The probability of seizures during continuous EEG monitoring in high-risk neonates.
Ontology highlight
ABSTRACT: Objective
We evaluated the impact of monitoring indication, early electroencephalography (EEG), and clinical features on seizure risk in all neonates undergoing continuous EEG (cEEG) monitoring following a standardized monitoring protocol.Methods
All cEEGs from unique neonates 34-48 weeks postmenstrual age monitored from 1/2011-10/2017 (n = 291) were included. We evaluated the impact of cEEG monitoring indication (acute neonatal encephalopathy [ANE], suspicious clinical events [SCEs], or other high-risk conditions [OHRs]), age, medication status, and early EEG abnormalities (including the presence of epileptiform discharges and abnormal background continuity, amplitude, asymmetry, asynchrony, excessive sharp transients, and burst suppression) on time to first seizure and overall seizure risk using Kaplan-Meier survival curves and multivariable Cox proportional hazards models.Results
Seizures occurred in 28% of high-risk neonates. Discontinuation of monitoring after 24 hours of seizure-freedom would have missed 8.5% of neonates with seizures. Overall seizure risk was lower in neonates monitored for ANE compared to OHR (P = .004) and trended lower compared to SCE (P = .097). The time course of seizure presentation varied by group, where the probability of future seizure was less than 1% after 17 hours of seizure-free monitoring in the SCE group, but required 42 hours in the OHR group, and 73 hours in the ANE group. The presence of early epileptiform discharges increased seizure risk in each group (ANE: adjusted hazard ratio [aHR] 4.32, 95% confidence interval [CI] 1.23-15.13, P = .022; SCE: aHR 10.95, 95% CI 4.77-25.14, P < 1e-07; OHR: aHR 56.90, 95% CI 10.32-313.72, P < 1e-05).Significance
Neonates who undergo cEEG are at high risk for seizures, and risk varies by monitoring indication and early EEG findings. Seizures are captured in nearly all neonates undergoing monitoring for SCE within 24 hours of cEEG monitoring. Neonates monitored for OHR and ANE can present with delayed seizures and require longer durations of monitoring. Early epileptiform discharges are the best early EEG feature to predict seizure risk.
SUBMITTER: Worden LT
PROVIDER: S-EPMC7083278 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:ObjectiveTo characterize the risk for seizures over time in relation to EEG findings in hospitalized adults undergoing continuous EEG monitoring (cEEG).MethodsRetrospective analysis of cEEG data and medical records from 625 consecutive adult inpatients monitored at a tertiary medical center. Using survival analysis methods, we estimated the time-dependent probability that a seizure will occur within the next 72-h, if no seizure has occurred yet, as a function of EEG abnormalities detected so far.ResultsSeizures occurred in 27% (168/625). The first seizure occurred early (<30min of monitoring) in 58% (98/168). In 527 patients without early seizures, 159 (30%) had early epileptiform abnormalities, versus 368 (70%) without. Seizures were eventually detected in 25% of patients with early epileptiform discharges, versus 8% without early discharges. The 72-h risk of seizures declined below 5% if no epileptiform abnormalities were present in the first two hours, whereas 16h of monitoring were required when epileptiform discharges were present. 20% (74/388) of patients without early epileptiform abnormalities later developed them; 23% (17/74) of these ultimately had seizures. Only 4% (12/294) experienced a seizure without preceding epileptiform abnormalities.ConclusionsSeizure risk in acute neurological illness decays rapidly, at a rate dependent on abnormalities detected early during monitoring. This study demonstrates that substantial risk stratification is possible based on early EEG abnormalities.SignificanceThese findings have implications for patient-specific determination of the required duration of cEEG monitoring in hospitalized patients.
