Literature DB >> 33342709

Meta-analysis of EEG findings in patients with COVID-19.

Takafumi Kubota1, Prasannakumar Kanubhai Gajera2, Naoto Kuroda3.   

Abstract

OBJECTIVE: To perform a systematic review and meta-analysis to summarize and quantitatively evaluate the electroencephalogram (EEG) findings in patients with coronavirus disease 2019 (COVID-19).
METHODS: The MEDLINE, CENTRAL, and ClinicalTrials.Gov databases were comprehensively assessed and searched for observational studies with EEG findings in patients with COVID-19. Pooled proportions of EEG findings with 95% confidence intervals (CIs) were assessed using a random effects model. The quality of assessment for each study, heterogeneity between the studies, and publication bias were also evaluated.
RESULTS: In total, 12 studies with 308 patients were included in the meta-analysis. Abnormal background activity and generalized slowing in the pooled proportions were common findings among the patients with COVID-19 (96.1% [95% CI: 89.4-99.9]; I2 = 60%; p < 0.01 and 92.3% [95% CI: 81.2-99.3]; I2 = 74%; p < 0.01, respectively). The proportion of patients with epileptiform discharges (EDs) was 20.3% ([95% CI: 9.85-32.9]; I2 = 78%; p < 0.01). The proportion of EDs varied between patients with a history of epilepsy or seizures (59.5% [95% CI: 33.9-83.2]; I2 = 0%; p = 0.49) and patients without them (22.4% [95% CI: 10.4-36.4]; I2 = 46%; p = 0.07). The findings of seizures and status epilepticus on EEG were observed in 2.05% ([95% CI: 0.02-6.04]; I2 = 39%; p = 0.08) and 0.80% ([95% CI: 0.00.-3.69]; I2 = 28%; p = 0.17) of the patients, respectively.
CONCLUSION: The proportion of abnormal background activity in patients with COVID-19 was high (96.1%). Epileptiform discharges were present in 20.3% of the cases and the proportion varied between people who had a history of epilepsy/seizure and those who did not. However, the proportion of seizures and status epilepticus on EEG was low (2.05% and 0. 80%, respectively).
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  COVID-19; EEG; Epilepsy; Neurology; Seizure; Status epilepticus

Year:  2020        PMID: 33342709      PMCID: PMC7833461          DOI: 10.1016/j.yebeh.2020.107682

Source DB:  PubMed          Journal:  Epilepsy Behav        ISSN: 1525-5050            Impact factor:   2.937


Introduction

Coronavirus disease 2019 (COVID-19) occurred in December 2019 in Wuhan, China and is currently one of the most important infectious diseases in the world. The common symptoms of patients with COVID-19 include fever, cough, and difficulty in breathing [1]. Some patients have neurological symptoms such as headache, dizziness, altered mental status, or seizures [2]. It has also been reported that COVID-19 causes serious neurological complications such as stroke, encephalitis, meningitis, encephalopathy, or status epilepticus [3], [4], [5]. Electroencephalography (EEG) is one of the simplest and most widely used neurological diagnostic tests. Moreover, EEG is an important test that can change clinical decisions. It is useful to evaluate whether patients have neurological complications. In particular, EEG can be used to assess encephalopathy, epileptogenicity, and any focal abnormalities in patients with COVID-19. Some studies successfully described EEG findings in patients with COVID-19 [6], [7], [8]. However, the number of patients in previous studies has been limited, and the proportions of abnormal findings in EEG vary across studies. In addition, a comprehensive and quantitative analysis of each finding in these past studies has not been conducted. Therefore, the aim of our systematic review and meta-analysis was to evaluate the proportion of EEG findings in patients with COVID-19, systematically and quantitatively.

Methods

Retrieval of studies

We conducted a systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines [9]. This review protocol has not been previously registered. MEDLINE (accessed from PubMed) and CENTRAL (accessed from the Cochrane Library) were searched systematically up to September 19, 2020. In the PubMed and Cochrane libraries, the following key words (in the title/abstract) were searched: (“COVID 19″ OR ”SARS CoV 2″) AND (“epilepsy” OR “seizure” OR “status epilepticus” OR “electroencephalogram” OR “EEG” OR “encephalopathy” OR “encephalitis”). We also used ClinicalTtrials.gov to search for unpublished, ongoing, terminated, or completed studies to avoid publication bias. We screened the reference lists of all relevant articles for additional data.

Eligibility and risk-of-bias assessment

Studies were included based on the following criteria: (1) reports of COVID-19 patients who underwent EEG; (2) original reports such as case series with more than 3 cases, case–control studies, or cohort studies; (3) studies with descriptions of EEG findings such as background activity, rhythmic/periodic discharges, epileptiform discharges, focal findings, seizures, or status epilepticus. To accurately evaluate the proportion and to avoid selection bias of the abnormal findings, we excluded case reports with 3 cases or less. We also excluded not yet recruiting, recruiting, or withdrawn studies in Clinical.Trials.gov. Studies written in languages other than English were excluded. We used the Joanna Briggs Institute checklist to assess the quality of the included case series and case–control studies [10], [11].

