complexes also have initiating polyspikes in individual channels. The complexes are high amplitude at approximately 200 μV, and the alpha rhythm and background are normal amplitude but appear low amplitude because of the vertical scale necessary to visualize the epileptiform discharges.

28. Generalized Interictal Epileptiform Discharge

29. A 42-year old with a 21-year history of absence and generalized tonic–clonic seizures. Asymmetric Slow Spike and Slow Wave Interictal Epileptiform Discharges The spike and slow wave complex recurs at 2 Hz , has a poorly formed spike component, and is consistently, asymmetrically better formed on the left side. Sharp waves with phase reversal at the T3 electrode have been noted on this patient’s other EEGs, suggesting possible secondary bilateral synchrony as the cause for the generalized spike and slow wave complexes.

30. An 18-year old with poorly controlled absence seizures and a history of six generalized tonic–clonic seizures. Generalized Interictal Epileptiform Discharges One complex of generalized polyspikes followed by slow wave occurs in isolation and is later followed by a 1 second run of generalized spike and slow wave complexes that occur with a frequency of 4 Hz.

31. Loạn nhịp cao thế - Hypsarrhythmia 4 tháng – 2 tuổi, hiếm ở sơ sinh Biên độ 200-400microV, có khi cao h ơ n 1000 microV Hoạt động nền vô tổ chức: không đồng bộ, bất đối xứng 2 bán cầu, song theta, delta lan toả và không theo nhịp, gai/nhọn sóng chậm đa ổ.

32. Hypsarrhythmia The background amplitude : 300 μV, includes a mixture of frequencies without normal consistent rhythms. Multiple spikes are present and have a bilateral posterior predominance. The most prominent spike occurs in the P3–O1 channel and has an amplitude of 700 μV. A 21-month old who was born at 25 weeks and developed infantile spasms at 17 months. The spasms were attributed to neonatal hypoxicischemia encephalopathy. Brain MRI identified periventricular leukomalacia.

33. Ictal focal / generalized onset seizure Đặc điểm c ơ n động kinh trên EEG Khởi phát đột ngột Kết thúc đột ngột Tiến triển về tần số Tiến triển về biên độ Tiến triển về phân bố Có triệu chứng lâm sàng t ư ơng ứng Đáp ứng với Benzodiazepines

34. Focal seizure with mesial temporal onset. Rhythmic slowing emerges across the right temporal region and evolves into a well-formed 3-Hz phase-reversing rhythm at the T2 and F8 electrodes. The rhythm continues to evolve over the following 20 seconds to reach a frequency of 6 Hz and encompass a larger right-sided field. A 37-year old with focal dyscognitive seizures manifested by oral automatisms with intact verbal interaction. Right hippocampal sclerosis was identified histopathologically following resective epilepsy surgery. A brief muscle artifact is present in the second half of the 30-second EEG segment. 1/3

35. 2/3

36. 3/3

37. 1/2 Focal seizure with mesial temporal onset Diffuse slowing transitions into rhythmic activity across the right temporal region. Over10 seconds, the rhythm becomes increasingly monomorphic and higher amplitude with 4-Hz phase reversals at the T2 and F8 electrodes. The ictal pattern is monophasic. A 63-year old with focal dyscognitive seizures manifested by staring and manual and oral automatisms. Right hippocampal sclerosis was identified histopathologically following resection for epilepsy surgery

38. 2/2

39. Generalized-onset seizure Khởi phát hai bên/ toàn thể 1 trong 3 dạng phóng điện: Hoạt động nhanh toàn thể hoá (Generalized paroxysmal fast activity (GPFA). Phức hợp gai sóng chậm toàn thể hoá (Generalized spike and slow-wave complexes (GSW) Sự sụt giảm điện thế hoạt động nền (electrodecrement) Kết thúc 1 trong 3 kiểu: Kết thúc đột ngột Tiến triển hình dang và tần số Giảm dần hoạt động trong c ơ n, thay thế bằng hoạt động nền.