| S-EPMC4289643 | biostudies-literature
Project description:ObjectiveThe aim of this multicentre study was to describe detailed characteristics of electrographic seizures in a cohort of neonates monitored with multichannel continuous electroencephalography (cEEG) in 6 European centres.MethodsNeonates of at least 36 weeks of gestation who required cEEG monitoring for clinical concerns were eligible, and were enrolled prospectively over 2 years from June 2013. Additional retrospective data were available from two centres for January 2011 to February 2014. Clinical data and EEGs were reviewed by expert neurophysiologists through a central server.ResultsOf 214 neonates who had recordings suitable for analysis, EEG seizures were confirmed in 75 (35%). The most common cause was hypoxic-ischaemic encephalopathy (44/75, 59%), followed by metabolic/genetic disorders (16/75, 21%) and stroke (10/75, 13%). The median number of seizures was 24 (IQR 9-51), and the median maximum hourly seizure burden in minutes per hour (MSB) was 21 min (IQR 11-32), with 21 (28%) having status epilepticus defined as MSB>30 min/hour. MSB developed later in neonates with a metabolic/genetic disorder. Over half (112/214, 52%) of the neonates were given at least one antiepileptic drug (AED) and both overtreatment and undertreatment was evident. When EEG monitoring was ongoing, 27 neonates (19%) with no electrographic seizures received AEDs. Fourteen neonates (19%) who did have electrographic seizures during cEEG monitoring did not receive an AED.ConclusionsOur results show that even with access to cEEG monitoring, neonatal seizures are frequent, difficult to recognise and difficult to treat.Oberservation study numberNCT02160171.
| S-EPMC6788873 | biostudies-literature
Project description:ObjectiveTo assess the risk factors for electrographic seizures among neonates treated with therapeutic hypothermia for hypoxic-ischemic encephalopathy (HIE).MethodsThree-center observational cohort study of 90 term neonates treated with hypothermia, monitored with continuous video-EEG (cEEG) within the first day of life (median age at onset of recording 9.5 hours, interquartile range 6.3-14.5), and continued for >24 hours (total recording 93.3 hours, interquartile range 80.1-112.8 among survivors). A pediatric electroencephalographer at each site reviewed cEEGs for electrographic seizures and initial EEG background category.ResultsA total of 43 (48%) had electrographic seizures, including 9 (10%) with electrographic status epilepticus. Abnormal initial EEG background classification (excessively discontinuous, depressed and undifferentiated, burst suppression, or extremely low voltage), but not clinical variables (including pH <6.8, base excess ≤-20, or 10-minute Apgar ≤ 3), was strongly associated with seizures.ConclusionsElectrographic seizures are common among neonates with HIE undergoing hypothermia and are difficult to predict based on clinical features. These results justify the recommendation for cEEG monitoring in neonates treated with hypothermia.
| S-EPMC4001204 | biostudies-literature
Project description:Background: Neonatal encephalopathy is caused by a wide variety of acute brain insults in newborns and presents with a spectrum of neurologic dysfunction, such as consciousness disturbance, seizures, and coma. The increased excitability in the neonatal brain appears to be highly susceptible to seizures after a variety of insults, and seizures may be the first clinical sign of a serious neurologic disorder. Subtle seizures are common in the neonatal period, and abnormal clinical paroxysmal events may raise the suspicion of neonatal seizures. Continuous video electroencephalographic (EEG) monitoring is the gold standard for the diagnosis of neonatal seizures. The aim of this study was to identify the prevalence of electrographic seizures and the impact of monitoring in neonates with a high risk of encephalopathy. Methods: We conducted this prospective cohort study in a tertiary neonatal intensive care unit over a 4-year period. Neonates with a high risk of encephalopathy who were receiving continuous video EEG monitoring were eligible. The patients were divided into 2 groups: (1) acute neonatal encephalopathy (ANE) and (2) other high-risk encephalopathy conditions (OHRs). The neonates’ demographic characteristics, etiologies, EEG background feature, presence of electrographic seizures and the impact of monitoring were analyzed. Results: A total of 71 neonates with a high risk of encephalopathy who received continuous video EEG monitoring were enrolled. In this consecutive cohort, 42 (59.2%) were monitored for ANE and 29 (40.8%) were monitored for OHRs. At the time of starting EEG monitoring, 54 (76.1%) of the neonates were term infants. The median gestational age at monitoring was 39 weeks (interquartile range, 37–41 weeks). The median total EEG monitoring duration was 64.7 h (interquartile range, 22.2–72.4 h). Electrographic seizures were captured in 25 of the 71 (35.2%) neonates, of whom 20 (80%) had electrographic-only seizures without clinical correlation. Furthermore, of these 20 neonates, 13 (65%) developed electrographic status epilepticus. Electrographic seizures were most commonly found in the ANE group (17, 40.5%) than in the OHRs group (8, 27.6%) (p = 0.013). Besides, normal/mild abnormality and inactive EEG background were less electrographic seizure than moderate and major abnormality EEG background (2 of 30, 6.7% vs. 23 of 41, 56.1%, p < 0.001). Finally, continuous video EEG monitoring excluded the diagnosis of electrographic seizures in two-thirds of the monitored neonates who had paroxysmal events mimicking seizures and led to a change in clinical management in 39.4% of the neonates. Conclusions: Our findings showed that monitoring could accurately detect seizures, and that it could be used to guide seizure medication management. Therefore, continuous video EEG monitoring has important clinical management implications in neonates with a high risk of encephalopathy.