Data extraction and outcome measures

Two reviewers (TK and PG) independently screened the titles and abstracts, and evaluated the full texts of the selected articles. They included those that met the inclusion criteria and discussed any discrepancies with a 3rd reviewer (NK). The following variables were extracted: author, publication year, study design, age and sex of the subjects, country in which the study was conducted, diagnostic methods used, neurological comorbidity in the subjects, time from symptom onset until EEG, clinical setting, presentation/indication for EEG, need for intubation, need for sedation and antiepileptic/seizure drug, occurrence of cardiac arrest, brain imaging investigations, if any, type and findings of EEG, and clinical outcomes. The outcome measures were the proportions of abnormal background activity, generalized slowing, discontinuous/burst attenuation or suppression/suppression, generalized periodic discharges (GPDs), lateralized periodic discharges (LPDs), generalized rhythmic delta activity (GRDA), lateralized rhythmic delta activity (LRDA), epileptiform discharges (EDs), focal slowing, seizures, and status epilepticus. We referred to the American Clinical Neurophysiology Society’s (ACNS) Standardized Critical Care EEG Terminology: 2012 version for the EEG terminology [12]. According to the ACNS’s EEG terminology, we defined any bilateral and bisynchronous pattern as generalized, sharp waves and spikes as epileptiform discharges, frontal intermittent rhythmic delta activity as GRDA, and triphasic waves such as GPDs [12]. We also defined background/diffuse slow as generalized slowing, seizure and status epilepticus as epileptiform discharges. We defined status epilepticus as one type of seizure, because based on the International League Against Epilepsy's definition of status epilepticus, status epilepticus is a prolonged seizure [13]. For findings that were not described, we used the following two approaches: (1) In studies with individual EEG reports, we included undescribed findings as negative findings in the meta-analysis; (2) in studies without individual EEG data, undescribed findings were not included in the meta-analysis as unavailable data. We excluded unclassifiable data in our meta-analysis (ex. severe diffuse slowing/discontinuous/electrocerebral inactivity).

Statistical analysis

In this systematic review and meta-analysis, we used a single-arm analysis. For categorical variables, the percentage, mean, and standard deviation were calculated. We used random-effects models with the DerSimonian-Laird estimator to consider the variance between and among the studies. We calculated the pooled proportions using the variance-stabilized Freeman–Tukey double arcsine transformation because some proportions from the original studies were extremely high or low. Confidence intervals (CIs) for individual studies were computed using the Wilson score CI method, adjusting for continuity. The I 2 statistic and Cochran Q tests were used to indicate heterogeneity between the studies. For the I 2 statistic, 25% to 50%, 50% to 75%, and ≥75% were considered as low, moderate, and high heterogeneity, respectively. For the Cochran Q test, P < 0.10 was considered as severe heterogeneity [14], [15]. Publication bias was assessed using a funnel plot and Egger’s test, which is a quantitative analysis of asymmetry in the funnel plot. For Egger’s test, P < 0.10 was considered significant publication bias [15], [16]. We did not assess publication bias for the outcomes reported in less than 10 studies. We conducted statistical analyses using the R software version 3.6.2 (R Development Core Team 2019), with packages meta version 4.15-0 and metaphor version 2.4-0.

Results

A total of 363 studies were retrieved (349 papers from MEDLINE, 3 papers from CENTRAL, and 11 studies from Clinical.Trials.gov) up to September 19, 2020. After removing duplicates and screening the titles and abstracts, 228 studies were identified. The full-text screening of these studies led to the exclusion of 216 studies that did not meet the inclusion criteria. A total of 12 studies with 308 patients fulfilled the eligibility criteria for inclusion in the meta-analysis [6], [7], [8], [17], [18], [19], [20], [21], [22], [23], [24], [25]. We referred to a case report [26] of patients who were included in a case series [19] to obtain more detailed EEG findings. Fig. 1 outlines the selection process. Table 1 summarizes the findings of the included studies. More details of the included studies are shown in Supplementary Table 1. The mean score for the quality of 10 case series and 2 case–control studies was 8.7 out of 10. (see Table 1 and Supplementary Table 2).
Fig. 1

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram of this research.

Table 1

Summary of findings.