40. Generalized Paroxysmal Fast Activity Brief, generalized attenuation is immediately followed by fully generalized, high-frequency, low-amplitude activity. The amplitude exceeds the baseline amplitude within 1 second and the continuous high-frequency activity evolves over 2 seconds into bursts of fast activity that are followed by high-amplitude slow waves. 1/3

41. Upon resolution of the polyspike and slow wave activity, generalized, rhythmic activity occurs and then resolves with return to baseline activity within 5 seconds. The EEG was recorded from a 44-year-old patient with cognitive disability and multiple seizure types, including tonic and atonic seizures. The segment was interictal, but similar GPFA corresponded to seizures. 2/3

42. 3/3

43. An 18-year old with juvenile absence epilepsy. Absence seizure High amplitude spike and slow-wave complexes replace the background activity and initially recur at 3 Hz before slowing to approximately 2.5 Hz. The complexes are best formed in the parasagittal regions and have a frontal prominence. The run lasts about 6 seconds, which is a duration that typically produces impairment.

44. Electrodecrement

45. sau c ơ n co giật lần đầu trong theo dõi điều trị trong quyết định ng ư ng thuốc EEG

46. W. Allen Hauser, M.D. et col, N Engl J Med 1998; 338:429-434 35%, 5 years

47. The clinical utility of routine electroencephalography (EEG) after a first unprovoked seizure remains uncertain. Its diagnostic accuracy in identifying adults and children with new onset epilepsy was examined. A systematic review and meta-analysis of studies examining individuals who underwent routine EEG after a first unprovoked seizure and were followed for seizure recurrence for at least 1 year was performed. A ‘positive’ test was defined by the presence of epileptiform discharges (ED). Pooled sensitivity and specificity estimates were calculated using a bivariate random effects regression model. In all, 3096 records were reviewed, from which 15 studies were extracted with a total of 1799 participants. Amongst adult studies , the sensitivity and specificity (95% confidence interval) of routine EEG were 17.3% (7.9, 33.8) and 94.7% (73.7, 99.1), respectively. Amongst child studies , the pooled sensitivity and specificity were 57.8% (49.7, 65.6) and 69.6% (57.5, 79.5), respectively. Based upon our positive likelihood ratios , and assuming a pre-test probability of 50%, an adult with ED on routine EEG after a first unprovoked seizure has a 77% probability of having a second seizure, whilst a child with similar findings has a 66% probability. Further studies are required to examine the impact of patient characteristics and EEG features on the diagnostic accuracy of routine EEG for new onset epilepsy. European Journal of Neurology 2016, 23: 455–463

48. SAU C Ơ N CO GIẬT LẦN ĐẦU EEG bất th ư ờng tuỳ loại c ơ n [1] Cơn vắng – 92% Mất tr ư ơng lực, giật cơ – 85% Cục bộ phức tạp – 59% Toàn thể hoá thứ phát – 44% [1] Seizure 49 (2017) 69–73

49. Tăng khả năng phát hiện IEDs sau c ơ n đầu Đo sớm ngay sau c ơ n 12-16h dễ phát hiện bất th ư ờng [1,2] với tỉ lệ #50% Đo nhiều lần Nghiệm pháp thiếu ngủ Đo kéo dài [1] Epilepsy Res. 2016 Nov;127:229-232; [2] Epilepsy behave. 2020 Oct;111:107315

50. How soon should urgent EEG be performed following a first epileptic seizure? Purpose:  Patients with a first unprovoked epileptic seizure are often seen in emergency services. Electroencephalography (EEG) is indicated for diagnosing epilepsy, but the optimal time to perform this test has not been defined. This study aimed to determine the time interval following a seizure within which EEG has the greatest diagnostic yield. Methods:  We conducted a retrospective study of all adult patients with a first unprovoked seizure who had undergone emergency EEG (July 2014-December 2019). Data collection included demographics, seizure type, time interval to EEG study, EEG pattern identified, and the prescription after emergency assessment. An optimal cut-off point for time to EEG was obtained, and an adjusted regression model was performed to establish associations with the presence of epileptiform abnormalities. Results:  A total of 170 patients were included (mean age: 50.7 years, 40.6% women). Epileptiform discharges were identified in 34.1% of recordings, nonepileptiform abnormalities in 46.5%, and normal findings in 19.4%. A lower latency from seizure to EEG was associated with a higher probability of finding epileptiform discharges (median: 12.7 in the epileptiform EEGs vs. 20 h in the nonepileptiform EEGs, p < 0.001). The time interval associated with the highest probability of detecting an epileptiform EEG pattern was within the first 16 h after seizure onset: 52.1% of recordings performed before the 16-h cut-off showed these abnormal patterns compared with 20.2% performed after (p < 0.001). These findings were not related to the presence of an epileptogenic lesion in neuroimaging or to other clinical variables. The finding of epileptiform abnormalities was followed by a greater prescription of antiseizure drugs (96.4% vs. 66% in nonepileptiform patterns, p < 0.001). Conclusion:  The diagnostic yield of EEG following a first unprovoked epileptic seizure is highest when this test is performed within the first 16 h after onset of the event. Epilepsy behave. 2020 Oct;111:107315