| S-EPMC9221774 | biostudies-literature
Project description:ImportanceNeonates with hypoxic-ischemic encephalopathy (HIE) undergoing therapeutic hypothermia (TH) frequently experience seizures, which are associated with adverse outcomes. Efforts to rapidly identify seizures and reduce seizure burden may positively change neurologic and neurodevelopmental outcomes.ObjectiveTo describe the onset, treatment, and evolution of seizures in a large cohort of newborns with HIE during TH assisted by a telehealth model and remote neuromonitoring approach.Design, setting, and participantsThis was a prospective, observational, multicenter cohort study performed between July 2017 and December 2021 in 32 hospitals in Brazil. Participants were newborns with HIE meeting eligibility criteria and receiving TH. Data were analyzed from November 2022 to April 2023.ExposureInfants with HIE receiving TH were remotely monitored with 3-channel amplitude-integrated electroencephalography (aEEG) including raw tracing and video imaging, and bedside clinicians received assistance from trained neonatologists and neurologists.Main outcomes and measuresData on modified Sarnat examination, presence, timing and seizure type, aEEG background activity, sleep-wake cycling, and antiepileptic drugs used were collected. Descriptive statistical analysis was used with independent t test, χ2, Mann-Whitney test, and post hoc analyses applied for associations.ResultsA total of 872 cooled newborns were enrolled; the median (IQR) gestational age was 39 (38-40) weeks, 518 (59.4%) were male, and 59 (6.8%) were classified as having mild encephalopathy by modified Sarnat examination, 504 (57.8%) as moderate, and 180 (20.6%) as severe. Electrographic seizures were identified in 296 newborns (33.9%), being only electrographic in 213 (71.9%) and clinical followed by electroclinical uncoupling in 50 (16.9%). Early abnormal background activity had a significant association with seizures. Infants with flat trace had the highest rate of seizures (58 infants [68.2%]) and the greatest association with the incidence of seizures (odds ratio [OR], 12.90; 95% CI, 7.57-22.22) compared with continuous normal voltage. The absence of sleep-wake cycling was also associated with a higher occurrence of seizures (OR, 2.22; 95% CI, 1.67-2.96). Seizure onset was most frequent between 6 and 24 hours of life (181 infants [61.1%]); however, seizure occurred in 34 infants (11.5%) during rewarming. A single antiepileptic drug controlled seizures in 192 infants (64.9%). The first line antiepileptic drug was phenobarbital in 294 (99.3%).Conclusions and relevanceIn this cohort study of newborns with HIE treated with TH, electrographic seizure activity occurred in 296 infants (33.9%) and was predominantly electrographic. Seizure control was obtained with a single antiepileptic drug in 192 infants (64.9%). These findings suggest neonatal neurocritical care can be delivered at remote limited resource hospitals due to innovations in technology and telehealth.