First author and year[Reference]Study designNoAge (SD or range)Male (%)CountryQuality score (out of 10)Neurological ComorbidityPresentation/EEG indicationSettingSedationCardiac arrestBrain ImageEEG typeEEG findings
Petrescu 2020 [17]CS3663.9 (12.1)80.5France910/36: Cognitive impairment, 2/36: Stroke,2/36: SDH, 1/36: Brain tumor, 1/36: Epilepsy, 1/36: Hydrocephalus,1/36: Anti-MAG Neuropathy36/36: ARDS, 6/18: Absence of awakening after stopping sedation,6/18: AMS, 2/18: Suspicion of epileptic seizures18/36: ICU,18/36: MU5/36N/A11/36: MRI (4: Atrophy, 3: Stroke, 2: SDH, 1: Gliosis, 1: Leptomeningeal enhancement),15/36: CT (8: Atrophy, 5: Normal, 1: SDH, 1: Stroke, 1: Meningioma, 1: Focal resection)36/36:Routine EEG32/36: ABA, 27/36: Generalized slowing, 4/36: Discontinuous background, 6/36: GPDs, 0/36: LPDs, 6/36: GRDA, 0/36: LRDA, 0/36: Focal slowing, 0/36 EDs, N/A: EDs in PWE, N/A: EDs in PwoES, 0/36: Seizure, 0/36: SE
Ayub 2020 [18]CS3766.0 (59.5–76.3)73USA98/37: Past history of CNS pathology,1/37: Past seizure history11/37: Possible seizure,24/37: AMS, 2/37: Cardiac arrestN/A27/372/379/35: Neuroimagingacutely abnormal23/37: cEEG,14/37: Routine EEGsN/A: Overall ABA, 34/37: Absent PDR, 31/37: Generalized slowing, 5/37: Burst suppression, 12/37: GPDs, 0/37: LPDs, 5/37: GRDA, 1/37: LRDA, 3/37: Focal slowing, 14/37 EDs, N/A: EDs in PWE, N/A: EDs in PwoES, 1/37: Seizure, 1/37: SE (NCSE)
Galanopoulou 2020 [6]CC2863.2 (11.9)63.6USA94/22: Epilepsy,7/22: Other neurological disorders20/22: AMS, 14/22: Suspicion of clinical seizure-like events,1/22: Confusion, 2/22: Gaze deviationICU14/22N/A3/13: Neuroimaging:new findings (subcortical and mild periventricular white matter signal hyperintensity, SAH, SDH)20/22: 8ch‐EEG,4/22: routine, 7/22: cEEG22/22: ABA, 22/22: Generalized slowing, 1/22: Discontinuous or burst suppression, 1/22 GPDs, N/A: LPDs, 3/22: GRDA, 1/22: LRDA, 5/22: Focal slowing, 9/22 EDs, 2/4: EDs in PWES, 7/18: EDs in PwoES, 0/22: Seizure, 0/22: SE
Pasini 2020 [7]CS1564.6 (47–79)40Italy82/15: Cognitive decline, 1/15: Previous limbic encephalitis,1/15: Frontal metastasis15/15: AMS (11 confusion, 4 impairment of consciousness),1/15: AphasiaN/AN/A2/150/8 CT: Abnormality,2/6: MRI: hyperintensity in white matterN/A11/15: ABA, 9/15: Generalized slowing, 2/15: Discontinued activity or background suppression, 10/15: No reactivity to external stimuli, N/A: GPDs, N/A: LPDs, 1/15: GRDA, 0/15: LRDA, 3/15: Focal slowing (frontal or central), 1/15 EDs, N/A: EDs in PWE, N/A: EDs in PwoES, 1/15: Seizure, 1/15: SE
Pastor 2020 [8]CC2063.9 (12.1)85Spain98/20: Stroke18/20: AMS(8 Stuporous, 10 Confused)Non-critical care unitN/A0/20N/AN/A20/20: ABA, 20/20: Generalized slowing (5/20: Excess of slow posterior activity, 5/20: Predominant thetaactivity in more than 50% of recording, 10/20 Predominant delta activity in more than 50% of recording), N/A: DC/BAS/S, 0/20: GPDs, 1/20: LPDs, GRDA: 0/20, LRDA: 0/20, 0/20: Focal slowing, 3/20 EDs, N/A: EDs in PWE, N/A: EDs in PwoES, 0/20: Seizure, 0/20: SE
Louis 2020 [19]CS2266.5 (11.2)63.6USA92/22: Epilepsy,1/22: Stroke, 1/22: Headache, TBI17/22: AMS,5/22: seizure-like eventN/A14/22N/AN/A19/22: cEEG,3/22: Routine EEG22/22: ABA, 22/22: Generalized slowing, 0/22: DC/BAS/S, 11/22: No PDR, 7/22: GPDs, N/A: LPDs, 11/22: GRDA, N/A: LRDA, 5/22 EDs, 2/2: EDs in PWES, 3/20: EDs in PwoES, 2/22: Seizure, 1/22: SE [26]
Canham 2020 [20]CS1055.9 (20.4)80UK81/10: Epilepsy,1/10: Stroke9/9: AMS, 2/9: Delirium,6/10 Seizure (4: GTCS, 1: Focal Motor, 2: Tonic)ICU1/100/1010/10: CT (2 venography,4: small vessel disease, 2: volume loss, 2: SAH), 3/10: MRI (1: small infarct in the left precentral gyrus, 1: frontal and medial temporal atrophy, 1: Normal)10/10: Routine EEG (a minimum of 9 electrodes)10/10: ABA, 10/10: Generalized slowing, 0/10: DC/BAS/S, 2/10: GPDs (Triphasic waves), 0/10: LPDs,1/10: GRDA, 0/10: LRDA, 0/10: Focal slowing, 2/10 EDs, 0/1: EDs in PWES, 2/9: EDs in PwoES, 0/10: Seizure, 0/10: SE
Pellinen 2020 [21]CS11164 (17)71.2USA923/111: Remote ischemic stroke, 13/111: Epilepsy,19/111: Other brain disorders42/111: Definite/suspected seizure,78/111: Coma85/111: ICU67/11111/11171/90: Abnormal,31/90: Acute focal cortical, 23/90: Acute diffuse, 10/90: Chronic focal cortical, 36/90: Chronic subcortical, 15/90: Chronic diffuseMajority: cEEG,Some cases: Reduced 8-bioplar channel montage106/111: ABA, N/A: Generalized slowing (17/111: Mild diffuse slowing, 60/111: Moderate diffuse slowing, 29/111: Severe diffuse slowing/discontinuous/ electrocerebral inactivity), N/A: DC/BAS/S, 11/111: GPDs, 3/111: LPDs, 4/111: GRDA, 7/111: LRDA, 27/111: Focal slowing, 35/111 EDs, 8/13: EDs in PWES, 20/85: EDs in PwoES, 8/111: Seizure, 2/111: SE
Cecchetti 2020 [22]CS1866.8 (10.7)61.1Italy91/18: Glioblastoma5/18: AMS, 5/18: Seizure/spasm, 3/18: Delirium, 5/18: ComaN/AN/AN/A1/18: PRES, 1/18: Remote IPH, 1/18: Glioblastoma, 1/18: Brain metastasis, 1/18: Traumatic SDH, 1/18: Remote hemispheric stroke, 1/18: Anterior pontine demyelinating les.N/A16/18: ABA, 16/18: Generalized slowing (5/18: Normal/mild EEG alteration, 9/18: Moderate EEG alteration, 4/18: Severe EEG alteration), N/A: DC/BAS/S, N/A: GPDs, N/A: LPDs, N/A: GRDA, N/A: LRDA, 7/18: Focal slowing, 2/18: EDs, N/A: EDs in PWES, 2/18: EDs in PwoES, 0/18 Seizure, 0/18: SE
Pilato 2020 [23]CS863 (47–87)62.5USA85/8: Epilepsy, 2/8: Developmental delay, 2/8: Dementia,1/8: TBI, 1/8: Anoxic brain injury6/8: AMS, 3/8: Seizure or seizure-like episode, 2/8: WeaknessN/A1/82/85/8: MRI (3: Atrophy,3: Ventriculomegaly, 2: Stroke)3/8: Routine EEG,5/8: cEEG8/8: ABA, 8/8: Generalized slowing, 1/8: Discontinuousbackground, 3/8: GPDs, 1/8: LPDs,0/8: GRDA, 0/8: LRDA, 1/8: Focal slowing (Right posterior quadrant), 5/8 EDs, 3/5: EDs in PWES, 2/3: EDs in PwoES, 2/8: Seizure, 2/8: SE (NCSE)
Chen 2020 [24]CS545.0 (9.8)40USA90/55/5: AMS (3/5: suspected encephalopathy), 3/5: Seizure-like episodeICU5/50/51/1: CT (small subacute-chronic strokes)3/5: Rapid-EEG recording (10-electrode),2/5: cEEG5/5: ABA, 5/5: Generalized slowing, 0/5: Discontinuous/Suppression, 2/5: GPDs, 0/5: LPDs, 5/5: GRDA, 0/5: LRDA, 0/5: Focal slowing, 2/5: EDs, N/A: EDs in PWES, 2/2: EDs in PwoES, 2/5: Seizure, 2/5: SE
Delorme 2020 [25]CS466.8 (5.1)50France81/4: Epilepsy3/4: AMS (Agitation), 2/4: Frontal lobe syndrome, 1/4: Generalized convulsive status epilepticus, 1/4: Anxiety and Depressed mood, 1/4: Cerebellar syndromeN/AN/AN/A4/4: MRI (1: Unremarkable, 1: Non-specific white matter hyperintensities, 1: Right mesial sclerosis (already known), 1: Right T2 orbitofrontal hyperintensity), 4/4: PET (4: hypometabolism within bilateral prefrontal or orbitofrontal cortex, 4: hypermetabolism within the cerebellar vermis)N/A1/4: ABA, 1/4: Generalized slowing, 0/4: Discontinuous/Suppression, 1/4: GPDs, 1/4: LPDs, 0/4: GRDA, 0/4: LRDA, 0/4: Focal slowing, 0/4: EDs, N/A: EDs in PWES, N/A: EDs in PwoES, 0/4: Seizure, 0/4: SE