51. Epileptiform abnormality in single unprovoked seizure and incident epilepsy Elisa Baldin , Epilepsia, 55(9):1389–1398, 2014

52. Elisa Baldin , Epilepsia, 55(9):1389–1398, 2014

53. Giấc ngủ và IEDs Phóng điện dạng ĐK (epileptiform discharges - IED) xuất hiện vào lúc ngủ nhiều hơn khi thức. Đặc biệt là đối với ĐK thùy trán. Giấc ngủ NREM làm tăng xuất hiện IED: ở ĐK toàn thể, ĐK toàn thể vô căn, cơn vắng ý thức. Giảm IED cục bộ. IED tăng ở các HC ĐK, chủ yếu gđ NREM: Benign Childhood Epilepsy with Centrotemporal Spikes (BCECTS) – ĐK lành tính ở trẻ nhỏ với gai vùng trung tâm thái dương. ĐK thùy trán. Landau-Kleffner syndrome. Lennox-Gaustaut Syndrome. ĐK giật cơ ở thiếu niên. ĐK toàn thể hóa khi thức giấc. Thiếu ngủ làm tăng IED

54. The importance of sleep deprivation as a mechanism for activating interictal epileptiform paroxysms, [Spain] Introduction:  Although sleep deprivation has been used for years in electroencephalography (EEG) as a method for activating interictal epileptiform discharges (IED) in patients with a strong suspicion of epilepsy, its sensitivity and specificity are still under discussion. Patients and methods:  We conducted a descriptive retrospective study of paediatric patients who were referred to a neurophysiology clinic for epilepsy assessment. The results of the sleep-deprived EEG (SD-EEG) were compared with those of the wakefulness EEG (W-EEG) carried out in each patient in order to describe the performance of each method as a mechanism for activating IED. Results:  A total of 500 patients were analysed (830 SD-EEG and 1018 W-EEG). IED were detected in 44% of the W-EEG. SD-EEG increased the capacity of the test to detect IED by 35%. IED (not detected in the W-EEG) were detected in 25.1% of the SD-EEG in which spontaneous sleep was achieved. In the group of focal epilepsies , it was found that W-EEG detected IED in 60.1% versus the 79.12% displayed with SD-EEG. In generalised epilepsies this difference was more marked ( 27.2% and 77.2%, respectively). In patients in whom no IED were detected following an SD-EEG (23.7%) and the clinical suspicion of epilepsy was still high, nocturnal polysomnography was performed and interictal epileptiform activity was observed in 13.6%. Conclusions:  SD-EEG increases the chances of recording IED by 35% with respect to W-EEG. Sleep deprivation is a method for activating epileptiform paroxysms, regardless of whether the EEG is performed while sleeping or not, although this effect is more pronounced in patients who do manage to sleep. [1] Rev Neurol. 2016 Apr 1;62(7):289-95

