Subacute encephalopathy and seizures in alcoholics (SESA) presenting with non-convulsive status epilepticus

AbstractSubacute encephalopathy with seizures in chronic alcoholism (SESA) was first described in 1981 by Niedermeyer who reported alcoholic patients presenting with confusion, seizures and focal neurological deficits and is quite distinct from patients presenting with typical alcohol withdrawal seizures. EEG often reveals periodic discharges and spikes, but SESA presenting with non-convulsive status epilepticus has rarely been described.We report a case of SESA with non-convulsive status epilepticus in a patient who was initially suspected of having a typical alcohol withdrawal seizure.A 61 year old woman with a history of chronic alcoholism was admitted at an outside hospital for confusion thought to be secondary to an alcohol withdrawal seizure. She had right hemiparesis and later developed right facial twitching that did not respond to intravenous fosphenytoin and levetiracetam. She was transferred for further management. Upon arrival, lorazepam and fosphenytoin were given and right face clonic movements resolved. However, continuous EEG monitoring revealed ongoing non-convulsive status epilepticus (NCSE). Following treatment with IV valproate and lacosamide, there was resolution of NCSE.SESA is likely an under recognized clinical syndrome that is quite distinct from typical alcohol withdrawal seizures and requires a different diagnostic and management approach. NCSE is likely to account for the encephalopathy and focal neurological deficits seen in patients presenting with the clinical syndrome of SESA. Therefore, a high degree of suspicion is warranted and continuous EEG monitoring is recommended for alcoholic patients with encephalopathy and focal neurological deficits

Association of an Electroencephalography-Based Risk Score With Seizure Probability in Hospitalized Patients.

IMPORTANCE: Continuous electroencephalography (EEG) use in critically ill patients is expanding. There is no validated method to combine risk factors and guide clinicians in assessing seizure risk. OBJECTIVE: To use seizure risk factors from EEG and clinical history to create a simple scoring system associated with the probability of seizures in patients with acute illness. DESIGN, SETTING, AND PARTICIPANTS: We used a prospective multicenter (Emory University Hospital, Brigham and Womens Hospital, and Yale University Hospital) database containing clinical and electrographic variables on 5427 continuous EEG sessions from eligible patients if they had continuous EEG for clinical indications, excluding epilepsy monitoring unit admissions. We created a scoring system model to estimate seizure risk in acutely ill patients undergoing continuous EEG. The model was built using a new machine learning method (RiskSLIM) that is designed to produce accurate, risk-calibrated scoring systems with a limited number of variables and small integer weights. We validated the accuracy and risk calibration of our model using cross-validation and compared its performance with models built with state-of-the-art logistic regression methods. The database was developed by the Critical Care EEG Research Consortium and used data collected over 3 years. The EEG variables were interpreted using standardized terminology by certified reviewers. EXPOSURES: All patients had more than 6 hours of uninterrupted EEG recordings. MAIN OUTCOMES AND MEASURES: The main outcome was the average risk calibration error. RESULTS: There were 5427 continuous EEGs performed on 4772 participants (2868 men, 49.9%; median age, 61 years) performed at 3 institutions, without further demographic stratification. Our final model, 2HELPS2B, had an area under the curve of 0.819 and average calibration error of 2.7% (95% CI, 2.0%-3.6%). It included 6 variables with the following point assignments: (1) brief (ictal) rhythmic discharges (B[I]RDs) (2 points); (2) presence of lateralized periodic discharges, lateralized rhythmic delta activity, or bilateral independent periodic discharges (1 point); (3) prior seizure (1 point); (4) sporadic epileptiform discharges (1 point); (5) frequency greater than 2.0 Hz for any periodic or rhythmic pattern (1 point); and (6) presence of plus features (superimposed, rhythmic, sharp, or fast activity) (1 point). The probable seizure risk of each score was 5% for a score of 0, 12% for a score of 1, 27% for a score of 2, 50% for a score of 3, 73% for a score of 4, 88% for a score of 5, and greater than 95% for a score of 6 or 7. CONCLUSIONS AND RELEVANCE: The 2HELPS2B model is a quick accurate tool to aid clinical judgment of the risk of seizures in critically ill patients