CS: Case series. CC: Case–control study. No: Number of patients. SD: Standard deviation. EEG: Electroencephalogram. CNS: Central nervous system. ARDS: Acute respiratory distress syndrome. RT-PCR: Reverse transcription polymerase chain reaction. RNA: Ribonucleic acid. N/A: Not available. MU: Medical unit. ICU: Intensive care unit. LTAC: Long-term acute care hospital. AMS: Altered mental status. SAH: Subarachnoid hemorrhage. SDH: Subdural hematoma. MAG: Myelin-associated glycoprotein. TBI: Trauma brain injury. GTCS: Generalized tonic-clonic seizure. cEEG: Continuous electroencephalogram. routine EEG: Routine electroencephalogram. CT: Computed tomography. MRI: Magnetic resonance imaging. PRES: Posterior reversible encephalopathy syndrome. IPH: Intraparenchymal hemorrhage. ABA: Abnormal background activity. DC/BAS/S: Discontinuous/Burst-attenuation or suppression/Suppression. GPD: Generalized periodic discharges. LPD: Lateralized periodic discharge. PDR: Posterior dominant rhythm. GRDA: Generalized rhythmic delta activity. LRDA: Lateralized rhythmic delta activity. EDs: Epileptiform discharges. PWES: Patients with prior epilepsy or seizure history. PwoES: Patients without prior epilepsy or seizure history. SE: Status epilepticus. NCSE: Nonconvulsive status epilepticus.