55. Effects of Sleep and Sleep Stage on Epileptic and Nonepileptic Seizures Purpose: Previous studies of patients with epilepsy and animal models of epilepsy suggest that sleep increases the frequency, duration, and secondary generalization of seizures. This information is, however, incomplete. Methods: We retrospectively examined video-EEG monitoring reports from our comprehensive epilepsy center. We recorded seizure type, site of onset (for partial seizures), sleep state at onset, and whether partial seizures secondarily generalized. Seizures arising from sleep were then reviewed to determine sleep state. Results: We analyzed 1,116 seizures in 188 patients . 35% of complex partial seizures (CPSs) starting during sleep underwent secondary generalization compared with 18% in wakefulness ( p < 0.0001 ). Frontal lobe CPSs secondarily generalized at equal rates during sleep (22%) and wakefulness (20%), but temporal lobe CPSs generalized much more frequent during sleep ( 45%) than in wakefulness ( 19%; p < 0,0001 ). Frontal lobe seizures were more likely to occur during sleep (37%) than were temporal lobe seizures ( 26%; p =0.0068 ). CPSs were more frequent in stages 1 and 2 and occurred rarely during REM. Seizures starting during slow-wave sleep were significantly longer than seizures starting during wakefulness or stage 2 sleep. Psychogenic nonepileptic seizures (PNESs) were rare between midnight and 6 a.m. and never occurred during sleep. Carl W. Bazil et col, Epilepsia, 38(1):56-62, 1997

56. Proportionof complex partial seizures (CPSs) in various stages of sleep and wakefulness. Left : seizures that did not generalize. RIght: Seizures that secondarily generalized. Twelve seizures that occurred from sleep but in which sleep stage could not be determined were excluded. GTC, generalized tonicclonic. Carl W. Bazil et col, Epilepsia, 38(1):56-62, 1997

57. Carl W. Bazil et col, Epilepsia, 38(1):56-62, 1997 Conclusions Sleep has a pronounced effect on secondary generalization of partial seizures, especially those of temporal lobe origin. Frontal lobe seizures occur more often during sleep than do temporal lobe seizures, and occurrence during sleep helps to distinguish PNESs from CPSs .

58. Guray Koc et col, European Journal of Epilepsy 69 (2019) 235–240

59. Conclusions: The fi rst-hour sleep EEG reliably predicts the occurrence of IEDs during the long-term video-EEG recording, and therefore can be a time-e ffi cient tool for identifying patients with IEDs during long-term video EEG recording in the adult epilepsy monitoring unit. Xi Liu et col, European Journal of Epilepsy 63 (2018) 48–51 The first-hour-of-the-day sleep EEG reliably identifies IEDs during long-term video-EEG monitoring Total 134 cases: 98 TLE, 12 FLE , 3 parietal lobe, 2 occipital lobe, 17 with generalized IEDs, and 2 with multi-focal IEDs

60. Theo dõi điều trị NG Ư NG THUỐC ?

61. Mục đích điều trị: không c ơ n ĐK ILAE: 3 lần thời gian không c ơ n dài nhất (ít nhất 1 năm) [1] EEG bất th ư ờng nếu ng ư ng thuốc gây tăng nguy c ơ tái phát c ơ n [2,3] [1] Patrick Kwan et col, Epilepsia, 51(6):1069–1077, 2010 [2] Clin neurophysiol. 2017 Feb;128(2):297-302 [3] Neurol Sci. 2019 Aug;40(8):1637-1644

62. Relapse following discontinuation of antiepileptic drugs: a meta-analysis The estimates in the literature of the risk of seizure relapse after antiepileptic medications are withdrawn range from less than 10% to nearly 70%. There is also little coherence regarding predictors of successful medication withdrawal. We performed a meta-analysis of the published literature to date to determine the risk of relapse at 1 and 2 years after discontinuation of medications and to examine the strength of association between the risk of relapse and three commonly assessed clinical factors: age of onset of epilepsy, presence of an underlying neurologic condition, and an abnormal EEG . We established criteria for inclusion of a study in the analysis, and 25 studies met these criteria. Overall, the risk of relapse at 1 year was 0.25 (95% CI, 0.21 to 0.30) and at 2 years it was 0.29 (95% CI, 0.24 to 0.34). Relative to epilepsy of childhood onset , epilepsy of adolescent onset was associated with a relative risk of relapse of 1.79 (95% CI, 1.46 to 2.19). Compared with childhood-onset epilepsy, adult-onset epilepsy was associated with a relative risk of 1.34 (95% CI, 1.00 to 1.81). Patients with remote symptomatic seizures were more likely to relapse than patients with idiopathic seizures; the relative risk was 1.55 (95% CI, 1.21 to 1.98). An abnormal EEG was associated with a relative risk of 1.45 (95% CI, 1.18 to 1.79). Although these figures help provide an estimate of an individual's likelihood of relapse, they should not be used as the sole basis on which to make the decision on discontinuation of medications. Neurology. 1994 Apr;44(4):601-8