| S-EPMC10652158 | biostudies-literature
Project description:Absence seizures-generalized rhythmic spike-and-wave discharges (SWDs) are the defining property of childhood (CAE) and juvenile (JAE) absence epilepsies. Such seizures are the most compelling examples of pathological neuronal hypersynchrony. All the absence detection algorithms proposed so far have been derived from the properties of individual SWDs. In this work, we investigate EEG phase synchronization in patients with CAE/JAE and healthy subjects to explore the possibility of using the wavelet phase synchronization index to detect seizures and quantify their disorganization (fragmentation). The overlap of the ictal and interictal probability density functions was high enough to preclude effective seizure detection based solely on changes in EEG synchronization. We used a machine learning classifier with the phase synchronization index (calculated for 1 s data segments with 0.5 s overlap) and the normalized amplitude as features to detect generalized SWDs. Using 19 channels (10-20 setup), we identified 99.2% of absences. However, the overlap of the segments classified as ictal with seizures was only 83%. The analysis showed that seizures were disorganized in approximately half of the 65 subjects. On average, generalized SWDs lasted about 80% of the duration of abnormal EEG activity. The disruption of the ictal rhythm can manifest itself as the disappearance of epileptic spikes (with high-amplitude delta waves persisting), transient cessation of epileptic discharges, or loss of global synchronization. The detector can analyze a real-time data stream. Its performance is good for a six-channel setup (Fp1, Fp2, F7, F8, O1, O2), which can be implemented as an unobtrusive EEG headband. False detections are rare for controls and young adults (0.03% and 0.02%, respectively). In patients, they are more frequent (0.5%), but in approximately 82% cases, classification errors are caused by short epileptiform discharges. Most importantly, the proposed detector can be applied to parts of EEG with abnormal EEG activity to quantitatively determine seizure fragmentation. This property is important because a previous study reported that the probability of disorganized discharges is eight times higher in JAE than in CAE. Future research must establish whether seizure properties (frequency, length, fragmentation, etc.) and clinical characteristics can help distinguish CAE and JAE.
| S-EPMC10317177 | biostudies-literature
Project description:BackgroundProlonged seizures generate cerebral hypoxia and increased intracranial pressure, resulting in an increased risk of neurological deterioration, increased long-term morbidity, and shorter survival. Seizures should be recognized early and treated promptly. The aim of the study was to investigate the occurrence of postoperative seizures in patients undergoing craniotomy for primary brain tumors and to determine if non-convulsive seizures could explain some of the postoperative neurological deterioration that may occur after surgery.MethodsA single-center prospective study of 100 patients with suspected glioma. Participants were studied with EEG and video recording for at least 24 h after surgery.ResultsSeven patients (7%) displayed seizure activity on EEG recording within 24 h after surgery and another two patients (2%) developed late seizures. One of the patients with early seizures also developed late seizures. In five patients (5%), there were non-convulsive seizures. Four of these patients had a combination of clinically overt and non-convulsive seizures and in one patient, all seizures were non-convulsive. The non-convulsive seizures accounted for the majority of total seizure time in those patients. Non-convulsive seizures could not explain six cases of unexpected postoperative neurological deterioration. Postoperative ischemic lesions were more common in patients with early postoperative seizures.ConclusionsEarly seizures, including non-convulsive, occurred in 7% of our patients. Within this group, non-convulsive seizure activity had longer durations than clinically overt seizures, but only 1% of patients had exclusively non-convulsive seizures. Seizures were not associated with unexpected neurological deterioration.