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram of this research. Summary of findings. CS: Case series. CC: Case–control study. No: Number of patients. SD: Standard deviation. EEG: Electroencephalogram. CNS: Central nervous system. ARDS: Acute respiratory distress syndrome. RT-PCR: Reverse transcription polymerase chain reaction. RNA: Ribonucleic acid. N/A: Not available. MU: Medical unit. ICU: Intensive care unit. LTAC: Long-term acute care hospital. AMS: Altered mental status. SAH: Subarachnoid hemorrhage. SDH: Subdural hematoma. MAG: Myelin-associated glycoprotein. TBI: Trauma brain injury. GTCS: Generalized tonic-clonic seizure. cEEG: Continuous electroencephalogram. routine EEG: Routine electroencephalogram. CT: Computed tomography. MRI: Magnetic resonance imaging. PRES: Posterior reversible encephalopathy syndrome. IPH: Intraparenchymal hemorrhage. ABA: Abnormal background activity. DC/BAS/S: Discontinuous/Burst-attenuation or suppression/Suppression. GPD: Generalized periodic discharges. LPD: Lateralized periodic discharge. PDR: Posterior dominant rhythm. GRDA: Generalized rhythmic delta activity. LRDA: Lateralized rhythmic delta activity. EDs: Epileptiform discharges. PWES: Patients with prior epilepsy or seizure history. PwoES: Patients without prior epilepsy or seizure history. SE: Status epilepticus. NCSE: Nonconvulsive status epilepticus. We summarized the outcomes of our meta-analysis in Table 2 . The pooled proportions of abnormal background activity, generalized slowing, and discontinuous/burst attenuation or suppression/suppression were 96.1% ([95% CI: 89.4–99.9]; I 2 = 60%; p < 0.01), 92.3% ([95% CI: 81.2–99.3]; I 2 = 74%; p < 0.01), and 5.33% ([95% CI: 1.60–10.4]; I 2 = 0%; p = 0.48), respectively (Fig. 2 ). The pooled proportions of GPDs, LPDs, GRDA, and LRDA were 16.5% ([95% CI: 7.65–27.4]; I 2 = 68%; p < 0.01), 0.19% ([95% CI: 0.00–2.65]; I 2 = 14%; p = 0.32), 13.4% ([95% CI: 3.49–26.9]; I 2 = 82%; p < 0.01), and 0.96% ([95% CI: 0.00–3.36]; I 2 = 0%; p < 0.82), respectively (Fig. 3 ). The pooled proportion of focal slowing was 8.65% ([95% CI: 1.63–18.9]; I 2 = 75%; p < 0.01) (Fig. 4 ). The pooled proportion of EDs was 20.3% ([95% CI: 9.85–32.9]; I 2 = 78%; p < 0.01) (Fig. 5 A). The proportion of EDs varied between patients with a history of epilepsy or seizure (59.5% [95% CI: 33.9–83.2]; I 2 = 0%; p = 0.49) and those without them (22.4% [95% CI: 10.4–36.4]; I 2 = 46%; p = 0.07) (Fig. 5B and C). The pooled proportion of seizures and status epilepticus was 2.05% ([95% CI: 0.02–6.04]; I 2 = 39%; p = 0.08) and 0.80% ([95% CI: 0.00–3.69]; I 2 = 28%; p = 0.17) of the patients, respectively (Fig. 6 ).
Table 2

Results of Meta-analysis.

Heterogenicity
Egger's test
OutcomesnNProportion (%)95% CII2 (%)pp
Abnormal background activity1127196.189.4–99.960< 0.010.18
Generalized slowing1119792.381.2–99.374< 0.010.48
Discontinuous/Burst-attenuation or suppression/Suppression91595.331.60–10.400.48-
GPDs1027516.57.65–27.468< 0.010.21
LPDs82310.190.00–2.65140.32-
GRDA1127513.43.49–26.982< 0.010.21
LRDA102680.960.00–3.3600.820.34
Focal slowing112868.651.63–18.975<0.010.55
EDs1230820.39.85–32.978<0.010.83
EDs in patients with prior history of epilepsy or seizure62659.533.9–83.200.49-
EDs in patients without prior history of epilepsy or seizure815522.410.4–36.4460.07-
Seizure123082.050.02–6.04390.080.18
Status epilepticus123080.800.00–3.69280.170.03

n: Number of studies. N: Number of patients. CI: Confidence interval. GPDs: Generalized periodic discharges. LPDs: Lateralized periodic discharges. GRDA: Generalized rhythmic delta activity. LRDA: Lateralized rhythmic delta activity. EDs: Epileptiform discharges.