63. Can electroencephalograms provide guidance for the withdrawal of antiepileptic drugs: A meta-analysis Objective:  The discontinuation of antiepileptic drugs (AEDs) is an important treatment decision for epilepsy patients who have been seizure-free for 2years or longer. Some patients experience seizures relapse after AED withdrawal. The prognostic value of electroencephalograms (EEGs) for seizure relapse following AED withdrawal is controversial. To our knowledge, this is the first meta-analysis to address whether EEG data can be used to guide the discontinuation of AEDs. Method:  We performed a meta-analysis of cohort studies that reported original EEG data from before AED withdrawal and recurrence after AED-withdrawal. The quality of each study was assessed using the Newcastle-Ottawa Scale. Results:  Fifteen studies including a total of 2349 participants were included in this meta-analysis. This meta-analysis of 15 studies demonstrates that an abnormal electroencephalogram was a predictor of the risk of relapse. Additionally, paroxysmal, slowing, spike and wave activities on electroencephalograms were associated with increased risk of relapse . Conclusion:  We reveal that abnormal EEG records, particularly paroxysmal abnormalities, before AED withdrawal predicted a high risk of relapse. Slowing and spike and wave activities also exhibited moderate predictive values. Significance:  Our findings suggest that, EEGs might be an important prognostic tool for antiepileptic drug reduction. Clin neurophysiol. 2017 Feb;128(2):297-302

64. European Journal of Epilepsy 94 (2022) 100–106

65. Purpose: Whether patients with epilepsy in long-term remission and interictal epileptiform discharges (IEDs) can stop antiseizure medication (ASM) remains a challenging topic even though multiple studies have investigated ASM withdrawal. This study aimed to estimate seizure relapse and its risk factors in patients with epilepsy in fiveyear remission and persistent IEDs . Methods: Patients with epilepsy and persistent IEDs were prospectively recruited from the Affiliated Nanjing Brain Hospital of Nanjing Medical University from Dec.1, 2010 to Dec.30, 2019. All enrolled patients achieved seizure remission for over five years and were divided into the ASM withdrawal and continuous treatment groups according to their personal preference. Seizure outcomes and 24 h video electroencephalogram findings were obtained through clinical visits or telephone interviews every three months until March 31, 2021. The cumulative recurrence rate and its diversity between the ASM withdrawal and continuous treatment groups were tested using Kaplan–Meier analysis. Multivariate Cox regression analysis was performed to explore the independent predictors for seizure recurrence. Relapsed patients were further monitored for their seizure control and prognosis. European Journal of Epilepsy 94 (2022) 100–106

66. Results: A total of 83 patients with epilepsy in five-year remission and persistent IEDs were enrolled in this study, including 41 (49.4%) in the ASM withdrawal group and 42 (50.6%) in the continuous ASM treatment group. During the follow-up with a median time of 36.8 months (range from 18.7 to 104.6 months), the seizure relapse in off-medication patients ( 43.9%, 18/41) was higher than that in on-medication patients ( 21.4%, 9/42; P =0.031 ). In the multivariate analysis model, independent predictors for seizure recurrence were structural metabolic epilepsy or unknown cause ( HR = 6.185, 95% CI 1.166–32.805) and multiple seizure types ( HR =2.807, 95% CI 1.051–7.502). ASM withdrawal was not found to be an independent risk factor for seizure recurrence. Of 27 patients with seizure recurrence, 25 were given reinstitution or continuous ASM therapy, whereas two chose sustained observation without medication. At the end of the follow-up, 70.4% (19/27) of recurrence patients were completely free from seizures for at least one year again, and only one patient developed refractory epilepsy. Conclusion: For patients with epilepsy in five-year remission and persistent IEDs, drug withdrawal may be a rational choice after the individualized assessment of benefits and risks. Furthermore, the independent risk factors for the seizure relapse were structural-metabolic epilepsy or an unknown cause, and multiple seizure types. Finally, patients with epilepsy relapsing after ASM withdrawal could achieve seizure remission again after ASM retreatment. European Journal of Epilepsy 94 (2022) 100–106