Sensitivity of quantitative EEG for seizure identification in the intensive care unit

Objective: To evaluate the sensitivity of quantitative EEG (QEEG) for electrographic seizure identification in the intensive care unit (ICU). Methods: Six-hour EEG epochs chosen from 15 patients underwent transformation into QEEG displays. Each epoch was reviewed in 3 formats: raw EEG, QEEG + raw, and QEEG-only. Epochs were also analyzed by a proprietary seizure detection algorithm. Nine neurophysiologists reviewed raw EEGs to identify seizures to serve as the gold standard. Nine other neurophysiologists with experience in QEEG evaluated the epochs in QEEG formats, with and without concomitant raw EEG. Sensitivity and false-positive rates (FPRs) for seizure identification were calculated and median review time assessed. Results: Mean sensitivity for seizure identification ranged from 51% to 67% for QEEG-only and 63%-68%for QEEG + raw. FPRs averaged 1/h for QEEG-only and 0.5/h for QEEG + raw. Mean sensitivity of seizure probability software was 26.2%-26.7%, with FPR of 0.07/h. Epochs with the highest sensitivities contained frequent, intermittent seizures. Lower sensitivities were seen with slow-frequency, low-amplitude seizures and epochs with rhythmic or periodic patterns. Median review times were shorter for QEEG (6 minutes) and QEEG + raw analysis (14.5 minutes) vs raw EEG (19 minutes; p = 0.00003). Conclusions: A panel of QEEG trends can be used by experts to shorten EEG reviewtime for seizure identification with reasonable sensitivity and low FPRs. The prevalence of false detections confirms that raw EEG review must be used in conjunction with QEEG. Studies are needed to identify optimal QEEG trend configurations and the utility of QEEG as a screening tool for non-EEG personnel. Classification of evidence review: This study provides Class II evidence that QEEG + raw interpreted by experts identifies seizures in patients in the ICU with a sensitivity of 63%-68% and FPR of 0.5 seizures per hour.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Randomized trial of lacosamide versus fosphenytoin for nonconvulsive seizures

© 2018 American Neurological Association Objective: The optimal treatment of nonconvulsive seizures in critically ill patients is uncertain. We evaluated the comparative effectiveness of the antiseizure drugs lacosamide (LCM) and fosphenytoin (fPHT) in this population. Methods: The TRENdS (Treatment of Recurrent Electrographic Nonconvulsive Seizures) study was a noninferiority, prospective, multicenter, randomized treatment trial of patients diagnosed with nonconvulsive seizures (NCSs) by continuous electroencephalography (cEEG). Treatment was randomized to intravenous (IV) LCM 400mg or IV fPHT 20mg phenytoin equivalents/kg. The primary endpoint was absence of electrographic seizures for 24 hours as determined by 1 blinded EEG reviewer. The frequency with which NCS control was achieved in each arm was compared, and the 90% confidence interval (CI) was determined. Noninferiority of LCM to fPHT was to be concluded if the lower bound of the CI for relative risk was \u3e0.8. Results: Seventy-four subjects were enrolled (37 LCM, 37 fPHT) between August 21, 2012 and December 20, 2013. The mean age was 63.6 years; 38 were women. Seizures were controlled in 19 of 30 (63.3%) subjects in the LCM arm and 16 of 32 (50%) subjects in the fPHT arm. LCM was noninferior to fPHT (p = 0.02), with a risk ratio of 1.27 (90% CI = 0.88–1.83). Treatment emergent adverse events (TEAEs) were similar in both arms, occurring in 9 of 35 (25.7%) LCM and 9 of 37 (24.3%) fPHT subjects (p = 1.0). Interpretation: LCM was noninferior to fPHT in controlling NCS, and TEAEs were comparable. LCM can be considered an alternative to fPHT in the treatment of NCSs detected on cEEG. Ann Neurol 2018;83:1174–1185

Consensus statement on continuous EEG in critically Ill adults and children, Part II: Personnel, technical specifications, and clinical practice