Fig. 2

Random-effects meta-analysis of the pooled proportions of (A) abnormal background activity, (B) generalized slowing, and (C) discontinuous/burst-attenuation or suppression/suppression (DC/BAS/S). 95% C.I. = 95% confidence intervals.

Fig. 3

Random-effects meta-analysis of the pooled proportions of (A) generalized periodic discharges (GPDs), (B) lateralized periodic discharges (LPDs), (C) generalized rhythmic delta activity (GRDA), and (D) lateralized rhythmic delta activity (LRDA). 95% C.I. = 95% confidence intervals.

Fig. 4

Random-effects meta-analysis of the pooled proportion of focal slowing. 95% C.I. = 95% confidence intervals.

Fig. 5

Random-effects meta-analysis of the pooled proportions of (A) epileptiform discharges (EDs), (B) EDs in patients with a history of epilepsy or seizure (PWES), and (C) EDs in patients without a history of epilepsy or seizure (PwoES). 95% C.I. = 95% confidence intervals.

Fig. 6

Random-effects meta-analysis of the pooled proportions of (A) electrographic seizure and (B) electrographic status epilepticus. 95% C.I. = 95% confidence intervals.

Results of Meta-analysis. n: Number of studies. N: Number of patients. CI: Confidence interval. GPDs: Generalized periodic discharges. LPDs: Lateralized periodic discharges. GRDA: Generalized rhythmic delta activity. LRDA: Lateralized rhythmic delta activity. EDs: Epileptiform discharges. Random-effects meta-analysis of the pooled proportions of (A) abnormal background activity, (B) generalized slowing, and (C) discontinuous/burst-attenuation or suppression/suppression (DC/BAS/S). 95% C.I. = 95% confidence intervals. Random-effects meta-analysis of the pooled proportions of (A) generalized periodic discharges (GPDs), (B) lateralized periodic discharges (LPDs), (C) generalized rhythmic delta activity (GRDA), and (D) lateralized rhythmic delta activity (LRDA). 95% C.I. = 95% confidence intervals. Random-effects meta-analysis of the pooled proportion of focal slowing. 95% C.I. = 95% confidence intervals. Random-effects meta-analysis of the pooled proportions of (A) epileptiform discharges (EDs), (B) EDs in patients with a history of epilepsy or seizure (PWES), and (C) EDs in patients without a history of epilepsy or seizure (PwoES). 95% C.I. = 95% confidence intervals. Random-effects meta-analysis of the pooled proportions of (A) electrographic seizure and (B) electrographic status epilepticus. 95% C.I. = 95% confidence intervals. We looked for publication bias for abnormal background activity, generalized slowing, GPDs, GRDA, LRDA, focal slowing, EDs, seizures, and status epilepticus using a funnel plot and Egger’s test (Fig. 7, Fig. 8 and Table 2). There was a significant publication bias for status epilepticus (P = 0.03); however, there was no significant publication bias for abnormal background activity (P = 0.18), generalized slowing (P = 0.48), GPDs (P = 0.21), GRDA (P = 0.21), LRDA (P = 0.34), focal slowing (P = 0.55), EDs (P = 0.83), and seizures (P = 0.18) (Table 2).
Fig. 7

Funnel plots of the meta-analysis of (A) abnormal background activity, (B) generalized slowing, (C) generalized periodic discharges, (D) generalized rhythmic delta activity, and (E) lateralized rhythmic delta activity.

Fig. 8

Funnel plots of the meta-analysis of (A) focal slowing, (B) epileptiform discharges, (C) electrographic seizure, and (D) electrographic status epilepticus.

Funnel plots of the meta-analysis of (A) abnormal background activity, (B) generalized slowing, (C) generalized periodic discharges, (D) generalized rhythmic delta activity, and (E) lateralized rhythmic delta activity. Funnel plots of the meta-analysis of (A) focal slowing, (B) epileptiform discharges, (C) electrographic seizure, and (D) electrographic status epilepticus.