| S-EPMC6704081 | biostudies-literature
Project description:Continuous electroencephalogram monitoring is associated with lower mortality in critically ill patients; however, it is underused due to the resource-intensive nature of manually interpreting prolonged streams of continuous electroencephalogram data. Here, we present a novel real-time, machine learning-based alerting and monitoring system for epilepsy and seizures that dramatically reduces the amount of manual electroencephalogram review.MethodsWe developed a custom data reduction algorithm using a random forest and deployed it within an online cloud-based platform, which streams data and communicates interactively with caregivers via a web interface to display algorithm results. We developed real-time, machine learning-based alerting and monitoring system for epilepsy and seizures on continuous electroencephalogram recordings from 77 patients undergoing routine scalp ICU electroencephalogram monitoring and tested it on an additional 20 patients.ResultsWe achieved a mean seizure sensitivity of 84% in cross-validation and 85% in testing, as well as a mean specificity of 83% in cross-validation and 86% in testing, corresponding to a high level of data reduction. This study validates a platform for machine learning-assisted continuous electroencephalogram analysis and represents a meaningful step toward improving utility and decreasing cost of continuous electroencephalogram monitoring. We also make our high-quality annotated dataset of 97 ICU continuous electroencephalogram recordings public for others to validate and improve upon our methods.
| S-EPMC8280012 | biostudies-literature
Project description:ObjectiveTo determine whether screening continuous EEG monitoring (cEEG) is associated with greater odds of treatment success for neonatal seizures.MethodsWe included term neonates with acute symptomatic seizures enrolled in the Neonatal Seizure Registry (NSR), a prospective, multicenter cohort of neonates with seizures. We compared 2 cEEG approaches: (1) screening cEEG, initiated for indications of encephalopathy or paralysis without suspected clinical seizures; and (2) confirmatory cEEG, initiated for the indication of clinical events suspicious for seizures, either alone or in addition to other indications. The primary outcome was successful response to initial seizure treatment, defined as seizures resolved without recurrence within 30 minutes after initial loading dose of antiseizure medicine. Multivariable logistic regression analyses assessed the association between cEEG approach and successful seizure treatment.ResultsAmong 514 neonates included, 161 (31%) had screening cEEG and 353 (69%) had confirmatory cEEG. Neonates with screening cEEG had a higher proportion of successful initial seizure treatment than neonates with confirmatory cEEG (39% vs 18%; p < 0.0001). After adjusting for covariates, there remained a greater odds ratio (OR) for successful initial seizure treatment in the screening vs confirmatory cEEG groups (adjusted OR 2.44, 95% confidence interval 1.45-4.11, p = 0.0008).ConclusionsThese findings provide evidence from a large, contemporary cohort of neonates that a screening cEEG approach may improve odds of successful treatment of acute seizures.Classification of evidenceThis study provides Class III evidence that for neonates a screening cEEG approach, compared to a confirmatory EEG approach, increases the probability of successful treatment of acute seizures.
| S-EPMC8424499 | biostudies-literature
Project description:ObjectiveTo determine whether the absence of early epileptiform abnormalities predicts absence of later seizures on continuous EEG monitoring of hospitalized patients.MethodsWe retrospectively reviewed 242 consecutive patients without a prior generalized convulsive seizure or active epilepsy who underwent continuous EEG monitoring lasting at least 18 hours for detection of nonconvulsive seizures or evaluation of unexplained altered mental status. The findings on the initial 30-minute screening EEG, subsequent continuous EEG recordings, and baseline clinical data were analyzed. We identified early EEG findings associated with absence of seizures on subsequent continuous EEG.ResultsSeizures were detected in 70 (29%) patients. A total of 52 patients had their first seizure in the initial 30 minutes of continuous EEG monitoring. Of the remaining 190 patients, 63 had epileptiform discharges on their initial EEG, 24 had triphasic waves, while 103 had no epileptiform abnormalities. Seizures were later detected in 22% (n = 14) of studies with epileptiform discharges on their initial EEG, vs 3% (n = 3) of the studies without epileptiform abnormalities on initial EEG (p < 0.001). In the 3 patients without epileptiform abnormalities on initial EEG but with subsequent seizures, the first epileptiform discharge or electrographic seizure occurred within the first 4 hours of recording.ConclusionsIn patients without epileptiform abnormalities during the first 4 hours of recording, no seizures were subsequently detected. Therefore, EEG features early in the recording may indicate a low risk for seizures, and help determine whether extended monitoring is necessary.
| S-EPMC3475619 | biostudies-literature