67. Relapse After Drug Withdrawal in Patients with Epilepsy After Two Years of Seizure-Free: A Cohort Study Background and Study Aims: Antiepileptic drugs are the first choice of treatment for patients with epilepsy. However, the withdrawal of antiepileptic drugs after seizure-free remains a significant focus for the majority of patients with epilepsy and their families. In this study, we We aimed evaluated the risk factors associated with relapse after drug withdrawal in patients with seizure free for 2 years . to guide patients in seizure-free to assess the risk of drug withdrawal. Patients and Methods: Through screening, 452 patients with epilepsy were included in the study.Patients were followed up for at least 2 years or more. Analyzed their clinical data by applying the χ 2-test, Kaplan-Meier survival analysis and multivariate Cox regression analysis. Results: 423 patients completed follow-up, of which 304 cases recurred (71.9%).Related recurrence factors include age of onset, type of seizure, number of AEDs, seizure-free time before withdrawal, and electroencephalogram (EEG) results before drug withdrawal ( P <0.05). The results of correlation analysis showed that age of onset, seizure frequency, seizure type, number of AEDs, the period from AEDs treatment to a seizure-free status, EEG results before drug withdrawal, and pre-medication course , were all significantly related to the recurrence of seizures after drug reduction and withdrawal ( P <0.05). We identified a range of independent risk factors, including onset age, seizure frequency, Multiple AEDs and the period from AEDs treatment to a seizure-free status. Conclusion: The overall recurrence rate of epilepsy in our patient cohort was high, and the peak recurrence period was within oneyear of drug withdrawal. Patients with partial seizures, a short seizure-free time before withdrawal, severe EEG abnormalities before drug reduction, and a long course of the disease, are prone to relapse . Patients with an older age at onset and a high frequency of attack, those taking multi-drug combination therapy, and those that take a long time to gain control, should be managed carefully to AEDs withdrawal. Xiaoli Zhang et col, Neuropsychiatric Disease and Treatment 2023:19 85–95

68. Mild abnormal EEG: (1) α rhythm of a is irregular, unstable, poorly regulated and amplitude modulated, the frequency slows down to 8Hz, the amplitude exceeds 100µv, and the physiological response is not obvious. (2) The amplitude difference of corresponding parts of both hemispheres exceeds 50%. (3)β activity increased significantly, and the amplitude was higher than 50µv. (4)θ activity increased significantly, mainly in the frontal area. (5)δ activity increased slightly. (6) Excessive ventilation shows moderate amplitude.Early appearance or delayed disappearance of slow wave activity in θ frequency band. Moderately abnormal EEG: (1) The basic rhythm is obviously slow, and the occipital region is slow at α rhythm of 7–8Hz, or α rhythm disappears completely, and is affected by θ rhythm of 4~7Hz replacement. (2) The left and right sides are obviously asymmetrical. (3) There are many medium amplitude waves scattered around 3Hz α wave α or activity. (4) Normal physiological sleep wave disappears on one or both sides, or normal sleep cycle disappears. (5) More widely scattered or less rhythmic epileptiform discharges. Severe abnormality EEG: (1) Background withδwaves are dominant, with a small amount θ activity, or few low amplitude fast wave of α or β frequency band, compounded on slow wave. (2) The background is dominated by θ rhythm, with a few scattered α,β, δ waves. (3) α generalization. (4) Irregular amplitude and frequency, completely out of rhythm. (5) Epileptic discharge with paroxysmal rhythm. (6) Periodic phenomenon. (7) Continuous low voltage or electrical quiescent state. Wu X, Wu W, Liu X, et al. Clinical EEG Training Course. People’s Health Publishing House; 2011

69. Xiaoli Zhang et col, Neuropsychiatric Disease and Treatment 2023:19 85–95

70. David Gloss, MD et col, Neurology 2021;97;1072-1081

71. THANK YOU