Discussion

In this analysis, using the methodology of systematic review and meta-analysis, we have shown the comprehensive and quantitative analysis of the proportion of EEG findings in patients with COVID-19 who underwent EEG tests. We found that the proportion of abnormal background activity was exceedingly high at 96.1%. This result suggests that patients infected with COVID-19 who required EEG may likely have encephalopathy. In fact, the most common indication for EEG was altered mental status (210/307; 68.4%). Symptoms such as fever, hypoxia, and sedation may cause encephalopathy. Furthermore, encephalopathy associated with COVID-19 might be caused by any of the three pathways as follows: (1) indirect immune-mediated responses such as a cytokine storm, (2) direct central nervous system invasion by the virus, and (3) damage to the neural cells through angiotensin-converting enzyme 2 (ACE2) receptors [27]. In addition, we found discontinuous/burst suppression/background suppression and GPDs in 5.33% and 16.5% of the patients, respectively. In general, GPDs are seen in only 1% of routine EEGs; however, these are seen in up to 20% of cases with severe post-anoxic encephalopathy [28]. Furthermore, many patients in the intensive care unit were included in our study. Hence, patients with COVID-19 who required EEG may likely have severe COVID-19 infection and/or severe encephalopathy. Alternatively, EEGs might have been selectively administered to more critically ill patients due to infection prevention to medical providers and medical resource limitations during the COVID-19 pandemic [29]. Our results showed that focal EEG abnormalities were not specific. Although focal slowing was seen in 8.65% of the cases, most of the included studies (9/12; 75.0%) did not describe the detailed location of the focal abnormalities. Some of them described that focal sharp/slow waves were seen in the frontal, central, and the right posterior quadrant; however, these were small in number and were inconsistent [7], [17], [23]. In addition, LPD and LRDA were infrequent. Complications of COVID-19, such as stroke, vasculitis, or encephalitis, might cause focal abnormalities [3]; however, focal findings on the EEG may also be affected by the patient’s preexisting chronic neurological diseases or past medical history of brain disease. We also found that EDs were present in 20.3% of patients. The causes of the ED findings in patients with COVID-19 may include acute symptomatic seizure, de novo epileptogenicity, or preexisting epilepsy with or without exacerbation. In fact, the proportion of EDs varied between patients with a history of epilepsy or seizures (59.5%) and those without them (22.4%). One study showed that a history of epilepsy has an increased risk of EDs [21]; however, other included studies were not properly designed to compare epileptiform discharge rates between patients with epilepsy and those without epilepsy. In addition, there might be an EEG ordering bias in which patients with epilepsy are given priority to take EEG in order to avoid unnecessary exposure of health-care workers to COVID-19. Therefore, our study cannot conclude that epileptiform discharges are more common in patients with epilepsy. Furthermore, it is not known whether epileptiform discharges in patients with epilepsy are increased by the COVID-19 infection. However, infection is widely known as a common precipitating factor for seizures in patients with epilepsy [30]. A well-designed study to determine whether COVID-19 infection increases epileptiform discharges is needed. The other major finding of our study was that the proportion of seizures and status epilepticus on EEG was low at 2.05% and 0.80%, respectively. The proportions of clinical seizures and status epilepticus in patients with COVID-19 have been reported to be 0.08–0.5% and 0.03%, respectively [2], [31]. On the contrary, suspicious seizure episodes were a common indication for EEG in the studies included in this meta-analysis. Although our study included a relatively large number of patients with clinical seizures or status epilepticus episodes, seizures and status epilepticus on EEG were rare. Hence, patients with COVID-19 having both clinical and electrographic seizures/status epilepticus might be rare. Although not to be taken lightly, the data showing low rates of seizures and status epilepticus on EEG might be helpful evidence for clinicians, especially in situations with limited medical resources, limiting the indication of EEG tests. Two systematic review studies with similar clinical questions have been previously reported [32], [33]. Our meta-analysis provided additional value to those studies. Our findings were consistent with those of previous studies showing that abnormal background activity was the most common finding, and seizure/status epilepticus was infrequent. However, this study has several limitations. First, we included only studies written in English. Moreover, all included studies were reported from either the USA or Europe. Hence, there might be a selection bias, and the results cannot be generalized to other regions. Second, we did not include preprint articles in this meta-analysis. Although we searched for unpublished studies using ClinicalTrials.gov, there might have been unpublished studies in MEDLINE or CENTRAL that could have been included. Third, we considered undescribed findings as negative findings in studies with individual EEG reports. Some infrequent or less critical findings such as focal slowing might have been overlooked or unreported. Hence, some findings might have been underestimated. Fourth, the patient characteristics and clinical settings, such as montage, timing, interpretation, and duration of EEG, COVID-19 severity, and treatment of COVID-19 patients varied across each study. In fact, there was heterogenicity in the ranges of abnormal background activity, generalized slowing, GPDs, GRDA, focal slowing, and EDs, EDs in patients without a history of epilepsy or seizure, seizure, which might support the possibility of these limitations. Finally, there was a significant publication bias for status epilepticus. This might be because small case series are likely to report status epilepticus.

Conclusion

In conclusion, our findings suggest that the proportion of abnormal background activity in patients with COVID-19 was high (96.1%). Epileptiform discharges were present in 20.3% of the cases and the proportion varied between people who had a history of epilepsy or seizures and those who did not. However, the proportion of seizures and status epilepticus on EEG was low (2.05% and 0.80%, respectively).