© 2015 by the American Clinical Neurophysiology Society.. Introduction: Critical Care Continuous EEG (CCEEG) is a common procedure to monitor brain function in patients with altered mental status in intensive care units. There is significant variability in patient populations undergoing CCEEG and in technical specifications for CCEEG performance. Methods: The Critical Care Continuous EEG Task Force of the American Clinical Neurophysiology Society developed expert consensus recommendations on the use of CCEEG in critically ill adults and children. Recommendations: The consensus panel describes the qualifications and responsibilities of CCEEG personnel including neurodiagnostic technologists and interpreting physicians. The panel outlines required equipment for CCEEG, including electrodes, EEG machine and amplifier specifications, equipment for polygraphic data acquisition, EEG and video review machines, central monitoring equipment, and network, remote access, and data storage equipment. The consensus panel also describes how CCEEG should be acquired, reviewed and interpreted. The panel suggests methods for patient selection and triage; initiation of CCEEG; daily maintenance of CCEEG; electrode removal and infection control; quantitative EEG techniques; EEG and behavioral monitoring by non-physician personnel; review, interpretation, and reports; and data storage protocols. Conclusion: Recommended qualifications for CCEEG personnel and CCEEG technical specifications will facilitate standardization of this emerging technolog

Consensus statement on continuous EEG in critically Ill adults and children, part I: Indications

© 2015 by the American Clinical Neurophysiology Society. Introduction: Critical Care Continuous EEG (CCEEG) is a common procedure to monitor brain function in patients with altered mental status in intensive care units. There is significant variability in patient populations undergoing CCEEG and in technical specifications for CCEEG performance. Methods: The Critical Care Continuous EEG Task Force of the American Clinical Neurophysiology Society developed expert consensus recommendations on the use of CCEEG in critically ill adults and children. Recommendations: The consensus panel recommends CCEEG for diagnosis of nonconvulsive seizures, nonconvulsive status epilepticus, and other paroxysmal events, and for assessment of the efficacy of therapy for seizures and status epilepticus. The consensus panel suggests CCEEG for identification of ischemia in patients at high risk for cerebral ischemia; for assessment of level of consciousness in patients receiving intravenous sedation or pharmacologically induced coma; and for prognostication in patients after cardiac arrest. For each indication, the consensus panel describes the patient populations for which CCEEG is indicated, evidence supporting use of CCEEG, utility of video and quantitative EEG trends, suggested timing and duration of CCEEG, and suggested frequency of review and interpretation. Conclusion: CCEEG has an important role in detection of secondary injuries such as seizures and ischemia in critically ill adults and children with altered mental statu

New-onset refractory status epilepticus: Etiology, clinical features, and outcome.

OBJECTIVES: The aims of this study were to determine the etiology, clinical features, and predictors of outcome of new-onset refractory status epilepticus. METHODS: Retrospective review of patients with refractory status epilepticus without etiology identified within 48 hours of admission between January 1, 2008, and December 31, 2013, in 13 academic medical centers. The primary outcome measure was poor functional outcome at discharge (defined as a score >3 on the modified Rankin Scale). RESULTS: Of 130 cases, 67 (52%) remained cryptogenic. The most common identified etiologies were autoimmune (19%) and paraneoplastic (18%) encephalitis. Full data were available in 125 cases (62 cryptogenic). Poor outcome occurred in 77 of 125 cases (62%), and 28 (22%) died. Predictors of poor outcome included duration of status epilepticus, use of anesthetics, and medical complications. Among the 63 patients with available follow-up data (median 9 months), functional status improved in 36 (57%); 79% had good or fair outcome at last follow-up, but epilepsy developed in 37% with most survivors (92%) remaining on antiseizure medications. Immune therapies were used less frequently in cryptogenic cases, despite a comparable prevalence of inflammatory CSF changes. CONCLUSIONS: Autoimmune encephalitis is the most commonly identified cause of new-onset refractory status epilepticus, but half remain cryptogenic. Outcome at discharge is poor but improves during follow-up. Epilepsy develops in most cases. The role of anesthetics and immune therapies warrants further investigation