Declarations

Conflicts of interest/Competing interests: The authors declare that they have no conflicts of interest. Ethics approval: Waived because of the nature of the article: A systematic review and meta-analysis. Consent to participate: Waived because of the nature of the article: A systematic review and meta-analysis. Consent for publication: All authors approve publication of the article. Consent from patients was waived because this article does not include personal details which allow patient identification. Availability of data and material: Data will be made available on reasonable request. Authors’ contributions: All authors contributed to study conception and design. Takafumi Kubota and Prasannakumar Gajera obtained and analyzed the data. All authors discussed any discrepancies found and results obtained. Takafumi Kubota drafted the manuscript. Takafumi Kubota and Prasannakumar Gajera made the tables and figures. Naoto Kuroda and Prasannakumar Gajera critically revised the work. All authors read and approved the final version of the manuscript.
  21 in total

Review 1.  Acute to Chronic Electro-Clinical Manifestations of Neuro-COVID and the Long-Haul Consequences in People With Epilepsy: A Review.

Authors:  Anna Milan; Philippe Salles; Carolina Pelayo; Reinaldo Uribe-San-Martin
Journal:  Cureus       Date:  2022-06-16

2.  Non-Invasive Multimodal Neuromonitoring in Non-Critically Ill Hospitalized Adult Patients With COVID-19: A Systematic Review and Meta-Analysis.

Authors:  Denise Battaglini; Lavienraj Premraj; Samuel Huth; Jonathon Fanning; Glenn Whitman; Rakesh C Arora; Judith Bellapart; Diego Bastos Porto; Fabio Silvio Taccone; Jacky Y Suen; Gianluigi Li Bassi; John F Fraser; Rafael Badenes; Sung-Min Cho; Chiara Robba
Journal:  Front Neurol       Date:  2022-04-14       Impact factor: 4.086

Review 3.  SARS-CoV-2 Infection: Symptoms of the Nervous System and Implications for Therapy in Neurological Disorders.

Authors:  Jacek Losy
Journal:  Neurol Ther       Date:  2020-11-23

Review 4.  Epilepsy and COVID-19: Updated evidence and narrative review.

Authors:  Naoto Kuroda
Journal:  Epilepsy Behav       Date:  2021-01-13       Impact factor: 3.337

5.  Association of Clinical, Biological, and Brain Magnetic Resonance Imaging Findings With Electroencephalographic Findings for Patients With COVID-19.

Authors:  Virginie Lambrecq; Aurélie Hanin; Esteban Munoz-Musat; Lydia Chougar; Salimata Gassama; Cécile Delorme; Louis Cousyn; Alaina Borden; Maria Damiano; Valerio Frazzini; Gilles Huberfeld; Frank Landgraf; Vi-Huong Nguyen-Michel; Phintip Pichit; Aude Sangare; Mario Chavez; Capucine Morélot-Panzini; Elise Morawiec; Mathieu Raux; Charles-Edouard Luyt; Pierre Rufat; Damien Galanaud; Jean-Christophe Corvol; Catherine Lubetzki; Benjamin Rohaut; Sophie Demeret; Nadya Pyatigorskaya; Lionel Naccache; Vincent Navarro
Journal:  JAMA Netw Open       Date:  2021-03-01

Review 6.  Evaluation and Treatment of Seizures and Epilepsy During the COVID-19 Pandemic.

Authors:  Jacob Pellinen; Manisha Gupte Holmes
Journal:  Curr Neurol Neurosci Rep       Date:  2022-01-26       Impact factor: 6.030

7.  The Effective Cognitive Assessment and Training Methods for COVID-19 Patients With Cognitive Impairment.

Authors:  Dong Wen; Jian Xu; Zhonglin Wu; Yijun Liu; Yanhong Zhou; Jingjing Li; Shaochang Wang; Xianlin Dong; M Iqbal Saripan; Haiqing Song
Journal:  Front Aging Neurosci       Date:  2022-01-11       Impact factor: 5.750

8.  Early Neurorehabilitation and Recovery from Disorders of Consciousness After Severe COVID-19.

Authors:  Lindsey Gurin; Megan Evangelist; Patricia Laverty; Kaitlin Hanley; John Corcoran; Jodi Herbsman; Brian Im; Jennifer Frontera; Steven Flanagan; Steven Galetta; Ariane Lewis
Journal:  Neurocrit Care       Date:  2021-10-05       Impact factor: 3.532

Review 9.  Neuroinflammation: A Signature or a Cause of Epilepsy?

Authors:  Enrico Pracucci; Vinoshene Pillai; Didi Lamers; Riccardo Parra; Silvia Landi
Journal:  Int J Mol Sci       Date:  2021-06-29       Impact factor: 5.923

10.  Retrospective Analysis of EEG in Patients With COVID-19: EEG Recording in Acute and Follow-up Phases.

Authors:  Isabel Sáez-Landete; Adriana Gómez-Domínguez; Beatriz Estrella-León; Alba Díaz-Cid; Olga Fedirchyk; Marta Escribano-Muñoz; Antonio Pedrera-Mazarro; Guillermo Martín-Palomeque; Guillermo Garcia-Ribas; Fernando Rodríguez-Jorge; Gloria Santos-Pérez; Daniel Lourido-García; Ignacio Regidor-BaillyBailliere
Journal:  Clin EEG Neurosci       Date:  2021-07-28       Impact factor: 1.843

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